OpenAI launched GPT-6 Astra on September 3, 2026, pitching it as a generational leap that costs 2.5x more via API than the previous model. Before paying for that leap (or switching your workflow away from Claude/Gemini) you need to know where it actually wins, where it doesn't, and whether your business needs those capabilities today.
Who this is NOT for
The rollout is staged: it reaches Trusted Access/Daybreak enterprises first, and Plus/Pro/Business/Enterprise only "in the coming days" — if you're on the free ChatGPT plan, it's not your turn yet. It's also not for someone doing only simple text tasks: the capabilities that justify the price (computer use, cybersecurity, advanced science) don't show up in basic writing chats.
There's no absolute winner, and OpenAI doesn't tell it that way. Astra clearly wins on math (97.6% vs. Claude Fable 5.1's 87.8% on FrontierMath) and agentic coding, but loses on Artificial Analysis's aggregate index (61.2 vs. Fable 5.1's 65.7) and on Humanity's Last Exam with tools (57.2% vs. 65.0%). The "99.9%" on ARC-AGI-3 you'll see repeated everywhere depends on an expensive harness you won't use in practice — with a normal API call the real number is 17-63%. It's the best model today for computer use and offensive/defensive cybersecurity; it is not automatically the best model for everything.
Your first step
If you have ChatGPT Plus or Pro, wait for the activation notice (days, not weeks) and test it first on a computer-use or document-generation task, where it shows its biggest jump. If you use the API, run a small test at $10/$50 per million tokens before migrating a full workflow — the cost adds up fast.
The Guía GPT-6 Astra vs. Claude vs. Gemini implementation guide
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