o1
OpenAI’s o1 series emphasizes extended internal reasoning before answering—useful for competition-style math, complex debugging, and multi-step planning where latency is acceptable.
Provider
OpenAI
Model family
OpenAI o-series
Reasoning LLM
Cost tier
Full
Status
Legacy
Why teams choose it
Broad capability envelope
Useful when the same stack must cover chat, multimodal inputs, tooling, or structured-output shapes without juggling many SKUs.
Long-context analysis
Helps teams summarize, compare, and extract insights from long documents without losing important nuance.
Coding and tools
Works well for code assistance, tool calling, and agent workflows where instructions must stay consistent across steps.
Cost-efficient routing
Useful as part of a routing stack where cheap models handle drafts and confirmations and this tier handles genuinely hard passages.
Tradeoffs to know
- Higher cost per successful answer on easy prompts if mis-routed.
- API capabilities evolve—check tool-use support on your snapshot.
When not to use this
- Not ideal for simple tasks where cheaper models in the same lineup are good enough.
- Avoid for latency-sensitive real-time chat when raw response speed outweighs reasoning depth.
- Confirm limits, pricing, and regional availability on the provider side before committing production workloads.
Technical specs
- Inputs
- text
- Outputs
- text
- Capabilities
- reasoning, math, coding
- License
- See vendor
- Model string
o1
Benchmarks
No benchmark data yet.
OpenAI o-series family lineup
Current models
Previous versions
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