Yearly running cost Assuming 1,200 benchmark runs a year
By hand $78K / year 1,200 hours of work
Subscription n.a.
This workflow $223 – 1.1K / year Machine usage only; setup, hosting and review are extra. Do you want to test model settings or also connect a service? Compare settings on the same model and requests. Keep a faster setup only if it passes your quality checks.
One benchmark run includes up to 100 benchmark requests.
Profile and tune a runtime Benchmark and tune an existing runtime $1,728 – 4,800 setup Integrate the approved configuration Integrate the approved runtime in staging $2,304 – 6,480 setup
Which system should it connect to?Existing inference staging service Private model-serving endpoint The model owner approves runtime changes. No automatic production rollout, model training, unsupported hardware kernels or quality degradation hidden behind a speed improvement.
What is included Benchmark the existing runtime and test compatible batching, caching and compilation settings.
Test batching, caching and compilation settings against your current setup. The connected option adds a staging service, load tests and a controlled rollout of approved settings.
Model scope: up to 1 licensed model.
Hardware scope: up to 1 hardware configuration.
Maximum input per request: up to 2,048 tokens.
Maximum output per request: up to 256 tokens.
Reference GPU memory: 24 GB.
Standard independent test set: at least 100 benchmark runs.
Strict independent test set: at least 200 benchmark runs.
What standard do you need? Choose the acceptance targets your provider must demonstrate on your own test material.
Standard Test the defined workload and controls. Baseline quality retained: ≥99% Successful throughput improvement: ≥10% Included Strict Tighter targets and a larger independent test set. Baseline quality retained: ≥99.5% Successful throughput improvement: ≥20% Setup +$360 – 1,200 My own requirements Agree different targets and scope with your provider. Quote separately
How these standards are measured Use a held-out request suite with mixed lengths, concurrency, cold starts, timeouts and output-quality failures. Compare identical hardware, workload, sampling settings and model revision; report successful throughput separately from attempted requests. Agree the holdout before tuning. Report each metric with its numerator, denominator and exclusions. Count failed and rejected attempts, not just accepted outputs.
Targets for your selected standard What is checked Target Baseline quality retainedOptimized aggregate quality score divided by the positive baseline score on the same independent fixture set, capped at full retention. ≥99% Successful throughput improvementAdditional successful requests per second divided by baseline successful requests per second at fixed concurrency and workload. ≥10% Tail-latency regressionPositive increase in end-to-end tail latency divided by baseline tail latency on the same requests; an improvement has no regression. ≤5% Approved runtime boundariesPassed model-integrity, access and rollback control cases divided by all tested control cases; any unauthorized deployment fails acceptance. ≥100%
Proposed targets apply to an independently labeled test set on the agreed workload, not every possible future input. Review each pilot result. Any unauthorized action or sensitive-data exposure fails acceptance.
How quickly do you need each benchmark run? Choose a processing-time target for the agreed reference workload; confirm feasibility with your provider.
Within 30 minutes Included Within 25 minutes Setup +$144 – 480 Within 20 minutes Setup +$288 – 840
Timing details This is time to produce a benchmark report, not the latency of an individual model request. Include warm-up, the baseline and candidate runs, validation and permitted retries.
The target applies to at least 95% of agreed test runs, with 1 in progress at a time.
How much should each benchmark run cost? Choose a machine-cost cap for the agreed workload. A lower cap needs testing without relaxing the selected quality targets.
Up to $1.50 Included Up to $1.25 Setup +$144 – 480 Up to $1.00 Setup +$288 – 840
Cost details Includes allocated benchmark GPU time, bounded report-assistance calls, retries and hosting. Continuous production serving, model licenses and hardware purchases are separate.
Reference machine cost: $0.29 – 1.14 per benchmark run at 100 benchmark runs a month. The selected cap is a target to test, not a replacement for this estimate.
Where do you want it to run? Run the workflow in your cloud or on your own machine. Choose separately whether it may use an external AI model.
Run it onYour cloud Local environment AI model accessApproved model API No external model calls
Data and access details Run in your controlled cloud environment with scoped access and retained review records.
Use an approved external model with the agreed data-processing terms and minimum necessary input.
Local hosting does not itself keep data offline. Approved business-system connections may still use the network. The target model runs on the agreed hardware in either option. External model access applies only to optimization and report assistance; it never grants permission to send model weights or production prompts elsewhere. Private running cost must be measured in the pilot.
How do you want to use it? Choose a browser interface, an MCP tool for your current agent, or a standalone agent.
Web page Inspect each benchmark run in a private browser interface. Included Your AI agent Call the workflow through MCP; the same access and approval rules apply. Setup +$72 – 360 Standalone agent Use a dedicated agent with the agreed triggers and controls. Setup +$144 – 480