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OpenAI introduced GPT-6.1 Sol on September 29, 2026, positioning it as a lower-cost option with near-Astra performance for complex coding, computer use, and professional work. That is not a claim that Sol matches GPT-6 Astra on every task: OpenAI recommends testing both models on your own workload before choosing.
What OpenAI says about GPT-6.1 Sol and Astra
OpenAI’s GPT-6.1 Sol model page describes the model as delivering “near-Astra performance at a lower cost” for complex coding, computer use, and professional work. The wording is a broad vendor positioning, not a published finding that the models perform identically across all tasks.
The API model ID is gpt-6.1-sol. OpenAI’s API changelog dates its release to September 29, 2026. The available official material does not establish a universal winner or provide evidence of equal results on every workload.
How much does GPT-6.1 Sol cost?
OpenAI’s September 29, 2026 API changelog lists the following standard rates for prompts with up to 272K input tokens:
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| Token type | GPT-6.1 Sol price per million tokens |
|---|---|
| Input | $2 |
| Cached input | $0.10 |
| Cache write | $2.50 |
| Output | $10 |
OpenAI’s published standard input and output rates for Sol are one-fifth of its listed $10 input and $50 output rates for Astra. That price ratio does not show that Sol produces equally good results for every task. Compare total usage costs for your workload, including cached input, cache writes, and generated output; the listed rates are for prompts up to 272K input tokens.
What to compare before choosing a model
OpenAI recommends evaluating GPT-6.1 Sol and Astra on your own tasks. A useful comparison measures the quality and success of the same work, rather than treating a broad model description or token price as a substitute for task results.
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- Task success and output quality: Run representative coding, computer-use, or professional-work tasks, then assess correctness and how much review or rework each answer requires.
- Total token cost: Include input, cached input, cache writes, and output at the rates applicable to your prompt size.
- Latency: Compare response time using the reasoning settings and tools you intend to deploy. The cited official material does not establish a universal latency advantage.
- Context and output needs: Check whether each model’s limits fit the size of your prompts and expected responses.
- Data residency: Confirm that the available residency options meet your deployment requirements.
Context limits and data residency
OpenAI’s model documentation, accessed October 3, 2026, lists a 1,050,000-token context window and a maximum output of 128,000 tokens for GPT-6.1 Sol. It lists US and EU data residency support, but fast mode is unavailable when using EU data residency.
What OpenAI’s safety addendum says
In its September 29, 2026 addendum to the GPT-6 Astra system card, OpenAI classifies GPT-6.1 Sol as Critical capability in cybersecurity and High for biological and chemical capability. These are OpenAI’s classifications, not independent verification.
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OpenAI also cautions that the addendum’s evaluations were conducted in a research environment or via API and may differ from production ChatGPT. Differences in prompts, available tools, and reasoning effort can affect results, so the evaluations should not be assumed to predict every deployment’s behavior.
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