GPT-5 Codex
by OpenAI · openai/gpt-5-codex · #246 cheapest of 325 paid models
Prices updated Jul 22, 2026, 2:43 AM UTC · refreshed hourly
GPT-5-Codex is a specialized version of GPT-5 optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks....
Compare vs:Claude Sonnet 5Claude Opus 4.6Claude Haiku 4.5Gemini 3.6 Flash
Pricing
Input
$1.25
per 1M tokens
Output
$10.00
per 1M tokens
Blended (3:1)
$3.44
3 input : 1 output
Cache read
$0.125
per 1M cached tokens
Cache write
—
per 1M tokens
Cache & batch economics
Effective prices for GPT-5 Codex with prompt caching.
| Cache hit rate | Effective blended $/1M | Example request* | vs no cache |
|---|---|---|---|
| 0% | $3.44 | $0.1375 | — |
| 50% | $3.02 | $0.0813 | −41% |
| 90% | $2.68 | $0.0362 | −74% |
*Example: 100K sticky context + 2K new input + 1K output. Batch discount is an approximate 50% off list rates for this provider’s batch API. Confirm on the vendor’s pricing page.
What a request costs
| Workload | Input tokens | Output tokens | Cost / request | Cost / 1K requests |
|---|---|---|---|---|
| Short chat message | 500 | 300 | $0.003625 | $3.62 |
| Document summary | 8,000 | 1,000 | $0.02 | $20.00 |
| Codebase question (RAG) | 30,000 | 2,000 | $0.0575 | $57.50 |
| Long-context analysis | 150,000 | 5,000 | $0.2375 | $237.50 |
Performance
Intelligence Index
36.1
AA composite quality
Coding Index
—
Math Index
98.7
Agentic Index
—
Output speed
173 tok/s
median
Time to first token
8.91s
median
Time to first answer
8.91s
after reasoning tokens
Artificial Analysis benchmarks
| Benchmark | Score |
|---|---|
| MMLU-Pro | 86.5% |
| GPQA Diamond | 83.7% |
| Humanity's Last Exam | 25.6% |
| LiveCodeBench | 84.0% |
| SciCode | 40.9% |
| AIME 2025 | 98.7% |
| IFBench | 74.1% |
| AA-LCR (Long Context Reasoning) | 69.0% |
| Terminal-Bench Hard | 37.9% |
| τ²-Bench (Telecom) | 86.8% |
Design Arena Elo
| Category | Elo |
|---|---|
| Web apps | 1,138 |
| Mobile apps | 1,132 |
Specs
Context window
400K
tokens
Max output
128K
tokens
Input modalities
text, image
Tokenizer
GPT