> ## 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.
# Compute Engine costs
> Compare Compute Engine backend choices using explicit service-adapter planning assumptions.
Tensor9 BYOC planning comparisons for `google::1.0.0::compute::instance`, 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).
## Allocated virtual machine capacity → EC2 Instances
Origin API: `google::1.0.0::compute::instance`. Target backend: `aws::1.0.0::ec2::instance`.
**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.
**Designed mapping.** This cost model describes an intended adapter. Its estimated price does not establish a delivered or selectable backend.
### Allocated virtual machine capacity · Allocated VM CPU-hours per month
**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.
Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.
| Allocated VM CPU-hours per month (vCPU-hour/month) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 39.2 | Planning native backend | 43.58 | 4.38 |
| 1460 | 97.6 | Planning native backend | 110.74 | 13.14 |
| 5840 | 272.8 | Planning native backend | 312.22 | 39.42 |
| 23360 | 973.6 | Planning native backend | 1118.14 | 144.54 |
| 93440 | 3776.8 | Planning native backend | 4341.82 | 565.02 |
| 373760 | 14989.6 | Planning native backend | 17236.54 | 2246.94 |
**Curve assumptions**
| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · VM allocated CPU | 0.04 | USD/vCPU-hour |
| Planning native backend | Origin price guess · VM allocated memory | 0.005 | USD/GiB-hour |
| Planning native backend | Origin price guess · VM allocated disks | 0.1 | USD/GiB-month |
| Planning native backend | Origin price guess · Billable VM network transfer | 0.09 | USD/GiB |
| Planning native backend | Target / origin VM CPU and RAM | 1.15 | 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 | 0.1 | 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 | 0.09 | 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 | 0.04 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0.005 | 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 | USD/input token |
| Planning native backend | Target price guess · output token | 0 | 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 exact directed mapping has a design profile. Cost modeling does not establish an implemented or deployable adapter.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* CPU, RAM, disks and network quantities remain independently editable. Increasing CPU does not silently increase the selected memory meter.
* VM provisioning and availability of its management adapter are separate facts; this cost model does not enable a runtime endpoint.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Allocated VM/fleet CPU and memory hours are explicit physical usage. Management API counts never create VM-hours.
Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.
Excluded costs and workload features:
* Operating-system and software licenses, GPUs, reserved/Spot discounts, dedicated tenancy, disk IOPS, snapshots and backup.
* 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-8227eb3f52d5b31137926d19a9ab4e5307389386` / `2026-10-18.planning.1`. Curve: `workload-1`.
## Allocated virtual machine capacity → Virtual Machines
Origin API: `google::1.0.0::compute::instance`. Target backend: `azure::1.0.0::vm`.
**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.
**Designed mapping.** This cost model describes an intended adapter. Its estimated price does not establish a delivered or selectable backend.
### Allocated virtual machine capacity · Allocated VM CPU-hours per month
**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.
Exact sampled model outputs in USD/month. Difference means target minus origin; a positive difference means the target costs more.
| Allocated VM CPU-hours per month (vCPU-hour/month) | Origin | Target scenario | Target | Difference |
| -: | -: | - | -: | -: |
| 0 | 39.2 | Planning native backend | 43.58 | 4.38 |
| 1460 | 97.6 | Planning native backend | 110.74 | 13.14 |
| 5840 | 272.8 | Planning native backend | 312.22 | 39.42 |
| 23360 | 973.6 | Planning native backend | 1118.14 | 144.54 |
| 93440 | 3776.8 | Planning native backend | 4341.82 | 565.02 |
| 373760 | 14989.6 | Planning native backend | 17236.54 | 2246.94 |
**Curve assumptions**
| Target scenario | Assumption | Value | Unit |
| - | - | -: | - |
| Planning native backend | Origin price guess · VM allocated CPU | 0.04 | USD/vCPU-hour |
| Planning native backend | Origin price guess · VM allocated memory | 0.005 | USD/GiB-hour |
| Planning native backend | Origin price guess · VM allocated disks | 0.1 | USD/GiB-month |
| Planning native backend | Origin price guess · Billable VM network transfer | 0.09 | USD/GiB |
| Planning native backend | Target / origin VM CPU and RAM | 1.15 | 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 | 0.1 | 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 | 0.09 | 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 | 0.04 | USD/vCPU-hour |
| Planning native backend | Target price guess · GiB-hour | 0.005 | 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 | USD/input token |
| Planning native backend | Target price guess · output token | 0 | 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 exact directed mapping has a design profile. Cost modeling does not establish an implemented or deployable adapter.
* All default unit prices and capacity coefficients are editable authored planning guesses, not measured capacity or a provider quote.
* CPU, RAM, disks and network quantities remain independently editable. Increasing CPU does not silently increase the selected memory meter.
* VM provisioning and availability of its management adapter are separate facts; this cost model does not enable a runtime endpoint.
* All target rates are editable authored planning guesses, not verified current list prices, customer discounts or benchmark evidence.
* Allocated VM/fleet CPU and memory hours are explicit physical usage. Management API counts never create VM-hours.
Cost scope: Modeled target native service and explicitly modeled state allocation; hosting and Tensor9 fees only when supplied.
Excluded costs and workload features:
* Operating-system and software licenses, GPUs, reserved/Spot discounts, dedicated tenancy, disk IOPS, snapshots and backup.
* 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-104bfbe1a775421e6dbfd2eb33f598d2ca3841b4` / `2026-10-18.planning.1`. Curve: `workload-1`.
See the [service catalog](/byoc/service-adapters/catalog) for operation coverage, supported directions and backend limitations.
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