o1-mini
CurrentA smaller, faster o1-class model for STEM-style reasoning where full o1 latency or cost is prohibitive.
Reasoning LLM · Release — · See vendor
Updated 1 day ago · Verified Apr 2026 · Score 78
Decision summary
Why teams reach for it, where it fits, and what to watch for — before you dive into specs.
Why teams choose it
- Good middle tier in routing: escalate failures to o1 or GPT-4o.
- Validate on your own math/code suite—aggregate benchmarks are only directional.
Best use cases
- Use this when sTEM tutoring with budget limits
- Use this when automated grading assistance
Tradeoffs
- Can still be slower than non-reasoning chat models.
- May underperform o1 on hardest tasks—keep escalation paths.
Technical details
Modalities, benchmarks, and release context.
Modalities
What goes in and what comes out.
- Inputs
- text
- Outputs
- text
- Capabilities
- reasoning, math
Benchmarks snapshot
Structured JSON for reproducible comparisons.
No benchmark data yet — see comparisons for relative performance.
Continue exploring
A short set of comparisons, nearby models, and links to go deeper — without repeating the same paths.
Compare with
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Catalog entry for this named release; see the provider’s official documentation for modalities, pricing, and context limits.
Learn & build
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