Claude Opus 5.5 and GPT-6 Sol launched on September 22, 2026. The obvious comparison is price per token. The useful comparison is cost per accepted task.
GPT-6 Sol has the lower rate card. Claude Opus 5.5 has the stronger provider-reported scores on several agentic coding tests. Neither fact tells you which model is cheaper for your repository, tools, prompts, stopping rules, and quality bar.
Price comparison
For standard short-context API work, GPT-6 Sol costs $2 input, $0.20 cached input, $2.50 cache writes, and $10 output per 1M tokens. Claude Opus 5.5 costs $4 input, $0.20 cache reads, $5 five-minute cache writes, and $20 output per 1M. Anthropic also charges $8 per 1M for one-hour cache writes.
That makes Opus 5.5 twice Sol’s fresh-input, cache-write, and output rate at equal token volumes. Cache reads cost the same. GPT-6 Sol also applies a higher rate when a request exceeds 272,000 input tokens; Opus 5.5 publishes one standard 1M-context rate.
The equal-volume verdict is simple: Sol wins. Opus has to reduce the amount of work needed to justify its premium.
Why cost per task can reverse the result
An agent bill is not one prompt multiplied by one rate. A useful model is:
effective task cost = model tokens + cache writes + tool fees + retries + failed runs + reviewer time
If Sol needs ten calls and Opus needs five, the nominal 2× price gap can disappear. If both finish in the same number of calls, Sol usually keeps the advantage. If the cheaper run produces a patch that fails tests or needs an engineer to repair it, its token saving may be irrelevant.
This is why “40% lower typical workload cost” means something different from “20% cheaper tokens.” Anthropic says Opus 5.5 is 20% cheaper than Opus 5 on standard input/output rates, 60% cheaper on cache reads, and about 40% cheaper on a typical default-settings workload because it also uses fewer tokens per task. The final number is a provider estimate, not a universal invoice discount.
Use the AI agent cost calculator to enter turns, tokens per turn, cache share, retries, tools, and success rate. Compare dollars per accepted result—not dollars per first attempt. The live Anthropic pricing page tracks the underlying rate card separately.
Our first exact-route control makes the point. Opus 5.5 and GPT-6 Sol both scored 49/49 with zero errors on the same deterministic suite, but Opus cost $0.05422 versus $0.015922 for Sol: 3.4× more per correct answer. Opus used 5,330 prompt and 1,645 completion tokens; Sol used 3,426 and 907. On these short machine-graded tasks, Opus did not recover its rate premium through efficiency.
The same run still showed meaningful progress over Opus 5. Opus 5.5 scored 49/49 for $0.05422; Opus 5 scored 48/49 for $0.09366. That is 43% lower cost per correct answer, close to Anthropic’s 40% typical-workload estimate—but it does not establish the result for repository-scale coding. See the live Labs leaderboard for scope and traces.
Benchmark comparison without the hype
Anthropic reports Opus 5.5 at 66.4% on Terminal-Bench 4.0 and 54.4% on FrontierCode, versus 37.3% and 47.5% for GPT-6 Sol in the same launch table. It also reports 57.8% on CursorBench, compared with 41.7% for Sol.
Those figures are useful shortlist evidence, but they are not a neutral head-to-head test. Anthropic publishes the table, effort settings differ by result, and the vendors use their own harness and cost assumptions. Anthropic’s claim that default-effort Opus 5.5 beats GPT-6 Astra at about one-fifth of the cost applies to selected FrontierCode and GDPval comparisons. It does not mean every Opus request costs 80% less than Astra.
At equal token volumes, Opus 5.5’s standard input and output prices are 60% below GPT-6 Astra’s short-context rates. Any larger saving must come from the task trace: fewer tokens, calls, retries, or failures.
OpenClaw and Hermes subscription reality
The model can be attractive while the buying route is not ready.
The OpenClaw build checked on launch day did not yet list Opus 5.5 in its Anthropic model catalog. OpenClaw can run Claude through the official CLI using claude -p; its documentation says that route consumes the signed-in subscription’s Agent SDK limits. But a missing catalog entry and the model’s breaking request changes mean users should wait for a tested compatibility path or validate a deliberate override.
Hermes has a separate experimental Claude Subscription DirectSDK plugin. Its September 22 catalog lists claude-opus-5-5[1m], requires Hermes 0.21.4 or newer plus a logged-in Claude Code CLI, and routes Hermes turns through the subscription. The plugin’s own test found the same metering as claude -p, about 1.7× the interactive Claude Code TUI meter, while Hermes sent about 0.6× as many tokens as native Claude Code on identical coding tasks. Those two effects can offset each other; only a paired workload test answers the bill.
Do not confuse that plugin with Hermes’ direct Anthropic OAuth path. Hermes documents different plan and extra-usage behavior for that route. Confirm which provider is selected before treating a subscription as included usage.
Migration risks that affect cost
Opus 5.5 always uses adaptive thinking and rejects requests that try to disable it. Forced tool choice is unsupported. Thinking blocks are tied to the model and conversation, and one older computer-use tool version is rejected on Anthropic’s API and Google Cloud. Progress text between tool calls also moves into thinking blocks.
A harness that mishandles any of these changes can retry, lose reasoning state, show silent progress, or fail a tool round. That is not a small integration detail: every extra loop raises the effective cost.
Run a controlled pilot with the same task set, repository commit, tool list, permissions, cache state, effort, and stop policy. Record successful tasks, total input, cache reads and writes, output, tool calls, wall time, retries, failures, and human review minutes.
Which model should you choose?
Choose GPT-6 Sol when equal-volume price, predictable API economics, and broad daily throughput matter most. It is the safer rate-card winner.
Choose Claude Opus 5.5 when difficult coding or knowledge work is expensive mainly because weaker runs wander, retry, or need substantial review. Its price premium is rational only when your own traces show a better completion rate or fewer steps.
Keep GPT-6 Luna or Claude Sonnet 5 as cheaper controls. A premium model should beat them on cost per accepted result, not merely on a launch benchmark.
Sources: Anthropic’s Opus 5.5 announcement, model overview, and migration changes; OpenAI’s GPT-6 Sol and Luna announcement; OpenClaw’s local Anthropic provider documentation; and the Hermes DirectSDK plugin. Checked September 22, 2026.