San Francisco, November 19, 2025, OpenAI officially launched GPT‑5.1‑Codex‑Max, a cutting‑edge agent code model designed for long‑horizon engineering tasks. As an extension of the GPT‑5.1 series, Codex‑Max uses "compaction" technology to overcome context‑window limits and operate autonomously for more than 24 hours, marking a shift from short, quick assistants to an around‑the‑clock engineer. OpenAI's website announced that the model is available through the Codex environment to ChatGPT Plus, Pro, Business, Edu and Enterprise users and supports npm installation ($ npm i ‑g @openai/codex). Chief Product Officer Kevin Weil said: "Codex‑Max is not a simple upgrade but a revolution addressing developer pain points. It enables AI to independently handle complex projects spanning millions of tokens." The release follows Google Gemini 3 Pro, with OpenAI responding on efficiency and endurance, and is expected to reshape the software engineering ecosystem. VentureBeat reported that Codex‑Max scored 77.9% on the SWE‑bench Verified benchmark, ranking first and well ahead of Anthropic Claude 4.5 and Google Gemini 3.
The creation of GPT‑5.1‑Codex‑Max stems from OpenAI's long‑term iteration on coding AI. Since Codex 1.0 debuted in 2021, the series has evolved from a code‑completion tool into an agent system. GPT‑5, released on August 7, 2025, laid the groundwork, and GPT‑5.1 (November 13) introduced adaptive reasoning and instant modes to optimize daily tasks. Codex‑Max, a coding‑specialized variant of GPT‑5.1, focuses on "long‑horizon tasks" such as building full applications or debugging large codebases. OpenAI's blog emphasizes that this model is the first system "natively trained" to operate across multiple context windows by automatically compressing session history: as the window limit nears, it summarizes key information and discards irrelevant details to maintain continuity of core tasks. Internal tests show Codex‑Max has completed autonomous tasks longer than 24 hours, such as generating an end‑to‑end web application from requirements, including front‑end React components, back‑end Node.js services and database integration.
Technically, Codex‑Max centers on a dual breakthrough in "endurance and efficiency." OpenAI's model card reports a 77.9% score on SWE‑bench Verified, an 11.6‑point improvement over GPT‑5.1‑Codex and the top rank. This result is credited to the "compaction" technique: when processing millions of tokens, token utilization drops by 30% and inference speed improves by 27–42%. ZDNet reported that Codex‑Max is the first model trained with native Windows support, enabling local‑environment collaboration and reducing "thinking time"—complex logic no longer requires lengthy prefixes. Compared with its predecessor, it scores 54.2% on Terminal‑Bench 2.0 and 79.9% on SWE‑Lancer IC SWE, showing strengths in long‑horizon engineering tasks like multi‑module code review. Architecturally, it is based on GPT‑5.1's base reasoning model and trained on agent‑task datasets spanning software engineering, mathematics and research simulations. Neowin notes that Codex‑Max's multi‑window operation gives it a human‑like "memory persistence," from hours‑long debugging to all‑day project management without repeated context restatement.
Codex‑Max's application scenarios are broad, from individual developers to enterprise deployment. First, for "long‑horizon engineering," it can autonomously handle 24‑hour tasks such as generating a complete microservice architecture from UML diagrams, including API design, tests and deployment scripts. OpenAI's blog demo shows that in the Codex CLI, entering "build a flight‑tracking app" prompts the model to plan the end‑to‑end workflow: front‑end UI, back‑end services, database integration and code verification. Second, for "collaborative development," working with partners like Cursor, Cognition and Warp, Codex‑Max optimizes "coding personality" and supports interruptible interactions—AI can pause its "thinking" to await user feedback. At the enterprise level, automation pipelines at companies like Factory can use Codex‑Max to generate CI/CD pipelines, cutting manual coding by 40%. The Decoder reported the model performs well in internal code‑review tools, identifying vulnerabilities and optimization opportunities. Pricing is approachable: Plus/Pro/Business/Edu/Enterprise users have free access via the Codex environment, and API pricing is the same as GPT‑5.1 ($0.0035 per 1K input tokens).
The release has far‑reaching implications. Codex‑Max marks OpenAI's strategic shift from general‑purpose models toward specialized agent models, challenging Google Gemini 3's agent coding capabilities. VentureBeat analyzes that it could reshape software engineering: developers may move from "code workers" to "AI directors," potentially boosting productivity two‑ to threefold. Compared with ChatGPT‑5.1‑codex (SWE‑bench 66.3%), Codex‑Max's 77.9% score leads by 18 percentage points, particularly on long tasks. The model's "compaction" mechanism addresses the "memory wall," supporting projects at the million‑token scale. OpenAI stresses that while its security capabilities (such as vulnerability detection) are strong, they do not yet meet a "high capability" threshold, and built‑in sandboxes and monitoring are in place.
User reaction has been enthusiastic. Since going live on November 19, Reddit's r/OpenAI saw hundreds of posts: "Codex‑Max is amazing—24‑hour tasks no longer need restarting!" ZDNet user tests show complex‑logic response times reduced by 42%, though a few users complained about loss of detail after compaction. On X, the #GPT5CodexMax tag showed about 80% excitement, with developers like @codewhisperer posting "From GPT‑4.5 to this, OpenAI won again." Criticisms focus on cost: long‑task token fees may rise by about 20%. Startup feedback is positive: Cursor's founder said integration improved code quality by 30%.
The release underscores the leap from code completion to autonomous engineering and challenges GitHub Copilot's dominance (Copilot already integrates GPT‑5.1‑Codex). Neowin projects the agent‑coding market could reach $100 billion by 2026, with OpenAI's market share exceeding 50%. Compared with Google Gemini 3's Antigravity platform, Codex‑Max emphasizes "endurance" and supports Windows‑native collaboration. Enterprises such as Warp can use it to generate CI/CD pipelines and cut manual work by 40%. The Decoder reported improved vulnerability detection in internal code review, and built‑in sandboxes mitigate prompt‑injection risks. Pricing remains aligned with GPT‑5.1 ($0.0035 per 1K input tokens), with Plus/Pro and similar plans offering free access.