> ## Documentation Index
> Fetch the complete documentation index at: https://docs.tensor9.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Bedrock (LLM inference) costs

> Compare Bedrock (LLM inference) backend choices using explicit service-adapter planning assumptions.

Tensor9 BYOC planning comparisons for `aws::1.0.0::bedrock`, with backend choices shown together. Read [how to think about service-adapter costs](/byoc/service-adapters/debugging/costs/overview) for price scope and capacity qualification, or return to [additional services](/byoc/service-adapters/debugging/costs/additional-services).

## Bedrock model inference → Anthropic Messages API

Origin API: `aws::1.0.0::bedrock`. Target backend: `anthropic::1.0.0::messages`.

**Planning estimate with editable assumptions.** Unit rates, workload amplification and capacity assumptions are educated guesses awaiting verification. The displayed amounts are planning estimates, not verified provider list-price quotes or benchmark-qualified capacity. Region names identify the authored scenario assumptions.

### Bedrock model inference · Input tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.

| Input tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 375 | Planning native backend | 375 | 0 |
| 10 | 453.84 | Planning native backend | 453.84 | 0 |
| 100 | 1163.4 | Planning native backend | 1163.4 | 0 |
| 1000 | 8259 | Planning native backend | 8259 | 0 |
| 10000 | 79215 | Planning native backend | 79215 | 0 |
| 100000 | 788775 | Planning native backend | 788775 | 0 |

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning native backend | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning native backend | Target / origin input tokens | 1 | multiplier |
| Planning native backend | Target / origin output tokens | 1 | multiplier |
| Planning native backend | Target price guess · read | 0 | USD/read |
| Planning native backend | Target price guess · write | 0 | USD/write |
| Planning native backend | Target price guess · provider operation | 0 | USD/provider operation |
| Planning native backend | Target price guess · GiB-month | 0 | USD/GiB-month |
| Planning native backend | Target price guess · published GiB | 0 | USD/published GiB |
| Planning native backend | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning native backend | Target price guess · network GiB | 0 | USD/network GiB |
| Planning native backend | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning native backend | Target price guess · vCPU-hour | 0 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning native backend | Target price guess · resource-month | 0 | USD/resource-month |
| Planning native backend | Target price guess · input token | 0.000003 | USD/input token |
| Planning native backend | Target price guess · output token | 0.000015 | USD/output token |
| Planning native backend | Approximate target service minimum | 0 | USD/month |
| Planning native backend | Minimum primary CPU | 2 | vCPU |
| Planning native backend | Minimum primary RAM | 8 | GiB |
| Planning native backend | Minimum primary disk | 100 | GiB |
| Planning native backend | Additional full-price standby copy | 0 | 0 or 1 |
| Planning native backend | Allocated share of provisioned cost | 1 | fraction |
| Planning native backend | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning native backend | Planning peak / mean work | 2 | multiplier |
| Planning native backend | Planning primary CPU utilization | 0.7 | fraction |
| Planning native backend | Resident state reserved in RAM | 0.1 | fraction |
| Planning native backend | Planning disk utilization | 0.7 | fraction |
| Planning native backend | Maintenance and log disk reserve | 20 | GiB |
| Planning native backend | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning native backend | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning native backend | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning native backend | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning native backend | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Input and output token tariffs remain distinct. These illustrative rates name no selected model SKU and establish no equivalent output quality or tokenizer.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-ccde7cd673441e8ba203e027d2e5f895e072eb7c` / `2026-10-18.planning.1`. Curve: `workload-1`.

### Bedrock model inference · Output tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.

| Output tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 300 | Planning native backend | 300 | 0 |
| 10 | 694.2 | Planning native backend | 694.2 | 0 |
| 100 | 4242 | Planning native backend | 4242 | 0 |
| 1000 | 39720 | Planning native backend | 39720 | 0 |
| 10000 | 394500 | Planning native backend | 394500 | 0 |
| 100000 | 3942300 | Planning native backend | 3942300 | 0 |

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning native backend | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning native backend | Target / origin input tokens | 1 | multiplier |
| Planning native backend | Target / origin output tokens | 1 | multiplier |
| Planning native backend | Target price guess · read | 0 | USD/read |
| Planning native backend | Target price guess · write | 0 | USD/write |
| Planning native backend | Target price guess · provider operation | 0 | USD/provider operation |
| Planning native backend | Target price guess · GiB-month | 0 | USD/GiB-month |
| Planning native backend | Target price guess · published GiB | 0 | USD/published GiB |
| Planning native backend | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning native backend | Target price guess · network GiB | 0 | USD/network GiB |
| Planning native backend | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning native backend | Target price guess · vCPU-hour | 0 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning native backend | Target price guess · resource-month | 0 | USD/resource-month |
| Planning native backend | Target price guess · input token | 0.000003 | USD/input token |
| Planning native backend | Target price guess · output token | 0.000015 | USD/output token |
| Planning native backend | Approximate target service minimum | 0 | USD/month |
| Planning native backend | Minimum primary CPU | 2 | vCPU |
| Planning native backend | Minimum primary RAM | 8 | GiB |
| Planning native backend | Minimum primary disk | 100 | GiB |
| Planning native backend | Additional full-price standby copy | 0 | 0 or 1 |
| Planning native backend | Allocated share of provisioned cost | 1 | fraction |
| Planning native backend | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning native backend | Planning peak / mean work | 2 | multiplier |
| Planning native backend | Planning primary CPU utilization | 0.7 | fraction |
| Planning native backend | Resident state reserved in RAM | 0.1 | fraction |
| Planning native backend | Planning disk utilization | 0.7 | fraction |
| Planning native backend | Maintenance and log disk reserve | 20 | GiB |
| Planning native backend | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning native backend | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning native backend | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning native backend | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning native backend | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Input and output token tariffs remain distinct. These illustrative rates name no selected model SKU and establish no equivalent output quality or tokenizer.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-ccde7cd673441e8ba203e027d2e5f895e072eb7c` / `2026-10-18.planning.1`. Curve: `workload-2`.

## Bedrock model inference → Azure RAI Content Filter Policy

Origin API: `aws::1.0.0::bedrock`. Target backend: `azure::1.0.0::rai-policy`.

**Planning estimate with editable assumptions.** Unit rates, workload amplification and capacity assumptions are educated guesses awaiting verification. The displayed amounts are planning estimates, not verified provider list-price quotes or benchmark-qualified capacity. Region names identify the authored scenario assumptions.

**Native or deployment mapping.** This mapping provisions an Azure content-filter policy. A policy is not a Bedrock inference endpoint; inference adapters have their own operation-specific terms. Cost estimates describe the selected service resources; operation coverage remains separate.

### Bedrock model inference · Input tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.
Estimated allocation from planning assumptions; not benchmark calibrated. Only discrete samples are shown. Unpriced means no target quote or cost difference is available within the sizing policy.

| Input tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 375 | Planning allocation · one copy | Unpriced | Unavailable |
| 0 | 375 | Planning allocation · two copies | Unpriced | Unavailable |
| 10 | 453.84 | Planning allocation · one copy | Unpriced | Unavailable |
| 10 | 453.84 | Planning allocation · two copies | Unpriced | Unavailable |
| 100 | 1163.4 | Planning allocation · one copy | Unpriced | Unavailable |
| 100 | 1163.4 | Planning allocation · two copies | Unpriced | Unavailable |
| 1000 | 8259 | Planning allocation · one copy | Unpriced | Unavailable |
| 1000 | 8259 | Planning allocation · two copies | Unpriced | Unavailable |
| 10000 | 79215 | Planning allocation · one copy | Unpriced | Unavailable |
| 10000 | 79215 | Planning allocation · two copies | Unpriced | Unavailable |
| 100000 | 788775 | Planning allocation · one copy | Unpriced | Unavailable |
| 100000 | 788775 | Planning allocation · two copies | Unpriced | Unavailable |

**Estimated allocation from planning assumptions; not benchmark calibrated.**

The sizing policy grows compute with translated work and peak headroom, memory with compute and working set, and disk with resident working state and reserve. Monthly usage is distinct from resident data; each workload's assumptions define the translation. HA changes pricing, not this policy's throughput estimate. Unpriced workloads exceed the policy's configuration range; no silent vertical cap or automatic sharding is assumed.

| Sample / scenario | Basis | Mean / peak work/s | Required vCPU | Allocated vCPU | Memory GiB | SSD GiB | Resident GiB | Policy | Constraints |
| - | - | -: | -: | -: | -: | -: | -: | - | - |
| 0 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 0 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 1000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 1000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |

* Authored operation throughput, peak and working-set assumptions are not benchmark-calibrated.
* Stored GiB already includes the origin family's physical footprint assumptions; no second storage amplification is applied.
* The generic operations/vCPU coefficient supplies a provisional compute requirement alongside explicit resource-hour minima.
* Copies and allocation fractions change cost only; they do not increase modeled primary capacity.

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning allocation · one copy | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning allocation · one copy | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning allocation · one copy | Target / origin input tokens | 1 | multiplier |
| Planning allocation · one copy | Target / origin output tokens | 1 | multiplier |
| Planning allocation · one copy | Target price guess · read | 0 | USD/read |
| Planning allocation · one copy | Target price guess · write | 0 | USD/write |
| Planning allocation · one copy | Target price guess · provider operation | 0 | USD/provider operation |
| Planning allocation · one copy | Target price guess · GiB-month | 0.17 | USD/GiB-month |
| Planning allocation · one copy | Target price guess · published GiB | 0 | USD/published GiB |
| Planning allocation · one copy | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning allocation · one copy | Target price guess · network GiB | 0.09 | USD/network GiB |
| Planning allocation · one copy | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning allocation · one copy | Target price guess · vCPU-hour | 0.05 | USD/vCPU-hour |
| Planning allocation · one copy | Target price guess · GiB-hour | 0.006 | USD/GiB-hour |
| Planning allocation · one copy | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning allocation · one copy | Target price guess · resource-month | 0 | USD/resource-month |
| Planning allocation · one copy | Target price guess · input token | 0 | USD/input token |
| Planning allocation · one copy | Target price guess · output token | 0 | USD/output token |
| Planning allocation · one copy | Approximate target service minimum | 0 | USD/month |
| Planning allocation · one copy | Minimum primary CPU | 2 | vCPU |
| Planning allocation · one copy | Minimum primary RAM | 8 | GiB |
| Planning allocation · one copy | Minimum primary disk | 100 | GiB |
| Planning allocation · one copy | Additional full-price standby copy | 0 | 0 or 1 |
| Planning allocation · one copy | Allocated share of provisioned cost | 1 | fraction |
| Planning allocation · one copy | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning allocation · one copy | Planning peak / mean work | 2 | multiplier |
| Planning allocation · one copy | Planning primary CPU utilization | 0.7 | fraction |
| Planning allocation · one copy | Resident state reserved in RAM | 0.1 | fraction |
| Planning allocation · one copy | Planning disk utilization | 0.7 | fraction |
| Planning allocation · one copy | Maintenance and log disk reserve | 20 | GiB |
| Planning allocation · one copy | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning allocation · one copy | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning allocation · one copy | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning allocation · one copy | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning allocation · one copy | Dependent object sink write price guess | 0.000005 | USD/write |
| Planning allocation · two copies | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning allocation · two copies | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning allocation · two copies | Target / origin input tokens | 1 | multiplier |
| Planning allocation · two copies | Target / origin output tokens | 1 | multiplier |
| Planning allocation · two copies | Target price guess · read | 0 | USD/read |
| Planning allocation · two copies | Target price guess · write | 0 | USD/write |
| Planning allocation · two copies | Target price guess · provider operation | 0 | USD/provider operation |
| Planning allocation · two copies | Target price guess · GiB-month | 0.17 | USD/GiB-month |
| Planning allocation · two copies | Target price guess · published GiB | 0 | USD/published GiB |
| Planning allocation · two copies | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning allocation · two copies | Target price guess · network GiB | 0.09 | USD/network GiB |
| Planning allocation · two copies | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning allocation · two copies | Target price guess · vCPU-hour | 0.05 | USD/vCPU-hour |
| Planning allocation · two copies | Target price guess · GiB-hour | 0.006 | USD/GiB-hour |
| Planning allocation · two copies | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning allocation · two copies | Target price guess · resource-month | 0 | USD/resource-month |
| Planning allocation · two copies | Target price guess · input token | 0 | USD/input token |
| Planning allocation · two copies | Target price guess · output token | 0 | USD/output token |
| Planning allocation · two copies | Approximate target service minimum | 0 | USD/month |
| Planning allocation · two copies | Minimum primary CPU | 2 | vCPU |
| Planning allocation · two copies | Minimum primary RAM | 8 | GiB |
| Planning allocation · two copies | Minimum primary disk | 100 | GiB |
| Planning allocation · two copies | Additional full-price standby copy | 1 | 0 or 1 |
| Planning allocation · two copies | Allocated share of provisioned cost | 1 | fraction |
| Planning allocation · two copies | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning allocation · two copies | Planning peak / mean work | 2 | multiplier |
| Planning allocation · two copies | Planning primary CPU utilization | 0.7 | fraction |
| Planning allocation · two copies | Resident state reserved in RAM | 0.1 | fraction |
| Planning allocation · two copies | Planning disk utilization | 0.7 | fraction |
| Planning allocation · two copies | Maintenance and log disk reserve | 20 | GiB |
| Planning allocation · two copies | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning allocation · two copies | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning allocation · two copies | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning allocation · two copies | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning allocation · two copies | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* Native/deployment comparison scope: This mapping provisions an Azure content-filter policy. A policy is not a Bedrock inference endpoint; inference adapters have their own operation-specific terms.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Named provisioned target: selected CPU, RAM and physical disk allocation grow with workload. No additional per-database-operation price is assumed. Managed service premiums and dedicated accelerator/model-fit requirements need explicit qualification.
* Authored operation throughput, peak and working-set assumptions are not benchmark-calibrated.
* Stored GiB already includes the origin family's physical footprint assumptions; no second storage amplification is applied.
* The generic operations/vCPU coefficient supplies a provisional compute requirement alongside explicit resource-hour minima.
* Copies and allocation fractions change cost only; they do not increase modeled primary capacity.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-16611989e2e34abf6767c0c4525fdf4ae72b8f64` / `2026-10-18.planning.1`. Curve: `workload-1`.

### Bedrock model inference · Output tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.
Estimated allocation from planning assumptions; not benchmark calibrated. Only discrete samples are shown. Unpriced means no target quote or cost difference is available within the sizing policy.

| Output tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 300 | Planning allocation · one copy | Unpriced | Unavailable |
| 0 | 300 | Planning allocation · two copies | Unpriced | Unavailable |
| 10 | 694.2 | Planning allocation · one copy | Unpriced | Unavailable |
| 10 | 694.2 | Planning allocation · two copies | Unpriced | Unavailable |
| 100 | 4242 | Planning allocation · one copy | Unpriced | Unavailable |
| 100 | 4242 | Planning allocation · two copies | Unpriced | Unavailable |
| 1000 | 39720 | Planning allocation · one copy | Unpriced | Unavailable |
| 1000 | 39720 | Planning allocation · two copies | Unpriced | Unavailable |
| 10000 | 394500 | Planning allocation · one copy | Unpriced | Unavailable |
| 10000 | 394500 | Planning allocation · two copies | Unpriced | Unavailable |
| 100000 | 3942300 | Planning allocation · one copy | Unpriced | Unavailable |
| 100000 | 3942300 | Planning allocation · two copies | Unpriced | Unavailable |

**Estimated allocation from planning assumptions; not benchmark calibrated.**

The sizing policy grows compute with translated work and peak headroom, memory with compute and working set, and disk with resident working state and reserve. Monthly usage is distinct from resident data; each workload's assumptions define the translation. HA changes pricing, not this policy's throughput estimate. Unpriced workloads exceed the policy's configuration range; no silent vertical cap or automatic sharding is assumed.

| Sample / scenario | Basis | Mean / peak work/s | Required vCPU | Allocated vCPU | Memory GiB | SSD GiB | Resident GiB | Policy | Constraints |
| - | - | -: | -: | -: | -: | -: | -: | - | - |
| 0 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 0 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 1000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 1000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |

* Authored operation throughput, peak and working-set assumptions are not benchmark-calibrated.
* Stored GiB already includes the origin family's physical footprint assumptions; no second storage amplification is applied.
* The generic operations/vCPU coefficient supplies a provisional compute requirement alongside explicit resource-hour minima.
* Copies and allocation fractions change cost only; they do not increase modeled primary capacity.

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning allocation · one copy | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning allocation · one copy | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning allocation · one copy | Target / origin input tokens | 1 | multiplier |
| Planning allocation · one copy | Target / origin output tokens | 1 | multiplier |
| Planning allocation · one copy | Target price guess · read | 0 | USD/read |
| Planning allocation · one copy | Target price guess · write | 0 | USD/write |
| Planning allocation · one copy | Target price guess · provider operation | 0 | USD/provider operation |
| Planning allocation · one copy | Target price guess · GiB-month | 0.17 | USD/GiB-month |
| Planning allocation · one copy | Target price guess · published GiB | 0 | USD/published GiB |
| Planning allocation · one copy | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning allocation · one copy | Target price guess · network GiB | 0.09 | USD/network GiB |
| Planning allocation · one copy | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning allocation · one copy | Target price guess · vCPU-hour | 0.05 | USD/vCPU-hour |
| Planning allocation · one copy | Target price guess · GiB-hour | 0.006 | USD/GiB-hour |
| Planning allocation · one copy | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning allocation · one copy | Target price guess · resource-month | 0 | USD/resource-month |
| Planning allocation · one copy | Target price guess · input token | 0 | USD/input token |
| Planning allocation · one copy | Target price guess · output token | 0 | USD/output token |
| Planning allocation · one copy | Approximate target service minimum | 0 | USD/month |
| Planning allocation · one copy | Minimum primary CPU | 2 | vCPU |
| Planning allocation · one copy | Minimum primary RAM | 8 | GiB |
| Planning allocation · one copy | Minimum primary disk | 100 | GiB |
| Planning allocation · one copy | Additional full-price standby copy | 0 | 0 or 1 |
| Planning allocation · one copy | Allocated share of provisioned cost | 1 | fraction |
| Planning allocation · one copy | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning allocation · one copy | Planning peak / mean work | 2 | multiplier |
| Planning allocation · one copy | Planning primary CPU utilization | 0.7 | fraction |
| Planning allocation · one copy | Resident state reserved in RAM | 0.1 | fraction |
| Planning allocation · one copy | Planning disk utilization | 0.7 | fraction |
| Planning allocation · one copy | Maintenance and log disk reserve | 20 | GiB |
| Planning allocation · one copy | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning allocation · one copy | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning allocation · one copy | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning allocation · one copy | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning allocation · one copy | Dependent object sink write price guess | 0.000005 | USD/write |
| Planning allocation · two copies | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning allocation · two copies | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning allocation · two copies | Target / origin input tokens | 1 | multiplier |
| Planning allocation · two copies | Target / origin output tokens | 1 | multiplier |
| Planning allocation · two copies | Target price guess · read | 0 | USD/read |
| Planning allocation · two copies | Target price guess · write | 0 | USD/write |
| Planning allocation · two copies | Target price guess · provider operation | 0 | USD/provider operation |
| Planning allocation · two copies | Target price guess · GiB-month | 0.17 | USD/GiB-month |
| Planning allocation · two copies | Target price guess · published GiB | 0 | USD/published GiB |
| Planning allocation · two copies | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning allocation · two copies | Target price guess · network GiB | 0.09 | USD/network GiB |
| Planning allocation · two copies | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning allocation · two copies | Target price guess · vCPU-hour | 0.05 | USD/vCPU-hour |
| Planning allocation · two copies | Target price guess · GiB-hour | 0.006 | USD/GiB-hour |
| Planning allocation · two copies | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning allocation · two copies | Target price guess · resource-month | 0 | USD/resource-month |
| Planning allocation · two copies | Target price guess · input token | 0 | USD/input token |
| Planning allocation · two copies | Target price guess · output token | 0 | USD/output token |
| Planning allocation · two copies | Approximate target service minimum | 0 | USD/month |
| Planning allocation · two copies | Minimum primary CPU | 2 | vCPU |
| Planning allocation · two copies | Minimum primary RAM | 8 | GiB |
| Planning allocation · two copies | Minimum primary disk | 100 | GiB |
| Planning allocation · two copies | Additional full-price standby copy | 1 | 0 or 1 |
| Planning allocation · two copies | Allocated share of provisioned cost | 1 | fraction |
| Planning allocation · two copies | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning allocation · two copies | Planning peak / mean work | 2 | multiplier |
| Planning allocation · two copies | Planning primary CPU utilization | 0.7 | fraction |
| Planning allocation · two copies | Resident state reserved in RAM | 0.1 | fraction |
| Planning allocation · two copies | Planning disk utilization | 0.7 | fraction |
| Planning allocation · two copies | Maintenance and log disk reserve | 20 | GiB |
| Planning allocation · two copies | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning allocation · two copies | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning allocation · two copies | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning allocation · two copies | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning allocation · two copies | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* Native/deployment comparison scope: This mapping provisions an Azure content-filter policy. A policy is not a Bedrock inference endpoint; inference adapters have their own operation-specific terms.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Named provisioned target: selected CPU, RAM and physical disk allocation grow with workload. No additional per-database-operation price is assumed. Managed service premiums and dedicated accelerator/model-fit requirements need explicit qualification.
* Authored operation throughput, peak and working-set assumptions are not benchmark-calibrated.
* Stored GiB already includes the origin family's physical footprint assumptions; no second storage amplification is applied.
* The generic operations/vCPU coefficient supplies a provisional compute requirement alongside explicit resource-hour minima.
* Copies and allocation fractions change cost only; they do not increase modeled primary capacity.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-16611989e2e34abf6767c0c4525fdf4ae72b8f64` / `2026-10-18.planning.1`. Curve: `workload-2`.

## Bedrock model inference → OCI Generative AI

Origin API: `aws::1.0.0::bedrock`. Target backend: `oci::1.0.0::genai`.

**Planning estimate with editable assumptions.** Unit rates, workload amplification and capacity assumptions are educated guesses awaiting verification. The displayed amounts are planning estimates, not verified provider list-price quotes or benchmark-qualified capacity. Region names identify the authored scenario assumptions.

### Bedrock model inference · Input tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.

| Input tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 375 | Planning native backend | 375 | 0 |
| 10 | 453.84 | Planning native backend | 453.84 | 0 |
| 100 | 1163.4 | Planning native backend | 1163.4 | 0 |
| 1000 | 8259 | Planning native backend | 8259 | 0 |
| 10000 | 79215 | Planning native backend | 79215 | 0 |
| 100000 | 788775 | Planning native backend | 788775 | 0 |

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning native backend | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning native backend | Target / origin input tokens | 1 | multiplier |
| Planning native backend | Target / origin output tokens | 1 | multiplier |
| Planning native backend | Target price guess · read | 0 | USD/read |
| Planning native backend | Target price guess · write | 0 | USD/write |
| Planning native backend | Target price guess · provider operation | 0 | USD/provider operation |
| Planning native backend | Target price guess · GiB-month | 0 | USD/GiB-month |
| Planning native backend | Target price guess · published GiB | 0 | USD/published GiB |
| Planning native backend | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning native backend | Target price guess · network GiB | 0 | USD/network GiB |
| Planning native backend | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning native backend | Target price guess · vCPU-hour | 0 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning native backend | Target price guess · resource-month | 0 | USD/resource-month |
| Planning native backend | Target price guess · input token | 0.000003 | USD/input token |
| Planning native backend | Target price guess · output token | 0.000015 | USD/output token |
| Planning native backend | Approximate target service minimum | 0 | USD/month |
| Planning native backend | Minimum primary CPU | 2 | vCPU |
| Planning native backend | Minimum primary RAM | 8 | GiB |
| Planning native backend | Minimum primary disk | 100 | GiB |
| Planning native backend | Additional full-price standby copy | 0 | 0 or 1 |
| Planning native backend | Allocated share of provisioned cost | 1 | fraction |
| Planning native backend | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning native backend | Planning peak / mean work | 2 | multiplier |
| Planning native backend | Planning primary CPU utilization | 0.7 | fraction |
| Planning native backend | Resident state reserved in RAM | 0.1 | fraction |
| Planning native backend | Planning disk utilization | 0.7 | fraction |
| Planning native backend | Maintenance and log disk reserve | 20 | GiB |
| Planning native backend | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning native backend | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning native backend | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning native backend | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning native backend | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Input and output token tariffs remain distinct. These illustrative rates name no selected model SKU and establish no equivalent output quality or tokenizer.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-867e301a8e1fa800d4506aa97b8132fa27fdb26a` / `2026-10-18.planning.1`. Curve: `workload-1`.

### Bedrock model inference · Output tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.

| Output tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 300 | Planning native backend | 300 | 0 |
| 10 | 694.2 | Planning native backend | 694.2 | 0 |
| 100 | 4242 | Planning native backend | 4242 | 0 |
| 1000 | 39720 | Planning native backend | 39720 | 0 |
| 10000 | 394500 | Planning native backend | 394500 | 0 |
| 100000 | 3942300 | Planning native backend | 3942300 | 0 |

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning native backend | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning native backend | Target / origin input tokens | 1 | multiplier |
| Planning native backend | Target / origin output tokens | 1 | multiplier |
| Planning native backend | Target price guess · read | 0 | USD/read |
| Planning native backend | Target price guess · write | 0 | USD/write |
| Planning native backend | Target price guess · provider operation | 0 | USD/provider operation |
| Planning native backend | Target price guess · GiB-month | 0 | USD/GiB-month |
| Planning native backend | Target price guess · published GiB | 0 | USD/published GiB |
| Planning native backend | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning native backend | Target price guess · network GiB | 0 | USD/network GiB |
| Planning native backend | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning native backend | Target price guess · vCPU-hour | 0 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning native backend | Target price guess · resource-month | 0 | USD/resource-month |
| Planning native backend | Target price guess · input token | 0.000003 | USD/input token |
| Planning native backend | Target price guess · output token | 0.000015 | USD/output token |
| Planning native backend | Approximate target service minimum | 0 | USD/month |
| Planning native backend | Minimum primary CPU | 2 | vCPU |
| Planning native backend | Minimum primary RAM | 8 | GiB |
| Planning native backend | Minimum primary disk | 100 | GiB |
| Planning native backend | Additional full-price standby copy | 0 | 0 or 1 |
| Planning native backend | Allocated share of provisioned cost | 1 | fraction |
| Planning native backend | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning native backend | Planning peak / mean work | 2 | multiplier |
| Planning native backend | Planning primary CPU utilization | 0.7 | fraction |
| Planning native backend | Resident state reserved in RAM | 0.1 | fraction |
| Planning native backend | Planning disk utilization | 0.7 | fraction |
| Planning native backend | Maintenance and log disk reserve | 20 | GiB |
| Planning native backend | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning native backend | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning native backend | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning native backend | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning native backend | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Input and output token tariffs remain distinct. These illustrative rates name no selected model SKU and establish no equivalent output quality or tokenizer.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-867e301a8e1fa800d4506aa97b8132fa27fdb26a` / `2026-10-18.planning.1`. Curve: `workload-2`.

## Bedrock model inference → OpenAI Chat Completions

Origin API: `aws::1.0.0::bedrock`. Target backend: `openai::1.0.0::chat`.

**Planning estimate with editable assumptions.** Unit rates, workload amplification and capacity assumptions are educated guesses awaiting verification. The displayed amounts are planning estimates, not verified provider list-price quotes or benchmark-qualified capacity. Region names identify the authored scenario assumptions.

### Bedrock model inference · Input tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.

| Input tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 375 | Planning native backend | 375 | 0 |
| 10 | 453.84 | Planning native backend | 453.84 | 0 |
| 100 | 1163.4 | Planning native backend | 1163.4 | 0 |
| 1000 | 8259 | Planning native backend | 8259 | 0 |
| 10000 | 79215 | Planning native backend | 79215 | 0 |
| 100000 | 788775 | Planning native backend | 788775 | 0 |

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning native backend | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning native backend | Target / origin input tokens | 1 | multiplier |
| Planning native backend | Target / origin output tokens | 1 | multiplier |
| Planning native backend | Target price guess · read | 0 | USD/read |
| Planning native backend | Target price guess · write | 0 | USD/write |
| Planning native backend | Target price guess · provider operation | 0 | USD/provider operation |
| Planning native backend | Target price guess · GiB-month | 0 | USD/GiB-month |
| Planning native backend | Target price guess · published GiB | 0 | USD/published GiB |
| Planning native backend | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning native backend | Target price guess · network GiB | 0 | USD/network GiB |
| Planning native backend | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning native backend | Target price guess · vCPU-hour | 0 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning native backend | Target price guess · resource-month | 0 | USD/resource-month |
| Planning native backend | Target price guess · input token | 0.000003 | USD/input token |
| Planning native backend | Target price guess · output token | 0.000015 | USD/output token |
| Planning native backend | Approximate target service minimum | 0 | USD/month |
| Planning native backend | Minimum primary CPU | 2 | vCPU |
| Planning native backend | Minimum primary RAM | 8 | GiB |
| Planning native backend | Minimum primary disk | 100 | GiB |
| Planning native backend | Additional full-price standby copy | 0 | 0 or 1 |
| Planning native backend | Allocated share of provisioned cost | 1 | fraction |
| Planning native backend | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning native backend | Planning peak / mean work | 2 | multiplier |
| Planning native backend | Planning primary CPU utilization | 0.7 | fraction |
| Planning native backend | Resident state reserved in RAM | 0.1 | fraction |
| Planning native backend | Planning disk utilization | 0.7 | fraction |
| Planning native backend | Maintenance and log disk reserve | 20 | GiB |
| Planning native backend | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning native backend | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning native backend | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning native backend | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning native backend | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Input and output token tariffs remain distinct. These illustrative rates name no selected model SKU and establish no equivalent output quality or tokenizer.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-24a146500f73787fcd1f2436716bcced0f4263b3` / `2026-10-18.planning.1`. Curve: `workload-1`.

### Bedrock model inference · Output tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.

| Output tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 300 | Planning native backend | 300 | 0 |
| 10 | 694.2 | Planning native backend | 694.2 | 0 |
| 100 | 4242 | Planning native backend | 4242 | 0 |
| 1000 | 39720 | Planning native backend | 39720 | 0 |
| 10000 | 394500 | Planning native backend | 394500 | 0 |
| 100000 | 3942300 | Planning native backend | 3942300 | 0 |

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning native backend | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning native backend | Target / origin input tokens | 1 | multiplier |
| Planning native backend | Target / origin output tokens | 1 | multiplier |
| Planning native backend | Target price guess · read | 0 | USD/read |
| Planning native backend | Target price guess · write | 0 | USD/write |
| Planning native backend | Target price guess · provider operation | 0 | USD/provider operation |
| Planning native backend | Target price guess · GiB-month | 0 | USD/GiB-month |
| Planning native backend | Target price guess · published GiB | 0 | USD/published GiB |
| Planning native backend | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning native backend | Target price guess · network GiB | 0 | USD/network GiB |
| Planning native backend | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning native backend | Target price guess · vCPU-hour | 0 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning native backend | Target price guess · resource-month | 0 | USD/resource-month |
| Planning native backend | Target price guess · input token | 0.000003 | USD/input token |
| Planning native backend | Target price guess · output token | 0.000015 | USD/output token |
| Planning native backend | Approximate target service minimum | 0 | USD/month |
| Planning native backend | Minimum primary CPU | 2 | vCPU |
| Planning native backend | Minimum primary RAM | 8 | GiB |
| Planning native backend | Minimum primary disk | 100 | GiB |
| Planning native backend | Additional full-price standby copy | 0 | 0 or 1 |
| Planning native backend | Allocated share of provisioned cost | 1 | fraction |
| Planning native backend | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning native backend | Planning peak / mean work | 2 | multiplier |
| Planning native backend | Planning primary CPU utilization | 0.7 | fraction |
| Planning native backend | Resident state reserved in RAM | 0.1 | fraction |
| Planning native backend | Planning disk utilization | 0.7 | fraction |
| Planning native backend | Maintenance and log disk reserve | 20 | GiB |
| Planning native backend | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning native backend | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning native backend | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning native backend | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning native backend | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Input and output token tariffs remain distinct. These illustrative rates name no selected model SKU and establish no equivalent output quality or tokenizer.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-24a146500f73787fcd1f2436716bcced0f4263b3` / `2026-10-18.planning.1`. Curve: `workload-2`.

## Bedrock model inference → Scaleway Managed Inference

Origin API: `aws::1.0.0::bedrock`. Target backend: `scaleway::1.0.0::inference`.

**Planning estimate with editable assumptions.** Unit rates, workload amplification and capacity assumptions are educated guesses awaiting verification. The displayed amounts are planning estimates, not verified provider list-price quotes or benchmark-qualified capacity. Region names identify the authored scenario assumptions.

### Bedrock model inference · Input tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.
Estimated allocation from planning assumptions; not benchmark calibrated. Only discrete samples are shown. Unpriced means no target quote or cost difference is available within the sizing policy.

| Input tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 375 | Planning allocation · one copy | Unpriced | Unavailable |
| 0 | 375 | Planning allocation · two copies | Unpriced | Unavailable |
| 10 | 453.84 | Planning allocation · one copy | Unpriced | Unavailable |
| 10 | 453.84 | Planning allocation · two copies | Unpriced | Unavailable |
| 100 | 1163.4 | Planning allocation · one copy | Unpriced | Unavailable |
| 100 | 1163.4 | Planning allocation · two copies | Unpriced | Unavailable |
| 1000 | 8259 | Planning allocation · one copy | Unpriced | Unavailable |
| 1000 | 8259 | Planning allocation · two copies | Unpriced | Unavailable |
| 10000 | 79215 | Planning allocation · one copy | Unpriced | Unavailable |
| 10000 | 79215 | Planning allocation · two copies | Unpriced | Unavailable |
| 100000 | 788775 | Planning allocation · one copy | Unpriced | Unavailable |
| 100000 | 788775 | Planning allocation · two copies | Unpriced | Unavailable |

**Estimated allocation from planning assumptions; not benchmark calibrated.**

The sizing policy grows compute with translated work and peak headroom, memory with compute and working set, and disk with resident working state and reserve. Monthly usage is distinct from resident data; each workload's assumptions define the translation. HA changes pricing, not this policy's throughput estimate. Unpriced workloads exceed the policy's configuration range; no silent vertical cap or automatic sharding is assumed.

| Sample / scenario | Basis | Mean / peak work/s | Required vCPU | Allocated vCPU | Memory GiB | SSD GiB | Resident GiB | Policy | Constraints |
| - | - | -: | -: | -: | -: | -: | -: | - | - |
| 0 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 0 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 1000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 1000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |

* Authored operation throughput, peak and working-set assumptions are not benchmark-calibrated.
* Stored GiB already includes the origin family's physical footprint assumptions; no second storage amplification is applied.
* The generic operations/vCPU coefficient supplies a provisional compute requirement alongside explicit resource-hour minima.
* Copies and allocation fractions change cost only; they do not increase modeled primary capacity.

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning allocation · one copy | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning allocation · one copy | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning allocation · one copy | Target / origin input tokens | 1 | multiplier |
| Planning allocation · one copy | Target / origin output tokens | 1 | multiplier |
| Planning allocation · one copy | Target price guess · read | 0 | USD/read |
| Planning allocation · one copy | Target price guess · write | 0 | USD/write |
| Planning allocation · one copy | Target price guess · provider operation | 0 | USD/provider operation |
| Planning allocation · one copy | Target price guess · GiB-month | 0.17 | USD/GiB-month |
| Planning allocation · one copy | Target price guess · published GiB | 0 | USD/published GiB |
| Planning allocation · one copy | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning allocation · one copy | Target price guess · network GiB | 0.09 | USD/network GiB |
| Planning allocation · one copy | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning allocation · one copy | Target price guess · vCPU-hour | 0.05 | USD/vCPU-hour |
| Planning allocation · one copy | Target price guess · GiB-hour | 0.006 | USD/GiB-hour |
| Planning allocation · one copy | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning allocation · one copy | Target price guess · resource-month | 0 | USD/resource-month |
| Planning allocation · one copy | Target price guess · input token | 0 | USD/input token |
| Planning allocation · one copy | Target price guess · output token | 0 | USD/output token |
| Planning allocation · one copy | Approximate target service minimum | 0 | USD/month |
| Planning allocation · one copy | Minimum primary CPU | 2 | vCPU |
| Planning allocation · one copy | Minimum primary RAM | 8 | GiB |
| Planning allocation · one copy | Minimum primary disk | 100 | GiB |
| Planning allocation · one copy | Additional full-price standby copy | 0 | 0 or 1 |
| Planning allocation · one copy | Allocated share of provisioned cost | 1 | fraction |
| Planning allocation · one copy | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning allocation · one copy | Planning peak / mean work | 2 | multiplier |
| Planning allocation · one copy | Planning primary CPU utilization | 0.7 | fraction |
| Planning allocation · one copy | Resident state reserved in RAM | 0.1 | fraction |
| Planning allocation · one copy | Planning disk utilization | 0.7 | fraction |
| Planning allocation · one copy | Maintenance and log disk reserve | 20 | GiB |
| Planning allocation · one copy | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning allocation · one copy | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning allocation · one copy | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning allocation · one copy | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning allocation · one copy | Dependent object sink write price guess | 0.000005 | USD/write |
| Planning allocation · two copies | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning allocation · two copies | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning allocation · two copies | Target / origin input tokens | 1 | multiplier |
| Planning allocation · two copies | Target / origin output tokens | 1 | multiplier |
| Planning allocation · two copies | Target price guess · read | 0 | USD/read |
| Planning allocation · two copies | Target price guess · write | 0 | USD/write |
| Planning allocation · two copies | Target price guess · provider operation | 0 | USD/provider operation |
| Planning allocation · two copies | Target price guess · GiB-month | 0.17 | USD/GiB-month |
| Planning allocation · two copies | Target price guess · published GiB | 0 | USD/published GiB |
| Planning allocation · two copies | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning allocation · two copies | Target price guess · network GiB | 0.09 | USD/network GiB |
| Planning allocation · two copies | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning allocation · two copies | Target price guess · vCPU-hour | 0.05 | USD/vCPU-hour |
| Planning allocation · two copies | Target price guess · GiB-hour | 0.006 | USD/GiB-hour |
| Planning allocation · two copies | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning allocation · two copies | Target price guess · resource-month | 0 | USD/resource-month |
| Planning allocation · two copies | Target price guess · input token | 0 | USD/input token |
| Planning allocation · two copies | Target price guess · output token | 0 | USD/output token |
| Planning allocation · two copies | Approximate target service minimum | 0 | USD/month |
| Planning allocation · two copies | Minimum primary CPU | 2 | vCPU |
| Planning allocation · two copies | Minimum primary RAM | 8 | GiB |
| Planning allocation · two copies | Minimum primary disk | 100 | GiB |
| Planning allocation · two copies | Additional full-price standby copy | 1 | 0 or 1 |
| Planning allocation · two copies | Allocated share of provisioned cost | 1 | fraction |
| Planning allocation · two copies | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning allocation · two copies | Planning peak / mean work | 2 | multiplier |
| Planning allocation · two copies | Planning primary CPU utilization | 0.7 | fraction |
| Planning allocation · two copies | Resident state reserved in RAM | 0.1 | fraction |
| Planning allocation · two copies | Planning disk utilization | 0.7 | fraction |
| Planning allocation · two copies | Maintenance and log disk reserve | 20 | GiB |
| Planning allocation · two copies | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning allocation · two copies | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning allocation · two copies | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning allocation · two copies | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning allocation · two copies | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Named provisioned target: selected CPU, RAM and physical disk allocation grow with workload. No additional per-database-operation price is assumed. Managed service premiums and dedicated accelerator/model-fit requirements need explicit qualification.
* Authored operation throughput, peak and working-set assumptions are not benchmark-calibrated.
* Stored GiB already includes the origin family's physical footprint assumptions; no second storage amplification is applied.
* The generic operations/vCPU coefficient supplies a provisional compute requirement alongside explicit resource-hour minima.
* Copies and allocation fractions change cost only; they do not increase modeled primary capacity.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-a6f9604e9c2919f36a8bcff1239ddada7e8d8663` / `2026-10-18.planning.1`. Curve: `workload-1`.

### Bedrock model inference · Output tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.
Estimated allocation from planning assumptions; not benchmark calibrated. Only discrete samples are shown. Unpriced means no target quote or cost difference is available within the sizing policy.

| Output tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 300 | Planning allocation · one copy | Unpriced | Unavailable |
| 0 | 300 | Planning allocation · two copies | Unpriced | Unavailable |
| 10 | 694.2 | Planning allocation · one copy | Unpriced | Unavailable |
| 10 | 694.2 | Planning allocation · two copies | Unpriced | Unavailable |
| 100 | 4242 | Planning allocation · one copy | Unpriced | Unavailable |
| 100 | 4242 | Planning allocation · two copies | Unpriced | Unavailable |
| 1000 | 39720 | Planning allocation · one copy | Unpriced | Unavailable |
| 1000 | 39720 | Planning allocation · two copies | Unpriced | Unavailable |
| 10000 | 394500 | Planning allocation · one copy | Unpriced | Unavailable |
| 10000 | 394500 | Planning allocation · two copies | Unpriced | Unavailable |
| 100000 | 3942300 | Planning allocation · one copy | Unpriced | Unavailable |
| 100000 | 3942300 | Planning allocation · two copies | Unpriced | Unavailable |

**Estimated allocation from planning assumptions; not benchmark calibrated.**

The sizing policy grows compute with translated work and peak headroom, memory with compute and working set, and disk with resident working state and reserve. Monthly usage is distinct from resident data; each workload's assumptions define the translation. HA changes pricing, not this policy's throughput estimate. Unpriced workloads exceed the policy's configuration range; no silent vertical cap or automatic sharding is assumed.

| Sample / scenario | Basis | Mean / peak work/s | Required vCPU | Allocated vCPU | Memory GiB | SSD GiB | Resident GiB | Policy | Constraints |
| - | - | -: | -: | -: | -: | -: | -: | - | - |
| 0 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 0 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 1000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 1000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |

* Authored operation throughput, peak and working-set assumptions are not benchmark-calibrated.
* Stored GiB already includes the origin family's physical footprint assumptions; no second storage amplification is applied.
* The generic operations/vCPU coefficient supplies a provisional compute requirement alongside explicit resource-hour minima.
* Copies and allocation fractions change cost only; they do not increase modeled primary capacity.

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning allocation · one copy | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning allocation · one copy | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning allocation · one copy | Target / origin input tokens | 1 | multiplier |
| Planning allocation · one copy | Target / origin output tokens | 1 | multiplier |
| Planning allocation · one copy | Target price guess · read | 0 | USD/read |
| Planning allocation · one copy | Target price guess · write | 0 | USD/write |
| Planning allocation · one copy | Target price guess · provider operation | 0 | USD/provider operation |
| Planning allocation · one copy | Target price guess · GiB-month | 0.17 | USD/GiB-month |
| Planning allocation · one copy | Target price guess · published GiB | 0 | USD/published GiB |
| Planning allocation · one copy | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning allocation · one copy | Target price guess · network GiB | 0.09 | USD/network GiB |
| Planning allocation · one copy | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning allocation · one copy | Target price guess · vCPU-hour | 0.05 | USD/vCPU-hour |
| Planning allocation · one copy | Target price guess · GiB-hour | 0.006 | USD/GiB-hour |
| Planning allocation · one copy | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning allocation · one copy | Target price guess · resource-month | 0 | USD/resource-month |
| Planning allocation · one copy | Target price guess · input token | 0 | USD/input token |
| Planning allocation · one copy | Target price guess · output token | 0 | USD/output token |
| Planning allocation · one copy | Approximate target service minimum | 0 | USD/month |
| Planning allocation · one copy | Minimum primary CPU | 2 | vCPU |
| Planning allocation · one copy | Minimum primary RAM | 8 | GiB |
| Planning allocation · one copy | Minimum primary disk | 100 | GiB |
| Planning allocation · one copy | Additional full-price standby copy | 0 | 0 or 1 |
| Planning allocation · one copy | Allocated share of provisioned cost | 1 | fraction |
| Planning allocation · one copy | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning allocation · one copy | Planning peak / mean work | 2 | multiplier |
| Planning allocation · one copy | Planning primary CPU utilization | 0.7 | fraction |
| Planning allocation · one copy | Resident state reserved in RAM | 0.1 | fraction |
| Planning allocation · one copy | Planning disk utilization | 0.7 | fraction |
| Planning allocation · one copy | Maintenance and log disk reserve | 20 | GiB |
| Planning allocation · one copy | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning allocation · one copy | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning allocation · one copy | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning allocation · one copy | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning allocation · one copy | Dependent object sink write price guess | 0.000005 | USD/write |
| Planning allocation · two copies | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning allocation · two copies | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning allocation · two copies | Target / origin input tokens | 1 | multiplier |
| Planning allocation · two copies | Target / origin output tokens | 1 | multiplier |
| Planning allocation · two copies | Target price guess · read | 0 | USD/read |
| Planning allocation · two copies | Target price guess · write | 0 | USD/write |
| Planning allocation · two copies | Target price guess · provider operation | 0 | USD/provider operation |
| Planning allocation · two copies | Target price guess · GiB-month | 0.17 | USD/GiB-month |
| Planning allocation · two copies | Target price guess · published GiB | 0 | USD/published GiB |
| Planning allocation · two copies | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning allocation · two copies | Target price guess · network GiB | 0.09 | USD/network GiB |
| Planning allocation · two copies | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning allocation · two copies | Target price guess · vCPU-hour | 0.05 | USD/vCPU-hour |
| Planning allocation · two copies | Target price guess · GiB-hour | 0.006 | USD/GiB-hour |
| Planning allocation · two copies | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning allocation · two copies | Target price guess · resource-month | 0 | USD/resource-month |
| Planning allocation · two copies | Target price guess · input token | 0 | USD/input token |
| Planning allocation · two copies | Target price guess · output token | 0 | USD/output token |
| Planning allocation · two copies | Approximate target service minimum | 0 | USD/month |
| Planning allocation · two copies | Minimum primary CPU | 2 | vCPU |
| Planning allocation · two copies | Minimum primary RAM | 8 | GiB |
| Planning allocation · two copies | Minimum primary disk | 100 | GiB |
| Planning allocation · two copies | Additional full-price standby copy | 1 | 0 or 1 |
| Planning allocation · two copies | Allocated share of provisioned cost | 1 | fraction |
| Planning allocation · two copies | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning allocation · two copies | Planning peak / mean work | 2 | multiplier |
| Planning allocation · two copies | Planning primary CPU utilization | 0.7 | fraction |
| Planning allocation · two copies | Resident state reserved in RAM | 0.1 | fraction |
| Planning allocation · two copies | Planning disk utilization | 0.7 | fraction |
| Planning allocation · two copies | Maintenance and log disk reserve | 20 | GiB |
| Planning allocation · two copies | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning allocation · two copies | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning allocation · two copies | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning allocation · two copies | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning allocation · two copies | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Named provisioned target: selected CPU, RAM and physical disk allocation grow with workload. No additional per-database-operation price is assumed. Managed service premiums and dedicated accelerator/model-fit requirements need explicit qualification.
* Authored operation throughput, peak and working-set assumptions are not benchmark-calibrated.
* Stored GiB already includes the origin family's physical footprint assumptions; no second storage amplification is applied.
* The generic operations/vCPU coefficient supplies a provisional compute requirement alongside explicit resource-hour minima.
* Copies and allocation fractions change cost only; they do not increase modeled primary capacity.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-a6f9604e9c2919f36a8bcff1239ddada7e8d8663` / `2026-10-18.planning.1`. Curve: `workload-2`.

## Bedrock model inference → Vertex AI - Claude

Origin API: `aws::1.0.0::bedrock`. Target backend: `google::1.0.0::vertex::claude`.

**Planning estimate with editable assumptions.** Unit rates, workload amplification and capacity assumptions are educated guesses awaiting verification. The displayed amounts are planning estimates, not verified provider list-price quotes or benchmark-qualified capacity. Region names identify the authored scenario assumptions.

### Bedrock model inference · Input tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.

| Input tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 375 | Planning native backend | 375 | 0 |
| 10 | 453.84 | Planning native backend | 453.84 | 0 |
| 100 | 1163.4 | Planning native backend | 1163.4 | 0 |
| 1000 | 8259 | Planning native backend | 8259 | 0 |
| 10000 | 79215 | Planning native backend | 79215 | 0 |
| 100000 | 788775 | Planning native backend | 788775 | 0 |

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning native backend | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning native backend | Target / origin input tokens | 1 | multiplier |
| Planning native backend | Target / origin output tokens | 1 | multiplier |
| Planning native backend | Target price guess · read | 0 | USD/read |
| Planning native backend | Target price guess · write | 0 | USD/write |
| Planning native backend | Target price guess · provider operation | 0 | USD/provider operation |
| Planning native backend | Target price guess · GiB-month | 0 | USD/GiB-month |
| Planning native backend | Target price guess · published GiB | 0 | USD/published GiB |
| Planning native backend | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning native backend | Target price guess · network GiB | 0 | USD/network GiB |
| Planning native backend | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning native backend | Target price guess · vCPU-hour | 0 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning native backend | Target price guess · resource-month | 0 | USD/resource-month |
| Planning native backend | Target price guess · input token | 0.000003 | USD/input token |
| Planning native backend | Target price guess · output token | 0.000015 | USD/output token |
| Planning native backend | Approximate target service minimum | 0 | USD/month |
| Planning native backend | Minimum primary CPU | 2 | vCPU |
| Planning native backend | Minimum primary RAM | 8 | GiB |
| Planning native backend | Minimum primary disk | 100 | GiB |
| Planning native backend | Additional full-price standby copy | 0 | 0 or 1 |
| Planning native backend | Allocated share of provisioned cost | 1 | fraction |
| Planning native backend | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning native backend | Planning peak / mean work | 2 | multiplier |
| Planning native backend | Planning primary CPU utilization | 0.7 | fraction |
| Planning native backend | Resident state reserved in RAM | 0.1 | fraction |
| Planning native backend | Planning disk utilization | 0.7 | fraction |
| Planning native backend | Maintenance and log disk reserve | 20 | GiB |
| Planning native backend | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning native backend | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning native backend | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning native backend | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning native backend | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Input and output token tariffs remain distinct. These illustrative rates name no selected model SKU and establish no equivalent output quality or tokenizer.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-48c312b989270b8c0eaf604ff9da8bb4641b8a7b` / `2026-10-18.planning.1`. Curve: `workload-1`.

### Bedrock model inference · Output tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.

| Output tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 300 | Planning native backend | 300 | 0 |
| 10 | 694.2 | Planning native backend | 694.2 | 0 |
| 100 | 4242 | Planning native backend | 4242 | 0 |
| 1000 | 39720 | Planning native backend | 39720 | 0 |
| 10000 | 394500 | Planning native backend | 394500 | 0 |
| 100000 | 3942300 | Planning native backend | 3942300 | 0 |

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning native backend | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning native backend | Target / origin input tokens | 1 | multiplier |
| Planning native backend | Target / origin output tokens | 1 | multiplier |
| Planning native backend | Target price guess · read | 0 | USD/read |
| Planning native backend | Target price guess · write | 0 | USD/write |
| Planning native backend | Target price guess · provider operation | 0 | USD/provider operation |
| Planning native backend | Target price guess · GiB-month | 0 | USD/GiB-month |
| Planning native backend | Target price guess · published GiB | 0 | USD/published GiB |
| Planning native backend | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning native backend | Target price guess · network GiB | 0 | USD/network GiB |
| Planning native backend | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning native backend | Target price guess · vCPU-hour | 0 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning native backend | Target price guess · resource-month | 0 | USD/resource-month |
| Planning native backend | Target price guess · input token | 0.000003 | USD/input token |
| Planning native backend | Target price guess · output token | 0.000015 | USD/output token |
| Planning native backend | Approximate target service minimum | 0 | USD/month |
| Planning native backend | Minimum primary CPU | 2 | vCPU |
| Planning native backend | Minimum primary RAM | 8 | GiB |
| Planning native backend | Minimum primary disk | 100 | GiB |
| Planning native backend | Additional full-price standby copy | 0 | 0 or 1 |
| Planning native backend | Allocated share of provisioned cost | 1 | fraction |
| Planning native backend | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning native backend | Planning peak / mean work | 2 | multiplier |
| Planning native backend | Planning primary CPU utilization | 0.7 | fraction |
| Planning native backend | Resident state reserved in RAM | 0.1 | fraction |
| Planning native backend | Planning disk utilization | 0.7 | fraction |
| Planning native backend | Maintenance and log disk reserve | 20 | GiB |
| Planning native backend | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning native backend | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning native backend | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning native backend | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning native backend | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Input and output token tariffs remain distinct. These illustrative rates name no selected model SKU and establish no equivalent output quality or tokenizer.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-48c312b989270b8c0eaf604ff9da8bb4641b8a7b` / `2026-10-18.planning.1`. Curve: `workload-2`.

## Bedrock model inference → Vertex AI - Gemini

Origin API: `aws::1.0.0::bedrock`. Target backend: `google::1.0.0::vertex::gemini`.

**Planning estimate with editable assumptions.** Unit rates, workload amplification and capacity assumptions are educated guesses awaiting verification. The displayed amounts are planning estimates, not verified provider list-price quotes or benchmark-qualified capacity. Region names identify the authored scenario assumptions.

### Bedrock model inference · Input tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.

| Input tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 375 | Planning native backend | 375 | 0 |
| 10 | 453.84 | Planning native backend | 453.84 | 0 |
| 100 | 1163.4 | Planning native backend | 1163.4 | 0 |
| 1000 | 8259 | Planning native backend | 8259 | 0 |
| 10000 | 79215 | Planning native backend | 79215 | 0 |
| 100000 | 788775 | Planning native backend | 788775 | 0 |

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning native backend | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning native backend | Target / origin input tokens | 1 | multiplier |
| Planning native backend | Target / origin output tokens | 1 | multiplier |
| Planning native backend | Target price guess · read | 0 | USD/read |
| Planning native backend | Target price guess · write | 0 | USD/write |
| Planning native backend | Target price guess · provider operation | 0 | USD/provider operation |
| Planning native backend | Target price guess · GiB-month | 0 | USD/GiB-month |
| Planning native backend | Target price guess · published GiB | 0 | USD/published GiB |
| Planning native backend | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning native backend | Target price guess · network GiB | 0 | USD/network GiB |
| Planning native backend | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning native backend | Target price guess · vCPU-hour | 0 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning native backend | Target price guess · resource-month | 0 | USD/resource-month |
| Planning native backend | Target price guess · input token | 0.000003 | USD/input token |
| Planning native backend | Target price guess · output token | 0.000015 | USD/output token |
| Planning native backend | Approximate target service minimum | 0 | USD/month |
| Planning native backend | Minimum primary CPU | 2 | vCPU |
| Planning native backend | Minimum primary RAM | 8 | GiB |
| Planning native backend | Minimum primary disk | 100 | GiB |
| Planning native backend | Additional full-price standby copy | 0 | 0 or 1 |
| Planning native backend | Allocated share of provisioned cost | 1 | fraction |
| Planning native backend | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning native backend | Planning peak / mean work | 2 | multiplier |
| Planning native backend | Planning primary CPU utilization | 0.7 | fraction |
| Planning native backend | Resident state reserved in RAM | 0.1 | fraction |
| Planning native backend | Planning disk utilization | 0.7 | fraction |
| Planning native backend | Maintenance and log disk reserve | 20 | GiB |
| Planning native backend | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning native backend | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning native backend | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning native backend | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning native backend | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Input and output token tariffs remain distinct. These illustrative rates name no selected model SKU and establish no equivalent output quality or tokenizer.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-4c72ad085195d9377822f40afb60d644ed875746` / `2026-10-18.planning.1`. Curve: `workload-1`.

### Bedrock model inference · Output tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.

| Output tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 300 | Planning native backend | 300 | 0 |
| 10 | 694.2 | Planning native backend | 694.2 | 0 |
| 100 | 4242 | Planning native backend | 4242 | 0 |
| 1000 | 39720 | Planning native backend | 39720 | 0 |
| 10000 | 394500 | Planning native backend | 394500 | 0 |
| 100000 | 3942300 | Planning native backend | 3942300 | 0 |

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning native backend | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning native backend | Target / origin input tokens | 1 | multiplier |
| Planning native backend | Target / origin output tokens | 1 | multiplier |
| Planning native backend | Target price guess · read | 0 | USD/read |
| Planning native backend | Target price guess · write | 0 | USD/write |
| Planning native backend | Target price guess · provider operation | 0 | USD/provider operation |
| Planning native backend | Target price guess · GiB-month | 0 | USD/GiB-month |
| Planning native backend | Target price guess · published GiB | 0 | USD/published GiB |
| Planning native backend | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning native backend | Target price guess · network GiB | 0 | USD/network GiB |
| Planning native backend | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning native backend | Target price guess · vCPU-hour | 0 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning native backend | Target price guess · resource-month | 0 | USD/resource-month |
| Planning native backend | Target price guess · input token | 0.000003 | USD/input token |
| Planning native backend | Target price guess · output token | 0.000015 | USD/output token |
| Planning native backend | Approximate target service minimum | 0 | USD/month |
| Planning native backend | Minimum primary CPU | 2 | vCPU |
| Planning native backend | Minimum primary RAM | 8 | GiB |
| Planning native backend | Minimum primary disk | 100 | GiB |
| Planning native backend | Additional full-price standby copy | 0 | 0 or 1 |
| Planning native backend | Allocated share of provisioned cost | 1 | fraction |
| Planning native backend | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning native backend | Planning peak / mean work | 2 | multiplier |
| Planning native backend | Planning primary CPU utilization | 0.7 | fraction |
| Planning native backend | Resident state reserved in RAM | 0.1 | fraction |
| Planning native backend | Planning disk utilization | 0.7 | fraction |
| Planning native backend | Maintenance and log disk reserve | 20 | GiB |
| Planning native backend | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning native backend | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning native backend | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning native backend | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning native backend | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Input and output token tariffs remain distinct. These illustrative rates name no selected model SKU and establish no equivalent output quality or tokenizer.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-4c72ad085195d9377822f40afb60d644ed875746` / `2026-10-18.planning.1`. Curve: `workload-2`.

## Bedrock model inference → Vertex AI - Llama

Origin API: `aws::1.0.0::bedrock`. Target backend: `google::1.0.0::vertex::llama`.

**Planning estimate with editable assumptions.** Unit rates, workload amplification and capacity assumptions are educated guesses awaiting verification. The displayed amounts are planning estimates, not verified provider list-price quotes or benchmark-qualified capacity. Region names identify the authored scenario assumptions.

### Bedrock model inference · Input tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.

| Input tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 375 | Planning native backend | 375 | 0 |
| 10 | 453.84 | Planning native backend | 453.84 | 0 |
| 100 | 1163.4 | Planning native backend | 1163.4 | 0 |
| 1000 | 8259 | Planning native backend | 8259 | 0 |
| 10000 | 79215 | Planning native backend | 79215 | 0 |
| 100000 | 788775 | Planning native backend | 788775 | 0 |

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning native backend | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning native backend | Target / origin input tokens | 1 | multiplier |
| Planning native backend | Target / origin output tokens | 1 | multiplier |
| Planning native backend | Target price guess · read | 0 | USD/read |
| Planning native backend | Target price guess · write | 0 | USD/write |
| Planning native backend | Target price guess · provider operation | 0 | USD/provider operation |
| Planning native backend | Target price guess · GiB-month | 0 | USD/GiB-month |
| Planning native backend | Target price guess · published GiB | 0 | USD/published GiB |
| Planning native backend | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning native backend | Target price guess · network GiB | 0 | USD/network GiB |
| Planning native backend | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning native backend | Target price guess · vCPU-hour | 0 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning native backend | Target price guess · resource-month | 0 | USD/resource-month |
| Planning native backend | Target price guess · input token | 0.000003 | USD/input token |
| Planning native backend | Target price guess · output token | 0.000015 | USD/output token |
| Planning native backend | Approximate target service minimum | 0 | USD/month |
| Planning native backend | Minimum primary CPU | 2 | vCPU |
| Planning native backend | Minimum primary RAM | 8 | GiB |
| Planning native backend | Minimum primary disk | 100 | GiB |
| Planning native backend | Additional full-price standby copy | 0 | 0 or 1 |
| Planning native backend | Allocated share of provisioned cost | 1 | fraction |
| Planning native backend | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning native backend | Planning peak / mean work | 2 | multiplier |
| Planning native backend | Planning primary CPU utilization | 0.7 | fraction |
| Planning native backend | Resident state reserved in RAM | 0.1 | fraction |
| Planning native backend | Planning disk utilization | 0.7 | fraction |
| Planning native backend | Maintenance and log disk reserve | 20 | GiB |
| Planning native backend | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning native backend | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning native backend | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning native backend | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning native backend | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Input and output token tariffs remain distinct. These illustrative rates name no selected model SKU and establish no equivalent output quality or tokenizer.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-5c6a290efb8ab2af09754f01caf66263075fec9b` / `2026-10-18.planning.1`. Curve: `workload-1`.

### Bedrock model inference · Output tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.

| Output tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 300 | Planning native backend | 300 | 0 |
| 10 | 694.2 | Planning native backend | 694.2 | 0 |
| 100 | 4242 | Planning native backend | 4242 | 0 |
| 1000 | 39720 | Planning native backend | 39720 | 0 |
| 10000 | 394500 | Planning native backend | 394500 | 0 |
| 100000 | 3942300 | Planning native backend | 3942300 | 0 |

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning native backend | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning native backend | Target / origin input tokens | 1 | multiplier |
| Planning native backend | Target / origin output tokens | 1 | multiplier |
| Planning native backend | Target price guess · read | 0 | USD/read |
| Planning native backend | Target price guess · write | 0 | USD/write |
| Planning native backend | Target price guess · provider operation | 0 | USD/provider operation |
| Planning native backend | Target price guess · GiB-month | 0 | USD/GiB-month |
| Planning native backend | Target price guess · published GiB | 0 | USD/published GiB |
| Planning native backend | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning native backend | Target price guess · network GiB | 0 | USD/network GiB |
| Planning native backend | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning native backend | Target price guess · vCPU-hour | 0 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0 | USD/GiB-hour |
| Planning native backend | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning native backend | Target price guess · resource-month | 0 | USD/resource-month |
| Planning native backend | Target price guess · input token | 0.000003 | USD/input token |
| Planning native backend | Target price guess · output token | 0.000015 | USD/output token |
| Planning native backend | Approximate target service minimum | 0 | USD/month |
| Planning native backend | Minimum primary CPU | 2 | vCPU |
| Planning native backend | Minimum primary RAM | 8 | GiB |
| Planning native backend | Minimum primary disk | 100 | GiB |
| Planning native backend | Additional full-price standby copy | 0 | 0 or 1 |
| Planning native backend | Allocated share of provisioned cost | 1 | fraction |
| Planning native backend | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning native backend | Planning peak / mean work | 2 | multiplier |
| Planning native backend | Planning primary CPU utilization | 0.7 | fraction |
| Planning native backend | Resident state reserved in RAM | 0.1 | fraction |
| Planning native backend | Planning disk utilization | 0.7 | fraction |
| Planning native backend | Maintenance and log disk reserve | 20 | GiB |
| Planning native backend | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning native backend | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning native backend | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning native backend | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning native backend | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Input and output token tariffs remain distinct. These illustrative rates name no selected model SKU and establish no equivalent output quality or tokenizer.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-5c6a290efb8ab2af09754f01caf66263075fec9b` / `2026-10-18.planning.1`. Curve: `workload-2`.

## Bedrock model inference → vLLM / Ollama

Origin API: `aws::1.0.0::bedrock`. Target backend: `tensor9::1.0.0::emu::aws/1.0.0/bedrock::incluster`.

**Planning estimate with editable assumptions.** Unit rates, workload amplification and capacity assumptions are educated guesses awaiting verification. The displayed amounts are planning estimates, not verified provider list-price quotes or benchmark-qualified capacity. Region names identify the authored scenario assumptions.

### Bedrock model inference · Input tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Input tokens per second: monthly service charges by Input tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.
Estimated allocation from planning assumptions; not benchmark calibrated. Only discrete samples are shown. Unpriced means no target quote or cost difference is available within the sizing policy.

| Input tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 375 | Planning allocation · one copy | Unpriced | Unavailable |
| 0 | 375 | Planning allocation · two copies | Unpriced | Unavailable |
| 10 | 453.84 | Planning allocation · one copy | Unpriced | Unavailable |
| 10 | 453.84 | Planning allocation · two copies | Unpriced | Unavailable |
| 100 | 1163.4 | Planning allocation · one copy | Unpriced | Unavailable |
| 100 | 1163.4 | Planning allocation · two copies | Unpriced | Unavailable |
| 1000 | 8259 | Planning allocation · one copy | Unpriced | Unavailable |
| 1000 | 8259 | Planning allocation · two copies | Unpriced | Unavailable |
| 10000 | 79215 | Planning allocation · one copy | Unpriced | Unavailable |
| 10000 | 79215 | Planning allocation · two copies | Unpriced | Unavailable |
| 100000 | 788775 | Planning allocation · one copy | Unpriced | Unavailable |
| 100000 | 788775 | Planning allocation · two copies | Unpriced | Unavailable |

**Estimated allocation from planning assumptions; not benchmark calibrated.**

The sizing policy grows compute with translated work and peak headroom, memory with compute and working set, and disk with resident working state and reserve. Monthly usage is distinct from resident data; each workload's assumptions define the translation. HA changes pricing, not this policy's throughput estimate. Unpriced workloads exceed the policy's configuration range; no silent vertical cap or automatic sharding is assumed.

| Sample / scenario | Basis | Mean / peak work/s | Required vCPU | Allocated vCPU | Memory GiB | SSD GiB | Resident GiB | Policy | Constraints |
| - | - | -: | -: | -: | -: | -: | -: | - | - |
| 0 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 0 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 1000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 1000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |

* Authored operation throughput, peak and working-set assumptions are not benchmark-calibrated.
* Stored GiB already includes the origin family's physical footprint assumptions; no second storage amplification is applied.
* The generic operations/vCPU coefficient supplies a provisional compute requirement alongside explicit resource-hour minima.
* Copies and allocation fractions change cost only; they do not increase modeled primary capacity.

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning allocation · one copy | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning allocation · one copy | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning allocation · one copy | Target / origin input tokens | 1 | multiplier |
| Planning allocation · one copy | Target / origin output tokens | 1 | multiplier |
| Planning allocation · one copy | Target price guess · read | 0 | USD/read |
| Planning allocation · one copy | Target price guess · write | 0 | USD/write |
| Planning allocation · one copy | Target price guess · provider operation | 0 | USD/provider operation |
| Planning allocation · one copy | Target price guess · GiB-month | 0.17 | USD/GiB-month |
| Planning allocation · one copy | Target price guess · published GiB | 0 | USD/published GiB |
| Planning allocation · one copy | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning allocation · one copy | Target price guess · network GiB | 0.09 | USD/network GiB |
| Planning allocation · one copy | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning allocation · one copy | Target price guess · vCPU-hour | 0.05 | USD/vCPU-hour |
| Planning allocation · one copy | Target price guess · GiB-hour | 0.006 | USD/GiB-hour |
| Planning allocation · one copy | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning allocation · one copy | Target price guess · resource-month | 0 | USD/resource-month |
| Planning allocation · one copy | Target price guess · input token | 0 | USD/input token |
| Planning allocation · one copy | Target price guess · output token | 0 | USD/output token |
| Planning allocation · one copy | Approximate target service minimum | 0 | USD/month |
| Planning allocation · one copy | Minimum primary CPU | 2 | vCPU |
| Planning allocation · one copy | Minimum primary RAM | 8 | GiB |
| Planning allocation · one copy | Minimum primary disk | 100 | GiB |
| Planning allocation · one copy | Additional full-price standby copy | 0 | 0 or 1 |
| Planning allocation · one copy | Allocated share of provisioned cost | 1 | fraction |
| Planning allocation · one copy | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning allocation · one copy | Planning peak / mean work | 2 | multiplier |
| Planning allocation · one copy | Planning primary CPU utilization | 0.7 | fraction |
| Planning allocation · one copy | Resident state reserved in RAM | 0.1 | fraction |
| Planning allocation · one copy | Planning disk utilization | 0.7 | fraction |
| Planning allocation · one copy | Maintenance and log disk reserve | 20 | GiB |
| Planning allocation · one copy | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning allocation · one copy | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning allocation · one copy | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning allocation · one copy | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning allocation · one copy | Dependent object sink write price guess | 0.000005 | USD/write |
| Planning allocation · two copies | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning allocation · two copies | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning allocation · two copies | Target / origin input tokens | 1 | multiplier |
| Planning allocation · two copies | Target / origin output tokens | 1 | multiplier |
| Planning allocation · two copies | Target price guess · read | 0 | USD/read |
| Planning allocation · two copies | Target price guess · write | 0 | USD/write |
| Planning allocation · two copies | Target price guess · provider operation | 0 | USD/provider operation |
| Planning allocation · two copies | Target price guess · GiB-month | 0.17 | USD/GiB-month |
| Planning allocation · two copies | Target price guess · published GiB | 0 | USD/published GiB |
| Planning allocation · two copies | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning allocation · two copies | Target price guess · network GiB | 0.09 | USD/network GiB |
| Planning allocation · two copies | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning allocation · two copies | Target price guess · vCPU-hour | 0.05 | USD/vCPU-hour |
| Planning allocation · two copies | Target price guess · GiB-hour | 0.006 | USD/GiB-hour |
| Planning allocation · two copies | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning allocation · two copies | Target price guess · resource-month | 0 | USD/resource-month |
| Planning allocation · two copies | Target price guess · input token | 0 | USD/input token |
| Planning allocation · two copies | Target price guess · output token | 0 | USD/output token |
| Planning allocation · two copies | Approximate target service minimum | 0 | USD/month |
| Planning allocation · two copies | Minimum primary CPU | 2 | vCPU |
| Planning allocation · two copies | Minimum primary RAM | 8 | GiB |
| Planning allocation · two copies | Minimum primary disk | 100 | GiB |
| Planning allocation · two copies | Additional full-price standby copy | 1 | 0 or 1 |
| Planning allocation · two copies | Allocated share of provisioned cost | 1 | fraction |
| Planning allocation · two copies | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning allocation · two copies | Planning peak / mean work | 2 | multiplier |
| Planning allocation · two copies | Planning primary CPU utilization | 0.7 | fraction |
| Planning allocation · two copies | Resident state reserved in RAM | 0.1 | fraction |
| Planning allocation · two copies | Planning disk utilization | 0.7 | fraction |
| Planning allocation · two copies | Maintenance and log disk reserve | 20 | GiB |
| Planning allocation · two copies | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning allocation · two copies | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning allocation · two copies | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning allocation · two copies | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning allocation · two copies | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Named provisioned target: selected CPU, RAM and physical disk allocation grow with workload. No additional per-database-operation price is assumed. Managed service premiums and dedicated accelerator/model-fit requirements need explicit qualification.
* Authored operation throughput, peak and working-set assumptions are not benchmark-calibrated.
* Stored GiB already includes the origin family's physical footprint assumptions; no second storage amplification is applied.
* The generic operations/vCPU coefficient supplies a provisional compute requirement alongside explicit resource-hour minima.
* Copies and allocation fractions change cost only; they do not increase modeled primary capacity.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-952508c3bf76f8b345ea3c168617029855c8f41f` / `2026-10-18.planning.1`. Curve: `workload-1`.

### Bedrock model inference · Output tokens per second

**Planning estimate with editable assumptions.** These authored unit rates and capacity assumptions require provider-price verification and representative benchmarks. They do not constitute verified list-price quotes or evidence that an adapter is available.

Estimated monthly service charges from native source usage; no calculator input is required. Adapter hosting and Tensor9 fees are excluded. Source: Explicit source planning region; target: Explicit target planning region; currency: USD.

<div className="t9-diagram-scroll" role="region" aria-label="Service charge comparison" tabIndex={0}>
  <img className="t9-diagram-light" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />

  <img className="t9-diagram-dark" src="data:image/svg+xml;base64,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" alt="Bedrock model inference · Output tokens per second: monthly service charges by Output tokens per second. Exact values are in the following table." />
</div>

Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.
Estimated allocation from planning assumptions; not benchmark calibrated. Only discrete samples are shown. Unpriced means no target quote or cost difference is available within the sizing policy.

| Output tokens per second (tokens/s) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 300 | Planning allocation · one copy | Unpriced | Unavailable |
| 0 | 300 | Planning allocation · two copies | Unpriced | Unavailable |
| 10 | 694.2 | Planning allocation · one copy | Unpriced | Unavailable |
| 10 | 694.2 | Planning allocation · two copies | Unpriced | Unavailable |
| 100 | 4242 | Planning allocation · one copy | Unpriced | Unavailable |
| 100 | 4242 | Planning allocation · two copies | Unpriced | Unavailable |
| 1000 | 39720 | Planning allocation · one copy | Unpriced | Unavailable |
| 1000 | 39720 | Planning allocation · two copies | Unpriced | Unavailable |
| 10000 | 394500 | Planning allocation · one copy | Unpriced | Unavailable |
| 10000 | 394500 | Planning allocation · two copies | Unpriced | Unavailable |
| 100000 | 3942300 | Planning allocation · one copy | Unpriced | Unavailable |
| 100000 | 3942300 | Planning allocation · two copies | Unpriced | Unavailable |

**Estimated allocation from planning assumptions; not benchmark calibrated.**

The sizing policy grows compute with translated work and peak headroom, memory with compute and working set, and disk with resident working state and reserve. Monthly usage is distinct from resident data; each workload's assumptions define the translation. HA changes pricing, not this policy's throughput estimate. Unpriced workloads exceed the policy's configuration range; no silent vertical cap or automatic sharding is assumed.

| Sample / scenario | Basis | Mean / peak work/s | Required vCPU | Allocated vCPU | Memory GiB | SSD GiB | Resident GiB | Policy | Constraints |
| - | - | -: | -: | -: | -: | -: | -: | - | - |
| 0 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 0 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 1000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 1000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 10000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100000 tokens/s / Planning allocation · one copy | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |
| 100000 tokens/s / Planning allocation · two copies | Unpriced | 0 / 0 | 0 | Unpriced | Unpriced | Unpriced | 0 | `service-adapter-planning-2026-10-18.1` | Dedicated inference accelerator allocation and model fit have not been selected. |

* Authored operation throughput, peak and working-set assumptions are not benchmark-calibrated.
* Stored GiB already includes the origin family's physical footprint assumptions; no second storage amplification is applied.
* The generic operations/vCPU coefficient supplies a provisional compute requirement alongside explicit resource-hour minima.
* Copies and allocation fractions change cost only; they do not increase modeled primary capacity.

**Curve assumptions**

| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning allocation · one copy | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning allocation · one copy | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning allocation · one copy | Target / origin input tokens | 1 | multiplier |
| Planning allocation · one copy | Target / origin output tokens | 1 | multiplier |
| Planning allocation · one copy | Target price guess · read | 0 | USD/read |
| Planning allocation · one copy | Target price guess · write | 0 | USD/write |
| Planning allocation · one copy | Target price guess · provider operation | 0 | USD/provider operation |
| Planning allocation · one copy | Target price guess · GiB-month | 0.17 | USD/GiB-month |
| Planning allocation · one copy | Target price guess · published GiB | 0 | USD/published GiB |
| Planning allocation · one copy | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning allocation · one copy | Target price guess · network GiB | 0.09 | USD/network GiB |
| Planning allocation · one copy | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning allocation · one copy | Target price guess · vCPU-hour | 0.05 | USD/vCPU-hour |
| Planning allocation · one copy | Target price guess · GiB-hour | 0.006 | USD/GiB-hour |
| Planning allocation · one copy | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning allocation · one copy | Target price guess · resource-month | 0 | USD/resource-month |
| Planning allocation · one copy | Target price guess · input token | 0 | USD/input token |
| Planning allocation · one copy | Target price guess · output token | 0 | USD/output token |
| Planning allocation · one copy | Approximate target service minimum | 0 | USD/month |
| Planning allocation · one copy | Minimum primary CPU | 2 | vCPU |
| Planning allocation · one copy | Minimum primary RAM | 8 | GiB |
| Planning allocation · one copy | Minimum primary disk | 100 | GiB |
| Planning allocation · one copy | Additional full-price standby copy | 0 | 0 or 1 |
| Planning allocation · one copy | Allocated share of provisioned cost | 1 | fraction |
| Planning allocation · one copy | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning allocation · one copy | Planning peak / mean work | 2 | multiplier |
| Planning allocation · one copy | Planning primary CPU utilization | 0.7 | fraction |
| Planning allocation · one copy | Resident state reserved in RAM | 0.1 | fraction |
| Planning allocation · one copy | Planning disk utilization | 0.7 | fraction |
| Planning allocation · one copy | Maintenance and log disk reserve | 20 | GiB |
| Planning allocation · one copy | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning allocation · one copy | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning allocation · one copy | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning allocation · one copy | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning allocation · one copy | Dependent object sink write price guess | 0.000005 | USD/write |
| Planning allocation · two copies | Origin price guess · Input tokens | 0.000003 | USD/Tokens |
| Planning allocation · two copies | Origin price guess · Output tokens | 0.000015 | USD/Tokens |
| Planning allocation · two copies | Target / origin input tokens | 1 | multiplier |
| Planning allocation · two copies | Target / origin output tokens | 1 | multiplier |
| Planning allocation · two copies | Target price guess · read | 0 | USD/read |
| Planning allocation · two copies | Target price guess · write | 0 | USD/write |
| Planning allocation · two copies | Target price guess · provider operation | 0 | USD/provider operation |
| Planning allocation · two copies | Target price guess · GiB-month | 0.17 | USD/GiB-month |
| Planning allocation · two copies | Target price guess · published GiB | 0 | USD/published GiB |
| Planning allocation · two copies | Target price guess · delivered GiB | 0 | USD/delivered GiB |
| Planning allocation · two copies | Target price guess · network GiB | 0.09 | USD/network GiB |
| Planning allocation · two copies | Target price guess · replica GiB-month | 0 | USD/replica GiB-month |
| Planning allocation · two copies | Target price guess · vCPU-hour | 0.05 | USD/vCPU-hour |
| Planning allocation · two copies | Target price guess · GiB-hour | 0.006 | USD/GiB-hour |
| Planning allocation · two copies | Target price guess · resource-hour | 0 | USD/resource-hour |
| Planning allocation · two copies | Target price guess · resource-month | 0 | USD/resource-month |
| Planning allocation · two copies | Target price guess · input token | 0 | USD/input token |
| Planning allocation · two copies | Target price guess · output token | 0 | USD/output token |
| Planning allocation · two copies | Approximate target service minimum | 0 | USD/month |
| Planning allocation · two copies | Minimum primary CPU | 2 | vCPU |
| Planning allocation · two copies | Minimum primary RAM | 8 | GiB |
| Planning allocation · two copies | Minimum primary disk | 100 | GiB |
| Planning allocation · two copies | Additional full-price standby copy | 1 | 0 or 1 |
| Planning allocation · two copies | Allocated share of provisioned cost | 1 | fraction |
| Planning allocation · two copies | Planning read/write work per vCPU-second | 1000 | operations/vCPU-second |
| Planning allocation · two copies | Planning peak / mean work | 2 | multiplier |
| Planning allocation · two copies | Planning primary CPU utilization | 0.7 | fraction |
| Planning allocation · two copies | Resident state reserved in RAM | 0.1 | fraction |
| Planning allocation · two copies | Planning disk utilization | 0.7 | fraction |
| Planning allocation · two copies | Maintenance and log disk reserve | 20 | GiB |
| Planning allocation · two copies | Staging database CPU unit-price guess | 0.0413 | USD/vCPU-hour |
| Planning allocation · two copies | Staging database RAM unit-price guess | 0.007 | USD/GiB-hour |
| Planning allocation · two copies | Staging database disk unit-price guess | 0.17 | USD/GiB-month |
| Planning allocation · two copies | Dependent object sink storage price guess | 0.023 | USD/GiB-month |
| Planning allocation · two copies | Dependent object sink write price guess | 0.000005 | USD/write |

* Only this native meter varies; all other source usage and translation assumptions retain the displayed defaults. Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote. Other native meters retain their explicitly displayed default quantities.
* Planning estimate · editable authored rates and sizing assumptions dated 2026-10-18; not verified provider prices. Explicit source planning region → Explicit target planning region, USD/month.
* Source prices are reference charges, not an invoice. Target lines cover selected service usage/configuration only; adapter hosting and Tensor9 fees are excluded.
* Explicit tariff samples are not performance measurements or capacity qualification. No interpolation or break-even guarantee is implied.
* Variant assumptions show the first axis sample; any axis-dependent configuration is described by this curve's workload note.
* Editable authored planning guesses, not verified provider tariffs, benchmark measurements or a commercial quote.
* Default-zero rates are explicit assumptions, not evidence that the deployed service or resource is free.
* Provisioned-unit minimums use an editable approximate allocation floor. Modeled target service cost is max(usage/allocation, minimum), with billable network, durable staging and dependent sinks added separately; actual RU/TU sizing, scaling increments and throughput remain unqualified.
* Durable staging is priced once: provisioned targets include adapter state in their selected allocation; native targets add a separate staging allocation when required. Adapter hosting is a separate allocation and must exclude resources already priced as staging, workers or target capacity.
* A declared adapter mapping and cost model do not establish implementation availability or service equivalence.
* This is a declared directed mapping; a planning estimate does not establish deployment or request-serving support.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* Source and target tariffs name no asserted current model SKU. Select model-specific rates before using the estimate.
* Input and output meters and token expansion remain independent. A cheaper model is not automatically equivalent in capability or quality.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Named provisioned target: selected CPU, RAM and physical disk allocation grow with workload. No additional per-database-operation price is assumed. Managed service premiums and dedicated accelerator/model-fit requirements need explicit qualification.
* Authored operation throughput, peak and working-set assumptions are not benchmark-calibrated.
* Stored GiB already includes the origin family's physical footprint assumptions; no second storage amplification is applied.
* The generic operations/vCPU coefficient supplies a provisional compute requirement alongside explicit resource-hour minima.
* Copies and allocation fractions change cost only; they do not increase modeled primary capacity.

Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.

Excluded costs and workload features:

* Prompt caching, batch discounts, context tiers, grounding, tools, agents, embeddings, search, guardrails and dedicated inference hardware.
* Taxes, discounts, credits and free-tier allowances unless explicitly reflected in edited rates.
* Unmodeled dependent services, task execution and operations outside the selected workload family.

Planning assumptions authored: 2026-10-18. Model: `plan-952508c3bf76f8b345ea3c168617029855c8f41f` / `2026-10-18.planning.1`. Curve: `workload-2`.

See the [service catalog](/byoc/service-adapters/catalog) for operation coverage, supported directions and backend limitations.


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