Back to Blog
    lab news

    Claude Sonnet 5.5 vs GPT-6.1 Sol: same base price, different trade-offs

    September 30, 2026The AI Take5 min readPrimary source

    Anthropic released Claude Sonnet 5.5 on 28 September 2026. OpenAI followed with GPT-6.1 Sol on 29 September. Both target everyday professional and coding work, and both list standard API rates of $2 per million input tokens and $10 per million output tokens. The useful differences are where you can use them, how they bill a complete job, and what an existing integration needs to change.

    For a small team, the first question is which model fits the work and tools already in use. This is a source-researched comparison of the announcements and documentation as of 30 September, not a hands-on benchmark.

    What launched, and where you can use it

    Claude Sonnet 5.5 is available across Anthropic's platforms and through AWS, Google Cloud and Azure. Its Claude API identifier is claude-sonnet-5-5. Anthropic presents it as the everyday companion to Opus 5.5 for scoped work such as bug fixes and producing documents, presentations and spreadsheets. It says Opus remains the stronger option for complex, open-ended judgment. See Anthropic's announcement.

    GPT-6.1 Sol is available in the OpenAI API as gpt-6.1-sol. In the apps, it is rolling out to eligible paid users in ChatGPT Work and Codex, beginning with Pro and expanding to Plus, Business, Enterprise and Edu. It is not available in Chat yet. Managed-workspace permissions can also affect access, so check the model picker in the product your team actually uses before promising everyone a migration. The OpenAI announcement and 29 September release notes establish the launch and rollout separately.

    That makes this a fresh comparison with GPT-6.1 Sol, rather than a repeat of last week's GPT-6 Sol and Luna guide.

    The same base price can produce a different bill

    These are standard API prices in USD per million tokens, checked on 30 September 2026. They are not monthly subscription prices.

    API detailClaude Sonnet 5.5GPT-6.1 Sol
    Standard input$2$2
    Standard output$10$10
    Cached input/read$0.20$0.10
    API context window1 million tokens1,050,000 tokens
    Maximum output128,000 tokens128,000 tokens
    Long-context pricingStandard rates across the full 1M windowAbove 272K input tokens: 2× input/cache and 1.5× output for the entire request

    The long-context row matters if an agent sends a large codebase or document pack on each turn. OpenAI's documentation applies the higher rates to the whole qualifying request. Anthropic's pricing documentation includes the full one-million-token window at standard rates. Neither API ceiling guarantees the same limit in an app or subscription. Sources: Sonnet specifications, Claude API pricing and GPT-6.1 Sol specifications.

    Caching also has write costs. Anthropic lists $2.50 for a five-minute cache write and $4 for a one-hour write; OpenAI lists $2.50 for cache writes. A lower read rate helps only when the workflow actually reuses cached context. Tool use, retries, output length, reasoning effort and provider-specific options can change the final charge.

    Anthropic reports more than 30% faster output generation than Sonnet 5 and up to 30% lower cost per task in its tests because Sonnet 5.5 used fewer tokens. Its standard input and output rates did not fall by 30%. Those are vendor-reported workload results, not savings every team can apply to its bill. OpenAI's one-fifth-price positioning compares Sol with Astra, not with the earlier GPT-6 Sol.

    Which should you try first?

    Start with the environment where a useful task can finish with the least setup.

    • Already working in Claude or Claude Code? Try Sonnet 5.5 on a bounded job you repeat: a contained bug fix, a document assembled from approved sources, or a spreadsheet with explicit checks. Keep Opus available for work that needs broader judgment
    • Already working in Codex or ChatGPT Work? Try GPT-6.1 Sol on a coding or computer-use job with a clear done condition. Check account access first and keep an existing working model available during the trial
    • Choosing an API for long-context work? Compare actual token usage and the Sol long-context threshold before treating the matching $2/$10 rates as an equal-cost result

    These are starting hypotheses based on documented availability and positioning. They are not findings that one model has beaten the other on these tasks.

    The launch charts do not settle this matchup

    Sonnet 5.5's launch charts compare it with GPT-6 Sol. OpenAI's GPT-6.1 Sol announcement highlights selected comparisons with Opus 5.5 and Astra. Those comparisons do not establish a direct Sonnet 5.5 versus GPT-6.1 Sol winner.

    Even similar-looking computer-use scores can involve different benchmark versions and test conditions. Harnesses, effort settings, tools and fixes affect what a score measures. Read the methods behind a chart before copying its ordering into a buying decision. For the practical scorecard, use our coding-agent pilot guide, updating the model IDs for this week's releases.

    Check compatibility before replacing a model ID

    Sonnet 5.5 is not necessarily a one-line change in an existing agent. Anthropic documents changes to thinking, forced tool choice, streamed content and computer-use tool compatibility. A parser or tool loop that worked with Sonnet 5 may need attention. Follow the Sonnet 5.5 migration guide for the provider route you use.

    For GPT-6.1 Sol, OpenAI documents tool calling through the Responses API; Chat Completions supports the model without tools. Check the model's supported interfaces before moving an existing tool-calling integration.

    Available now is different from coming soon

    The two base models have launched. GPT-6.1 Sol's app access is still a rollout. Anthropic says Haiku 5.5 is coming in the weeks ahead, while OpenAI says GPT-6.1 Sol Ultrafast is coming in the days ahead. Do not build a deadline around either future option being available in your account today.

    Pick five recurring tasks, keep the source files and acceptance checks the same, and record total cost, elapsed time, retries and human repair time. Include failed attempts. The decision is which model produces more work your team can accept within its budget and review capacity.

    Editorial note: The AI Take reviewed the linked official announcements and live documentation on 30 September 2026. We did not benchmark these models for this article. Performance and savings claims are attributed to the vendors; pricing, access and rollout details can change.

    Working through a similar decision?

    Tell us the task, the tools you use, and where a person needs to review the result. Your message will include this article's URL so we know the context.

    Ask a workflow question