OpenAI Opens GPT-6 Astra to Business Subscribers Days After Rating It Critical for Cyber Capability

OpenAI has moved GPT-6 Astra from a staged launch into broad paid availability. The Russian-language technical channel AI ML Big Data reported that Pro, Enterprise and Business Premium subscribers now reach the model directly inside ChatGPT Work, inside the Codex development environment and through the applications programming interface (API), with Plus and standard Business accounts to follow over several days.

The capability numbers OpenAI published are large. The company reports 72.6% on OSWorld 2.0 against 65.7% for its prior model at roughly 47% less time per task, 97.6% against 83.0% on FrontierMath Tier 4, and 92.7% against 76.9% on ScreenSpot-Pro, which measures whether a model can locate and click the correct pixel in a dense interface. Every one of those figures comes from OpenAI's own launch material rather than from independent reproduction, and the OSWorld and ScreenSpot comparisons are drawn against GPT-5.6 Sol, OpenAI's previous release, not against Anthropic's or Google's current models.

The security classification is the part that changes how engineers must deploy it. OpenAI says Astra is the first model to reach the Critical cybersecurity tier of its Preparedness Framework, meaning it can develop working zero-day exploits against hardened real-world systems without human direction. It scored 100% on ExploitBench for turning documented vulnerabilities into working exploits, and 39% on the June to August 2026 slice covering vulnerabilities disclosed after training. CSO Online reported that the public deployment refuses proof-of-concept exploit generation, with looser access promised to vetted defenders through a program OpenAI calls Daybreak.

For builders, the API documentation is where the structural change shows up. Astra supports asynchronous tool calling, so the model keeps reasoning or answers independent parts of a request while an application executes a tool and returns the result later against the original call identifier. Context runs to 1,050,000 tokens with up to 128,000 output tokens, and pricing is $10 per million input tokens and $50 per million output tokens, well above the $1.25 and $4.25 Meta charges for Muse Spark on its standard tier.

The clearest way to read this is that OpenAI is doing two things at once. It is asserting a capability jump that only it has measured, and it is using a self-defined safety tier to justify gating the most commercially valuable version of that capability behind a vetting program it controls.