GPT-5.2-Codex
gpt-5.2-codexGPT-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.... Built by OpenAI.
Prices updated
Input price
$1.75
per 1M tokens · Standard
Output price
$14
per 1M tokens · Standard
Input limit
400K
tokens
Output limit
128K
tokens
Input formats
Output formats
GPT-5.2-Codex price history
2 price records since 9/25/2026
GPT-5.2-Codex cost calculator
$105/month
Standard pricing
Overview
What is GPT-5.2-Codex?
GPT-5.2-Codex is a text & reasoning and vision and code & slms model from OpenAI. 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.... Its 400K context window and $1.75 input price make it a candidate for quality-focused production applications.
Benchmarks
GPT-5.2-Codex benchmarks & speed
How GPT-5.2-Codex scores on standardized evaluations, and where it lands among every model we track.
28.5
Intelligence Index
Reasoning
GPQA Diamond
89.9%
Graduate-level scientific reasoning · top 27%
HLE
35.7%
Humanity's Last Exam · top 29%
Independent scores from Artificial Analysis and DesignArena · updated 10/5/2026. Higher is better; ranks compare against every model we track with that score.
Rates
GPT-5.2-Codex pricing
Pricing is based on token usage. Provider-specific caching, batch, regional, and tool charges may affect the final cost.
Input · Standard
$1.75
Per 1M tokens
Cached input · Standard
$0.17
Per 1M tokens
Capabilities
GPT-5.2-Codex Tools
Tools available when using GPT-5.2-Codex through supported provider APIs.
Function calling
Supported
Structured outputs
Supported
JSON mode
Supported
Reasoning
Supported
Built-in web search
Not supported
Log probabilities
Not supported
Deterministic seed
Supported
Parallel tool calls
Not supported
Prompt caching
Supported
Strengths and limitations
Strengths
- Measured results (AA Intelligence 28.5) position it for demanding production work.
- 400K context supports large documents, repositories and extended conversations.
- Supports text & reasoning and vision and code & slms workloads in one model.
Limitations
- Generated tokens cost 8× more than input tokens, which matters for verbose responses.
- Large context capacity does not guarantee consistent retrieval across the entire prompt.
- Arena Elo and MMLU-Pro are directional; test accuracy, latency and reliability on your own workload before committing.
Arena Elo, MMLU-Pro and pricing figures are illustrative; validate current vendor terms before purchase.
Same provider