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OpenAI has given us GPT-5.1-Codex-Max, their best coding model for OpenAI Codex.

They claim it is faster, more capable and token-efficient and has better persistence on long tasks.

It scores 77.9% on SWE-bench-verified, 79.9% on SWE-Lancer-IC SWE and 58.1% on Terminal-Bench 2.0, all substantial gains over GPT-5.1-Codex.

It's triggering OpenAI to prepare for being high level in cybersecurity threats.

There's a 27 page system card. One could call this the secret ‘real’ GPT-5.1 that matters.

They even finally trained it to use Windows, somehow this is a new idea.

My goal is for my review of Opus 4.5 to start on Friday, as it takes a few days to sort through new releases. This post was written before Anthropic revealed Opus 4.5, and we don’t yet know how big an upgrade Opus 4.5 will prove to be. As always, try all your various options and choose what is best for you.

The Famous METR Graph

GPT-5.1-Codex-Max is a new high on the METR graph. METR's thread is here.

Prinz: METR (50% accuracy):

GPT-5.1-Codex-Max = 2 hours, 42 minutes

This is 25 minutes longer than GPT-5.

Samuel Albanie [...]

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Outline:

(01:18) The Famous METR Graph

(02:46) The System Card

(03:43) Basic Disallowed Content

(04:17) Sandbox

(05:34) Mitigations For Harmful Tasks and Prompt Injections

(06:13) Preparedness Framework

(06:35) Biological and Chemical

(07:50) Cybersecurity

(11:58) AI Self-Improvement

(14:27) Reactions

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First published:

November 25th, 2025


Source:

https://www.lesswrong.com/posts/YMFYQpsY2MGbXKPtS/chatgpt-5-1-codex-max

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Narrated by TYPE III AUDIO.

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Images from the article:

Table showing test results for different GPT models across nine cybersecurity attack scenarios.
Table showing production benchmarks for two GPT models across thirteen content safety categories.
Bar graph showing pass rates for professional CTFs across different GPT models.
Graph showing time-horizon of software engineering tasks different LLMs can complete over time by release date.
Table showing
Table showing vulnerability identification and exploitation capabilities evaluations with three assessment categories.
Graph showing AI coding task completion times with exponential and superexponential trendlines.
Bar graph showing CVEBench blind 0day performance across four GPT model versions.

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