GPT-6 Sol vs Claude Opus 5.5: Benchmarks, Real Cost and Which to Use

In the GPT-6 Sol vs Claude Opus 5.5 matchup, Opus 5.5 is the stronger model on independent tests, while GPT-6 Sol is half the price per token and streams output faster. Choose Opus 5.5 for long agentic coding, documents over 272K tokens and careful writing. Choose Sol for clear, checkable, high-volume work where cost matters most.

This comparison relies on published pricing, Artificial Analysis measurements and third-party tests; LMSPedia ran no tests of its own. Figures are as of 24 September 2026.

Did GPT-6 Sol and Claude Opus 5.5 launch on the same day?

Yes. Anthropic released Claude Opus 5.5 on 22 September 2026, and OpenAI announced GPT-6 Sol and GPT-6 Luna about an hour later, according to Simon Willison’s same-day write-up of Opus 5.5, Sol and Luna. Both launches led with lower prices, and neither company could benchmark against the other’s new model.

OpenAI’s GPT-6 Sol and Luna announcement says Sol costs half of GPT-5.6 Sol’s promotional price (see GPT-6 Sol and Luna explained). Opus 5.5 is the first Opus price cut: tokens are 20% and cache reads 60% cheaper than Opus 5, per our Claude Opus 5.5 explainer.

GPT-6 Sol vs Claude Opus 5.5: how do price and specs compare?

GPT-6 Sol costs $2 per million input tokens and $10 per million output tokens, exactly half of Claude Opus 5.5’s $4 and $20. Both offer roughly a million tokens of context and 128K tokens of output. The differences that change real bills are Sol’s surcharge above 272K input tokens and Opus’s always-on thinking.

Sources: the OpenAI GPT-6 Sol model and pricing docs and Anthropic’s Claude Opus 5.5 announcement, per million tokens, as of 24 September 2026.

Why don’t the vendor benchmarks for Sol and Opus 5.5 line up?

Because each lab benchmarked against the other lab’s earlier models. OpenAI compared GPT-6 Sol with Claude Opus 5 and Fable 5.1; Anthropic compared Opus 5.5 with GPT-5.6 Sol and GPT-6 Astra. Shared benchmark names also hide different versions and scoring, so the vendor tables cannot be stacked into a fair head-to-head.

On AutomationBench, Sol scores 33.2% at xhigh (OpenAI-reported) and Opus 5.5 40.0% at max (Anthropic-reported), but the scoring methodology differs. Anthropic’s 66.4% on Terminal-Bench 4.0 came in lower on independent re-runs: 59.6% at Artificial Analysis and 61.6% at Vals. Our GPT-6 Astra benchmarks guide covers OpenAI’s flagship.

Why are the OSWorld 2.0 scores for Sol and Opus 5.5 different?

The labs used different OSWorld 2.0 variants. OpenAI reports 60.5% for Sol at xhigh on an “offline set, partial score” version dated 8 August 2026 (OpenAI-reported). Anthropic’s 81.8% partial score for Opus 5.5 uses a different task set (Anthropic-reported). The two numbers are not comparable.

GPT-6 Sol vs Claude Opus 5.5 benchmarks: what do independent tests show?

Artificial Analysis runs both models on the same test setup. Its Intelligence Index v4.3.2 puts Claude Opus 5.5 at 58 at max effort and GPT-6 Sol at 48. Opus leads on coding, knowledge work and science evals, but Sol costs far less per task: about $1.06 against $5.98, both at max.

The Artificial Analysis GPT-6 Sol vs Claude Opus 5.5 comparison shows Opus ahead on Terminal-Bench 4.0 (59.6% to 43.9%). Some results are close: AA-LCR long-context reasoning is 84.7% to 83.7%, and on AutomationBench-AA, Opus at medium scores 61.2% to Sol at max’s 61.6%. Opus was tested with Anthropic’s default fallback enabled.

What effort level should you use on Opus 5.5 vs Sol?

Effort changes the verdict more than the model name. As DigitalApplied’s cost-per-benchmark analysis puts it, “Opus 5.5 at its default outscores Sol at max”, costing about 26% more per task and scoring 3.7 points higher.

Sol is the cheaper route to any index score up to about 44. Beyond that it spends heavily for small gains.

GPT-6 Sol vs Opus 5.5 pricing: how much cheaper is Sol in real use?

On list price Sol is half the cost of Opus 5.5, but real bills depend on caching, request size and effort. Identical $0.20 cache reads narrow the gap on agent loops, while Opus’s heavier token use widens it: on the Artificial Analysis index, Opus costs over four times as much per task at every effort level.

Worked example at list prices, ignoring cache writes: 100K input (80K cached) plus 10K output costs about $0.16 on Sol ($0.04 fresh, $0.016 cached, $0.10 output) and $0.30 on Opus ($0.08, $0.016, $0.20). Sol is roughly 53% of Opus before token-use differences.

What happens to the price gap above 272K tokens?

Once a request passes 272K input tokens, OpenAI bills the whole request at 2x input and 1.5x output, so Sol becomes $4 input and $15 output. Opus 5.5 stays at $4 and $20 across its full window. Input prices match, and Sol’s saving shrinks to its cheaper output.

Take 400K input (300K cached) plus 10K output. Sol costs $0.40 fresh, $0.12 cached (that rate doubles too) and $0.15 output: $0.67. Opus costs $0.40, $0.06 and $0.20: $0.66. DataCamp’s modelling likewise puts the gap at about 8% above 272K.

Which is better for coding, GPT-6 Sol or Opus 5.5?

Opus 5.5 is the better choice for long, multi-step coding agents: it scores 59.6% on Artificial Analysis’s Terminal-Bench 4.0 run against Sol’s 43.9%. Sol is the better value for bounded tasks. In DataCamp’s one-shot game test it produced the more polished result at about a third of the cost.

In DataCamp’s GPT-6 Sol vs Claude Opus 5.5 test, Tom Farnschläder had both build a gravity-flip Tetris. Sol took six turns, cost $0.26 and averaged 5.0 out of 5; Opus took three turns, cost $0.87 and averaged 4.3. The verdict: “Both got the hard logic right, and Sol shipped the more polished game.” DataCamp still picks Opus for unattended agents; our roundup of AI tools for developers shows where each plugs in.

Which is faster, GPT-6 Sol or Claude Opus 5.5?

Sol streams tokens faster, but the answer depends on effort. Artificial Analysis measures Sol at max at about 131 tokens per second, against roughly 76 to 93 for Opus 5.5 across its effort levels. At the highest settings, both models can think for more than two minutes before the first token appears.

Artificial Analysis recorded about 150 seconds to first token for Sol at max and 160 for Opus at xhigh. At low effort Sol starts in 1.69 seconds and Opus in 7.03, and only Sol offers a “none” level. Anthropic says Opus 5.5 generates output more than 30% faster than Opus 5 (Anthropic-reported).

How do the safeguards differ between Sol and Opus 5.5?

Opus 5.5 ships with safeguards similar to Claude Fable 5.1’s. Anthropic says “most cybersecurity tasks will be re-routed to Opus 4.8” and higher-risk biology requests fall back to Opus 5, though routine bug fixing is unaffected. None of the OpenAI sources we reviewed describe comparable model re-routing for GPT-6 Sol.

Anthropic’s help article on why Claude switched models calls it “a narrow set of higher-risk requests”, such as exploit generation. On claude.ai a notice appears when a switch happens; on the API, fallback is an opt-in beta, otherwise you get a refusal. The Cyber Verification Program will cover Opus 5.5 “soon”, but not yet.

Is GPT-6 Sol or Opus 5.5 better for writing?

Opus 5.5 is the stronger writer on current evidence. Anthropic says it “puts the most important information up front” and “follows the writing rules you give it” (Anthropic-reported). Independent knowledge-work evals agree: at max effort, Opus leads Sol by more than 300 Elo on two of Artificial Analysis’s document-heavy tests.

Those are GDPval-AA (1,846 against 1,487) and AA-Briefcase (1,822 against 1,483). OpenAI’s docs pitch Sol at “complex coding and agentic workflows”, not prose. For client-facing documents, start with Opus and still plan a human edit.

What are reviewers saying about Sol vs Opus 5.5?

Reviewers broadly agree on the trade-off: Opus 5.5 is the more capable model and Sol is the better deal. Simon Willison made both his defaults. The main complaints are Opus’s cost and wasted tokens at max effort and its cyber routing, and Sol’s lower scores, slow first tokens and long-context price jump.

Willison’s pelican test on Opus at max ran nearly 20 minutes and hit the 128K output limit mid-reasoning, at $2.56 per failed attempt. OpenAI’s charts compared Sol with Opus 5, not 5.5, and ChatGPT offers Sol only in Work and Codex, not Chat. In Sol’s favour, DataCamp found it can win on polish, and Artificial Analysis rates it the faster, cheaper-per-task model.

Which should you choose: GPT-6 Sol or Claude Opus 5.5?

Pick by job, not by brand. Use Opus 5.5 where a mistake is expensive: long coding agents, big documents and client-facing writing. Use Sol where the task is clear, checkable and repeated at volume. Many teams will run both, with Sol on routine work and Opus handling escalations and review.

If Sol is more than you need, Luna costs a twentieth as much; our GPT-6 Sol vs Luna vs Astra comparison explains when to step down. Weighing Opus against Fable? Read Claude Opus 5.5 vs Fable 5.1 before paying 2.5x per token.

Conclusion

Neither model wins outright. Opus 5.5 scores higher on the Artificial Analysis index at every effort level; Sol is the cheaper, faster default for work you can verify. Effort is the biggest lever: Opus at medium beats Sol at max, and Sol at medium costs $0.25 per index task.

Before committing, run 20 real backlog tasks through both models at medium effort and record cost per accepted result, not per token. Count how many calls cross 272K input tokens, since that alone can decide it. Then browse our AI tools directory for platforms offering both.