Model detail
gpt-5.2-codex
GPT-5.2-Codex is an upgraded version of GPT-5.1-Codex optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks. The model supports building projects from scratch, feature development, debugging, large-scale refactoring, and code review. Compared to GPT-5.1-Codex, 5.2-Codex is more steerable, adheres closely to developer instructions, and produces cleaner, higher-quality code outputs. Reasoning effort can be adjusted with the `reasoning.effort` parameter. Read the [docs here](https://openrouter.ai/docs/use-cases/reasoning-tokens#reasoning-effort-level) Codex integrates into developer environments including the CLI, IDE extensions, GitHub, and cloud tasks. It adapts reasoning effort dynamically—providing fast responses for small tasks while sustaining extended multi-hour runs for large projects. The model is trained to perform structured code reviews, catching critical flaws by reasoning over dependencies and validating behavior against tests. It also supports multimodal inputs such as images or screenshots for UI development and integrates tool use for search, dependency installation, and environment setup. Codex is intended specifically for agentic coding applications.
Model specs
- Context length
- 400K
- Max output
- 128K
- I/O modalities
- Text / Image
- Released
- 2026-01
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API endpoints
One MixRoute gateway, OpenAI-compatible
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OpenAI-compatible
/v1/chat/completionsPOST
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Pricing
Flat rate, unit: /1M Tokens
Input
$1.7500 /1M Tokens
Completion
$14.0000 /1M Tokens
Cache read
$0.1750 /1M Tokens
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Selection summary
Quickly judge whether it fits your workload
What is this model good for?
Interactive and independent software engineering tasks
Use gpt-5.2-codex for project creation, feature work, debugging, refactoring, code review, and longer engineering runs.
What should you check before using it?
Set reasoning effort and validate the delivery loop
Choose an appropriate reasoning setting, then test code changes, dependency handling, tests, and review requirements on your own repository.
How should you start?
Start with a reviewable engineering task
Use model ID gpt-5.2-codex for a scoped task with version control and tests so the team can assess output before wider use.
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Token cost estimator
Live estimate from this page's pricing, not an actual bill
Share of the same prefix read repeatedly, up to 100%
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FAQ
gpt-5.2-codex is intended for interactive and independent software engineering, including project creation, feature work, debugging, refactoring, and code review.
One endpoint, a testable decision
Test this model and alternate routes with the same request format
Start from a real workload, then let quality, total cost, and failure conditions decide whether to send production traffic.