o1
CurrentOpenAI’s o1 series emphasizes extended internal reasoning before answering—useful for competition-style math, complex debugging, and multi-step planning where latency is acceptable.
Reasoning LLM · Release — · See vendor
Featured · Updated 1 day ago · Verified Apr 2026 · Score 86
Decision summary
Why teams reach for it, where it fits, and what to watch for — before you dive into specs.
Why teams choose it
- Not a drop-in replacement for all chat—latency and pricing profiles differ sharply.
- Use structured evals; reasoning models can overthink simple tasks.
Best use cases
- Use this when hard math and code contest–style problems
- Use this when architecture planning with explicit intermediate steps
Tradeoffs
- Higher cost per successful answer on easy prompts if mis-routed.
- API capabilities evolve—check tool-use support on your snapshot.
Technical details
Modalities, benchmarks, and release context.
Modalities
What goes in and what comes out.
- Inputs
- text
- Outputs
- text
- Capabilities
- reasoning, math, coding
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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