o3 Mini
by OpenAI · openai/o3-mini · #224 cheapest of 325 paid models
Prices updated Jul 22, 2026, 2:47 AM UTC · refreshed hourly
OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. This model supports the `reasoning_effort` parameter, which can be set to...
Compare vs:Claude Sonnet 5Claude Opus 4.6Claude Haiku 4.5Gemini 3.6 Flash
Pricing
Input
$1.10
per 1M tokens
Output
$4.40
per 1M tokens
Blended (3:1)
$1.93
3 input : 1 output
Cache read
$0.55
per 1M cached tokens
Cache write
—
per 1M tokens
Cache & batch economics
Effective prices for o3 Mini with prompt caching.
| Cache hit rate | Effective blended $/1M | Example request* | vs no cache |
|---|---|---|---|
| 0% | $1.93 | $0.1166 | — |
| 50% | $1.72 | $0.0891 | −24% |
| 90% | $1.55 | $0.0671 | −42% |
*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 | $0.00187 | $1.87 |
| Document summary | 8,000 | 1,000 | $0.0132 | $13.20 |
| Codebase question (RAG) | 30,000 | 2,000 | $0.0418 | $41.80 |
| Long-context analysis | 150,000 | 5,000 | $0.187 | $187.00 |
Performance
Intelligence Index
19
AA composite quality
Coding Index
—
Math Index
—
Agentic Index
—
Output speed
228 tok/s
median
Time to first token
5.94s
median
Time to first answer
5.94s
after reasoning tokens
Artificial Analysis benchmarks
| Benchmark | Score |
|---|---|
| MMLU-Pro | 79.1% |
| GPQA Diamond | 74.8% |
| Humanity's Last Exam | 8.7% |
| LiveCodeBench | 71.7% |
| SciCode | 39.9% |
| MATH-500 | 97.3% |
| AIME | 77.0% |
| Terminal-Bench Hard | 6.8% |
| τ²-Bench (Telecom) | 28.7% |
Specs
Context window
200K
tokens
Max output
100K
tokens
Input modalities
text, file
Tokenizer
GPT