GPT‑6 Astra

# GPT‑6 Astra Source: [https://simonwillison.net/2026/Sep/3/gpt6-astra/](https://simonwillison.net/2026/Sep/3/gpt6-astra/) 3rd September 2026 \- Link Blog **[GPT‑6 Astra](https://openai.com/index/gpt-6-astra/)**\([via](https://news.ycombinator.com/item?id=49554643)\) GPT\-6 Astra is "rolling out today to a limited set of organizations and over the coming days will become available to all ChatGPT Plus, Pro, Business, and Enterprise users, as well as through the OpenAI API and AWS" \- I've not tried it yet myself, so I don't have a great deal to say about it yet\. It's going to be API priced at the same rate as Claude Fable 5 and 5\.1: $10/million input and $50/million output\. This is clearly OpenAI's Fable competitor, and appears to score higher than Fable on most of OpenAI's self\-reported benchmarks\. Most impressively, Astra scores 99\.9% on the recent \(released in March\)[ARC\-AGI 3 benchmark](https://arcprize.org/arc-agi/3)\- though notably Fable 5 does not yet have a published result, and the[ARC\-AGI blog notes](https://arcprize.org/blog/astra)that the 99\.9% score was achieved for $19K using OpenAI's custom "Provider Adapter harness", while the default ARC\-AGI harness scored 62\.7% for $26K\. > The Provider Adapter harness preserves opaque reasoning state between requests and uses compaction for longer conversations, allowing the model to reuse prior work\. Unsurprisingly, given[the recent Hugging Face incident](https://simonwillison.net/tags/openai-hugging-face-incident/), Astra is a beast at security tasks\. It scores 100% on ExploitBench \(GPT\-5\.6 Sol got 78\.5%\), 42\.4% on ExploitGym \(Sol got 30\.3%\), and 99\.2% within four attempts on SRE\-Bench binary reverse engineering compared to Sol's 68\.7%\. It's also better at long context: on OpenAI's eight\-needle benchmark it got 100% at 256K–512K tokens and 96\.3% at 512K–1M tokens\. OpenAI may have vanquished one of the ongoing challenges with long context processing\. It doesn't win at everything though\.[Artificial Analysis](https://twitter.com/ArtificialAnlys/status/2095595489031000350)note that Astra is still beaten by Fable on their Intelligence Index: > **Sits beside GPT\-5\.6 Sol in Intelligence**: GPT\-6 Astra scores equal to GPT\-5\.6 Sol in the Index at 61\. This is 5 points lower than Claude Fable 5\.1 \(max with fallback\)\. The model also trails Meta’s newly released Muse Spark 1\.3 \(max\)\. It did better on their Coding Agent Index: > **Leads Coding Agent Index cost efficiency frontier**: At max effort, GPT\-6 Astra costs about the same as GPT\-5\.6 Sol \(max\) while scoring 2 points higher on the Index\. Per task, the model is less than half the cost of Claude Fable 5, for the same score\. I'll write more about Astra once I get access to it\. The API model label once it rolls out will be`gpt\-6\-astra`\.