o3 Mini High
OpenAI · released Feb 12, 2025
OpenAI o3-mini-high is the same model as [o3-mini](/openai/o3-mini) with reasoning_effort set to high. o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and...
Specification
- Context window
- 200K
- Max output
- 100K
- Knowledge cutoff
- Oct 31, 2023
- Parameters
- Undisclosed
- Licence
- Proprietary
- Serving providers
- 1
- Moderated
- Yes
Intelligence
15.7
51th percentile
Coding
16.3
Coding Index
Agentic
1.7
Agentic Index
Output speed
—
Median across providers
Latency
—
Time to first token
Cost per task
$0.41
Estimated
Benchmarks
Where the score comes from
The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.
Evaluation scores
Percentage correct · higher is better
- AIME 202586.0%
- MMLU-Pro80.2%
- GPQA Diamond77.3%
- LiveCodeBench73.4%
- IFBench67.1%
- AA-LCR (long context)42.0%
- SciCode39.8%
- τ²-bench (Telecom)31.3%
- Humanity's Last Exam12.0%
- Terminal-Bench Hard6.1%
An evaluation missing from this list was not run for this model — it is not a zero.
View as table
| Evaluation | Score |
|---|---|
| AIME 2025 | 86.0% |
| MMLU-Pro | 80.2% |
| GPQA Diamond | 77.3% |
| LiveCodeBench | 73.4% |
| IFBench | 67.1% |
| AA-LCR (long context) | 42.0% |
| SciCode | 39.8% |
| τ²-bench (Telecom) | 31.3% |
| Humanity's Last Exam | 12.0% |
| Terminal-Bench Hard | 6.1% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- GLM 4.5 AirZ.ai16.7
- o3 Mini HighOpenAI15.7
- gpt-oss-20bOpenAI15.2
- gpt-oss-20b (free)OpenAI15.2
- 15.0
- GPT-4.1 MiniOpenAI14.8
- Mistral Medium 3.1Mistral AI14.7
- Solar Pro 3Upstage14.5
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| GLM 4.5 Air | 16.7 |
| o3 Mini High | 15.7 |
| gpt-oss-20b | 15.2 |
| gpt-oss-20b (free) | 15.2 |
| Nemotron 3 Nano Omni (free) | 15.0 |
| GPT-4.1 Mini | 14.8 |
| Mistral Medium 3.1 | 14.7 |
| Solar Pro 3 | 14.5 |
Percentile among all indexed models
Pricing
What it costs to run
List prices per million tokens, plus what one representative task works out to.
List price
- Input / 1M tokens
- $1.1
- Output / 1M tokens
- $4.4
- Cached input / 1M
- $0.55
- Blended 3:1
- $1.93
One task, estimated
$0.41
- Input tokens
- 50,000
- Output tokens
- 80,000
- Profile
- Reasoning
Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).
Serving providers
Speed and latency figures are medians across these providers, so a widely-served model reports a blend rather than any single endpoint.