What the rate comparison does and does not show
Use standard token rates to establish a baseline, not to choose a coding agent on their own. The chart and calculator compare equal volumes; an agent can change its bill by changing how much work it performs.
This page preserves the September launch comparison between Claude Opus 5.5 and GPT-6 Sol. Our tracker now marks GPT-6 Sol as legacy and lists GPT-6.1 Sol as active. Legacy does not mean unavailable, but a new deployment should evaluate the successor rather than treating the older model as the default.
The generated table separates fresh input, cached input, and output. For request-specific conditions, use Anthropic pricing and OpenAI pricing: cache creation is distinct from cache reads, and Sol’s long-context tariff can differ from its standard rates. Do not apply the chart to an oversized prompt without checking the relevant tier.
Why cost per task can reverse the result
An agent bill includes more than one prompt:
effective task cost = token charges + cache creation + tool fees + retries + failed runs + reviewer time
| Decision variable | Keep constant or record | Why it changes the result |
|---|---|---|
| Task and repository | Same issue, commit, tests, and acceptance criteria | Easier tasks can make a model look more efficient |
| Model settings | Exact route, effort, tools, and output caps | Different settings produce different token volumes |
| Cache state | Cold and warm runs separately | Repeated context may have a different tariff |
| Recovery | Retries, failed tool calls, and fallback traffic | A cheap first attempt can become an expensive workflow |
| Human work | Review and repair minutes | A passing patch can save more than its token premium |
| Pricing data: How we verify → | ||
Use the token calculator for the standard-volume estimate and the agent cost calculator for turns, retries, tools, and success rate. Divide the full evaluation bill by accepted results, not by attempted tasks.
Our historical 49-task deterministic route check gave both models 49 correct answers without errors, but Opus used more prompt and completion tokens. The archived launch-day comparison was 3.4× more per correct answer for Opus, not a current cost estimate. That narrow result did not show an efficiency advantage for Opus; it also did not test repository-scale coding. Consult the Labs leaderboard for available traces and test scope, rather than treating a launch-day run as a current model ranking.
Qualify benchmark evidence
Anthropic’s launch comparison reported stronger Opus results on several coding and agent benchmarks. These are provider-published measurements with harness and effort assumptions, not a neutral guarantee about your application.
A claim about lower typical task cost combines token rates with behavior: fewer calls, shorter traces, or more accepted outputs. Reproduce those gains on your own tasks before changing a production budget.
OpenClaw and Hermes subscription reality
Subscription access is a separate procurement question. OpenClaw and Hermes compatibility notes in the original launch coverage described the software and plugins checked in September; they are not a statement of current support. Verify the installed version, exact model identifier, authentication path, plan terms, and usage meter before relying on either integration. A browser subscription does not automatically entitle a third-party harness to API use.
A practical migration decision
Keep GPT-6 Sol if an existing integration remains supported and passes your requirements. For a new integration, test GPT-6.1 Sol alongside Opus 5.5 and a cheaper control such as Claude Sonnet 5; compare accepted-task cost rather than moving every request to the newest or strongest model.
Before an Opus migration, check Anthropic’s model migration documentation for thinking, tool-choice, and conversation-state changes. A harness that retries rejected parameters or loses reasoning state can erase a nominal saving.
Run a bounded pilot with identical permissions, stop rules, and review criteria. Keep the existing route available until the replacement clears quality, latency, reliability, and cost requirements. Our developer API selection guide explains how to turn that pilot into a routing policy.
Open-model control: If the task may not need a frontier model, inspect Novita’s managed open-model catalog for a separate budget candidate. This is not an equivalent Opus or Sol endpoint; verify the model and host terms before comparing it.
Affiliate disclosure: we may earn a commission through that link, at no extra cost to you. Compensation does not determine the rates or recommendations.
Official references: Anthropic’s Opus 5.5 announcement, Anthropic pricing, OpenAI pricing, and GPT-6.1 Sol documentation. The displayed rates come from our maintained dataset; this refresh does not claim a new benchmark run.