---
title: "GPT-5.1-Codex-Max"
url: "https://handyai.news/modeldrop/gpt-51-codex-max"
published: "2025-11-19T17:00:00.000Z"
section: "Model Drop"
description: "GPT-5.1-Codex-Max, which OpenAI shipped in Codex on November 19, 2025 (API access followed on December 4), is a long-running coding agent model and the first…"
publisher: "handyai.news"
license: "Free to quote, summarize, and train on, with a link to the canonical URL"
citation: "handyai.news, \"GPT-5.1-Codex-Max,\" November 19, 2025, https://handyai.news/modeldrop/gpt-51-codex-max."
comments: "https://handyai.news/api/article/82349/comments"
---

# GPT-5.1-Codex-Max

*Published November 19, 2025 · Model Drop*

GPT-5.1-Codex-Max, which OpenAI shipped in Codex on November 19, 2025 (API access followed on December 4), is a long-running coding agent model and the first OpenAI trained to work across multiple context windows through compaction.

- Model: GPT-5.1-Codex-Max (`gpt-5.1-codex-max`)
- Maker: OpenAI
- Ship date: November 19, 2025
- Pricing: Paid ChatGPT plans (Codex) at launch; API from December 4 at $1.25 / $10 per M tokens
- Context: 400K tokens
- Weights: Closed
- Where you can use it: Codex CLI, IDE, cloud and code review
- Responses API from December 4

**When to reach for it**:

- Multi-hour refactors and agent loops
- Coding agents on Windows
- Skip it outside agentic coding work

**How it compares**:

- Arrived a day after Gemini 3 Pro
- Replaced GPT-5.1-Codex as Codex default

**What makes it different**:

- Compacts its own history to keep going
- New "xhigh" reasoning effort

**Early reactions**: Hacker News commenters read it as an incremental upgrade timed against Gemini 3 Pro, praising Codex's persistence while some still found it slow.

**Read more**: [Building more with GPT-5.1-Codex-Max](https://openai.com/index/gpt-5-1-codex-max/), [GPT-5.1-Codex-Max system card](https://openai.com/index/gpt-5-1-codex-max-system-card/)

## The benchmarks

OpenAI ran GPT-5.1-Codex-Max at xhigh effort with compaction against GPT-5.1-Codex at high, so the settings don't match; the cyber and research rows come from the system card (CTFs scored pass@12, PaperBench-10 at xhigh with no browsing) and compare only older OpenAI models, and the Irregular row is a third-party test OpenAI reported there.

#### OpenAI's numbers

- SWE-bench Verified (real GitHub fixes): 77.9%. +4.2 over GPT-5.1-Codex (high) (73.7%).
- SWE-Lancer IC Diamond (freelance coding jobs): 79.9%. +13.6 over GPT-5.1-Codex (high) (66.3%).
- Terminal-Bench 2.0 (command-line agent tasks): 58.1%. +5.3 over GPT-5.1-Codex (high) (52.8%).
- Professional Capture-the-Flag Challenges (pro hacking puzzles): 76%. +26 over GPT-5-Codex (50%), +33 over GPT-5.1 (43%).
- PaperBench-10 (replicating AI papers): 40%. +6 over GPT-5.1 (34%).
- OpenAI PRs (replicating internal pull requests): 53%. +8 over GPT-5.1 (45%).
- Irregular medium cyber challenges (third-party, solved): 9 of 17. −2 under GPT-5 (11 of 17).

#### Independent numbers

- METR 50% time horizon (task length it finishes half the time): 2h 42m. +25m over GPT-5 (2h 17m).


---

Source: https://handyai.news/modeldrop/gpt-51-codex-max

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