OpenAI Codex

OpenAI's coding agent, now part of the ChatGPT desktop app and running on the GPT-6 models: GPT-6.1 Sol for complex coding and agent work, Luna for fast, high-volume tasks.

Included with ChatGPT plans: Free and Go get GPT-6 Luna; Plus ($20/month) gets GPT-6.1 Sol and Luna plus Codex on web, CLI, IDE extension and iOS; Pro is $100, $200 or $500/month (Ultrafast mode only on Pro $500 and eligible Enterprise/Edu); Business $20/user/month billed annually

My take

Codex is more or less on par with the latest Opus model in Claude Code, but it feels like it needs way more precise instructions, including what not to do, to yield the same results. Talking to Claude feels more natural, but depending on your tech stack, Codex might be the better, faster, and currently especially the cheaper choice.

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At a Glance

Pros

+ Excellent at writing, refactoring, and debugging production code
+ Deep training on real pull requests and code review patterns
+ Strong performance across many programming languages
+ Integrated into ChatGPT and API for flexible workflows
+ Currently cheaper than comparable Claude usage for heavy coding

Cons

− Requires more precise instructions than Claude Code for equivalent results
− Less natural conversational feel — needs explicit 'what not to do' guidance
− Pro plans are expensive for heavy use: $100 to $500 per month
− Less autonomous than Claude Code's agentic workflow

Best for: Developers who need a strong alternative to Claude Code, especially for tech stacks where OpenAI's models excel

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GPT-6 Astra multimodal GPT-6.1 Sol and GPT-6 Luna multimodal

Full review

Codex is OpenAI’s coding agent. It started as a code-tuned variant of GPT-5, trained further on code repositories and real pull requests, and has since become a product of its own: in July 2026 the Codex app merged into the new ChatGPT desktop app, next to Chat and Work.

What runs underneath

Codex now runs on the GPT-6 models. GPT-6 Sol and Luna arrived there on 22 September, and GPT-6.1 Sol (29 September) is now the recommended model for complex coding and agentic work. Luna is the most efficient, for focused, high-volume tasks. GPT-6 Astra remains the most capable, for the hardest problems, at five times Sol’s price. On 14 October GPT-5.5 was retired from Codex: paid plans moved to GPT-6.1 Sol, Free and Go to Luna. The code training shows in the output: Codex understands code conventions, testing patterns, CI/CD workflows, and the nuances of production codebases, and it writes code that looks like what an experienced developer would write, idiomatic for the language and framework rather than merely valid syntax.

Claude Code vs. Codex

Both are top-tier coding AI tools, but they feel different in practice. Claude Code is more conversational and agentic — you describe what you want and it figures out the details. Codex requires more explicit instruction: you need to specify not just what you want, but also what you don’t want. The tradeoff is that Codex can be faster and cheaper for well-defined tasks.

Use cases

Code generation: Write new features from specifications
Refactoring: Modernize and clean up existing codebases
Bug fixing: Debug issues with context-aware analysis
Code review: Get detailed feedback on pull requests
Tech stack specialization: Particularly strong in certain languages and frameworks

Who should use Codex

Developers who want a strong coding AI and either prefer the OpenAI ecosystem, need specific tech stack expertise where Codex excels, or want a cost-effective alternative to Claude Code for high-volume coding tasks.