GPT-6 Astra in Practice: Tests, Use Cases, and Feedback

A user reports that running several tasks with GPT-6 Astra Light in Codex used under 10% of their 5-hour quota, versus roughly 50% for similar work before.

The author added DeepSeek to a benchmark comparison with GPT-6 Astra and Fable 5.1 and found it performs well at 98% lower cost, 70-80x cheaper than frontier models.

Both list $10 input and $50 output per million tokens, but Astra's cache reads cost 4x more and long inputs carry a surcharge, so the author spent 20 hours working out the real cost gap.

A fact-check found the viral post's architecture is sound and Astra's $10 per million token pricing is real, but the claimed Sharpe, drawdown and win rate don't match the code.

Pliny published GPT-6 Astra's full system prompts and tool definitions, over 330k characters of prompts and over 1.1M of tools, now on GitHub.

OpenAI says GPT-6 Astra is available in ChatGPT Work, Codex and the API for Pro, Enterprise and Business Premium users, with Plus and Business to follow within days.

CADArena tests AI reconstruction of editable 3D parts from 18 real engineering drawings across five CAD platforms, finding Astra and Fable 5.1 lead but feature trees stay messy.

Users report that Astra Medium burns through their allowance in just a few turns and ask whether Medium can sometimes use more quota than Extra High.

A joke post contrasts Anthropic's Fable 5.1 and OpenAI's GPT-6 Astra with bored AI posters who respond with their own dubious benchmark.

The author had Codex with GPT-6 Astra xhigh use a music theory CLI and 320 skills to find sheet music for Clare's Dragoons and compose Mozart-style piano variations.

An OpenAI employee cites the Artificial Analysis Intelligence Index to say GPT-6 Astra at Max reasoning scores higher and costs less per task than Opus 5 at High.

The author says the skill generates a 3D scene in one 25-minute run using 7% of a ChatGPT Plus quota, but notes Astra is expensive and full games still need smaller models.