GPT-5.5 available in Codex with browser use and automatic approval reviews
OpenAI has made GPT-5.5 the recommended frontier model in its Codex product (CLI, IDE extension, and app), positioning it as the default for coding, debugging, refactoring, and knowledge-work tasks. The Codex app also gains two new capabilities: browser use allowing Codex to operate an in-app browser for local development servers and visual bug reproduction, and an automatic approval review agent that pre-screens eligible approval prompts with risk-level assessments. Users on older versions must update to access GPT-5.5, with GPT-5.4 as the fallback during rollout.
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OpenAI releases GPT-5.4 in Codex with native computer-use and 1M context window
OpenAI has made GPT-5.4 available across all Codex surfaces — the app, CLI, IDE extension, and Codex Cloud — positioning it as the recommended model for most Codex tasks. GPT-5.4 is the first general-purpose model in Codex with native computer-use capabilities and experimental support for a 1M token context window. The release also includes stronger tool use and tool search for agentic workflows, and the model is available via API.
OpenAI releases GPT-5.3-Codex, upgraded agentic coding model with faster inference and real-time steering
OpenAI released GPT-5.3-Codex, an incremental upgrade to GPT-5.2-Codex targeting complex software engineering tasks. The new model runs 25% faster, improves reasoning and professional knowledge, and adds better real-time collaboration features including progress updates and in-session steering. It is available immediately across ChatGPT paid plans via the Codex app, CLI, IDE extension, and Codex Cloud, with API access forthcoming.
OpenAI introduces GPT-5.4 mini in Codex for fast, efficient coding tasks
OpenAI has made GPT-5.4 mini available in Codex across the CLI, IDE extension, app, and API, positioning it as a faster and cheaper alternative to GPT-5.4 for lighter coding and subagent work. The model runs more than 2x faster than GPT-5.4 and consumes only 30% of the usage limits, allowing roughly 3.3x more work within the same quota. It improves over GPT-5 mini on coding, reasoning, image understanding, and tool use. Recommended use cases include codebase exploration, large-file review, and document processing, while GPT-5.4 remains preferred for complex planning and final judgment.
Introducing GPT-5.3-Codex
OpenAI has announced GPT-5.3-Codex, described as a Codex-native agent combining frontier coding performance with general reasoning capabilities. The model is designed to support long-horizon, real-world technical work. The announcement positions it as an agentic coding system rather than a standalone language model.
GPT 5.4 is a big step for Codex
A Tier 2 commentary piece from Interconnects evaluates GPT 5.4 in the context of OpenAI's Codex agent ecosystem, examining what the model release means for the frontier of AI agents. The author reflects on the current state of agent evaluation and notes a continued preference for Claude in practice. The piece offers analysis of how GPT 5.4 advances coding-agent capabilities relative to competing offerings.
Introducing GPT-5.2-Codex
OpenAI has released GPT-5.2-Codex, described as their most advanced coding model. The model features long-horizon reasoning, large-scale code transformation capabilities, and enhanced cybersecurity features. This represents a specialized coding-focused model in the GPT-5 family.
GPT-5.3-Codex System Card
OpenAI has released the system card for GPT-5.3-Codex, described as the most capable agentic coding model to date. It combines the frontier coding performance of GPT-5.2-Codex with the reasoning and professional knowledge capabilities of GPT-5.2. The release represents a continuation of OpenAI's Codex line of specialized coding models within the GPT-5 family.
OpenAI releases GPT-5-Codex: GPT-5 variant optimized for agentic coding
OpenAI has published an addendum to the GPT-5 system card introducing GPT-5-Codex, a version of GPT-5 specifically optimized for agentic coding within the Codex environment. The model features dynamic thinking-effort adjustment, scaling compute based on task complexity—responding quickly to simple queries while sustaining longer independent work on complex coding tasks. This represents a specialized derivative of GPT-5 targeting software engineering agents rather than general-purpose use.