o3 Mini (batch)
by OpenAI · openai/o3-mini:batch · #232 cheapest of 422 paid models
Prices updated Sep 19, 2026, 6:21 PM 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
$0.55
per 1M tokens
Output
$2.20
per 1M tokens
Blended (3:1)
$0.963
3 input : 1 output
Cache read
$0.275
per 1M cached tokens
Cache write
—
per 1M tokens
Cache & batch economics
Effective prices for o3 Mini (batch) with prompt caching.
| Cache hit rate | Effective blended $/1M | Example request* | vs no cache |
|---|---|---|---|
| 0% | $0.963 | $0.0583 | — |
| 50% | $0.859 | $0.0446 | −24% |
| 90% | $0.777 | $0.0336 | −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 | $0.000935 | $0.935 |
| Document summary | 8,000 | 1,000 | $0.0066 | $6.60 |
| Codebase question (RAG) | 30,000 | 2,000 | $0.0209 | $20.90 |
| Long-context analysis | 150,000 | 5,000 | $0.0935 | $93.50 |
Performance
Intelligence Index
12.5
AA composite quality
Coding Index
—
Math Index
—
Agentic Index
—
Output speed
0 tok/s
median
Time to first token
0s
median
Time to first answer
0s
after reasoning tokens
Artificial Analysis benchmarks
| Benchmark | Score |
|---|---|
| MMLU-Pro | 79.1% |
| GPQA Diamond | 74.8% |
| Humanity's Last Exam | 7.9% |
| LiveCodeBench | 71.7% |
| 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