What are the strengths of this model?

Advanced coding capabilities Large 400K context window Optimized by OpenAI

What are the weaknesses of this model?

Restricted by non-open-source license Limited external access Closed usage conditions

What are the best use cases?

Analyzing large codebases Implementing complex programs Advanced bug fixing

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OpenAIProprietary

OpenAI GPT-5.1-Codex-Max

Name: OpenAI GPT-5.1-Codex-Max
Author: OpenAI

OpenAI GPT-5.1-Codex-Max is a programming-specialized foundation model developed by OpenAI. It features a very long context window of 400K, making it suitable for processing large codebases.

Parameters

Undisclosed

Context Window

400K

License

Proprietary

Release Date

2025-11-19

API Pricing

API pricing for this model is not yet available

Strengths

・Advanced coding capabilities
・Large 400K context window
・Optimized by OpenAI

Weaknesses

・Restricted by non-open-source license
・Limited external access
・Closed usage conditions

Use Cases

・Analyzing large codebases
・Implementing complex programs
・Advanced bug fixing

Deep Analysis

Release Date

November 19, 2025

Context Window

Effectively unlimited (compaction)

Input Price

$1.25 / 1M tokens

Output Price

$10.00 / 1M tokens

Cached Input

$0.625 / 1M tokens

SWE-bench Verified

77.9% (xhigh)

Terminal-Bench 2.0

58.1%

SWE-Lancer IC SWE

79.9%

Autonomous Operation

24+ hours continuous

Throughput

58.4 tok/s avg (11-110 range)

Strengths

・First model with context compaction — effectively unlimited context through iterative summarization
・SWE-bench Verified 77.9% with 30% fewer thinking tokens than predecessor
・Autonomous operation for 24+ hours on complex tasks
・Native Windows support — first OpenAI coding model to offer this
・Configurable reasoning effort (none/medium/high/xhigh) for cost/quality tradeoffs

Weaknesses

・High latency (2,060ms avg TTFT) with significant variability (169.3% CV)
・Context compaction can 'blur' details over very long sessions
・METR evaluation suggests 80% reliability time-horizon is ~2 hours, not 24
・Follows instructions very literally — may not recognize obvious typos
・Higher code churn compared to Claude Code (30% more reworks)

Competitor Comparison

Model	Arena	SWE	GPQA	Price
Claude Opus 4.5	~1450	80.9%	~92%	$15/$75 per 1M tokens
Gemini 3 Pro	~1420	76.2%	~90%	$3.50/$10.50 per 1M tokens
GPT-5.1 Codex	~1400	73.7%	~88%	$1.25/$10 per 1M tokens
Cursor (varies)	N/A	Varies	N/A	$20/month subscription

Overview

GPT-5.1-Codex-Max is OpenAI's frontier agentic coding model released November 19, 2025, featuring revolutionary context compaction technology for effectively unlimited context. It achieves SWE-bench Verified 77.9% with 30% fewer thinking tokens than its predecessor and can operate autonomously for over 24 hours. It replaced GPT-5.1-Codex as the default across all Codex surfaces.

Benchmarks & Performance

GPT-5.1-Codex-Max achieves SWE-bench Verified 77.9% at xhigh reasoning (76.5% at high), SWE-Lancer IC SWE 79.9%, and Terminal-Bench 2.0 58.1%. It uses 30% fewer thinking tokens than GPT-5.1-Codex while achieving better results. The context compaction system reduces overall tokens by 20-40% in long sessions. Average throughput is 58.4 tok/s with high variability (11-110 range). Claude Opus 4.5 leads on SWE-bench at 80.9%.

Detailed Comparison

GPT-5.1-Codex-Max trails Claude Opus 4.5 on SWE-bench (77.9% vs 80.9%) but offers effectively unlimited context through compaction vs Claude's 200K. It beats Gemini 3 Pro (76.2%) on SWE-bench. The model has higher code churn than Claude Code but offers native Windows support and 24+ hour autonomous operation. At $1.25/$10 per 1M tokens, it is significantly cheaper than Claude Opus ($15/$75) while being competitive on benchmarks.

Community Feedback

Developers report it as a 'significant advancement' over GPT-5.1-Codex, with one developer successfully creating a 64-bit SMP OS with 100K+ lines of code. 95% of OpenAI engineers reportedly use Codex weekly, shipping ~70% more PRs. The main criticisms are high latency, literal instruction following, and context compaction causing detail loss over time. The model is preferred for large autonomous coding tasks but Claude is preferred for interactive development.

Use Cases

Best for: autonomous code generation and refactoring over extended periods, large-scale project scaffolding, multi-file architecture changes, continuous integration and testing pipelines, Windows-native development, and complex debugging sessions. The configurable reasoning effort makes it flexible: use 'medium' for everyday tasks, 'xhigh' for hardest problems (race conditions, legacy systems). NOT ideal for: quick completions (overkill), sub-5-minute tasks, interactive pair programming, or security-critical code where Claude's lower churn is preferred.

Latest News

Released November 19, 2025. The METR evaluation report and System Card were published. GPT-5.2-Codex and GPT-5.3-Codex have since been released as newer coding models. The model remains available via the Responses API and Codex CLI.

Sources

Analysis generated: 2026-05-24