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模型詳情

gpt-5.2-codex

由 OpenAI 提供
隨用隨付

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.

模型規格

上下文長度
400K
最大輸出
128K
輸入/輸出模態
文字 / 圖片
發布日期
2026-01

02

API 端點

單一 MixRoute 閘道,OpenAI 相容

  • OpenAI-compatible /v1/chat/completions POST

03

價格

固定費率,單位:/1M Tokens

輸入

$1.7500 /1M Tokens

補全

$14.0000 /1M Tokens

快取讀取

$0.1750 /1M Tokens

05

選型摘要

快速判斷是否適合你的工作負載

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.

08

Token 成本估算

基於本頁價格的即時估算,非實際帳單

同一前綴被重複讀取的輸入占比,最高 100%

單一端點,可驗證的決策

使用相同的請求格式測試此模型與替代路由

從真實工作負載開始,再由品質、總成本與故障條件決定是否導入正式環境流量。