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OpenAIReasoning ModelProprietaryOpenAI's advanced reasoning model using chain-of-thought to solve complex problems in math, science, and coding.
Abilities
Use Cases
Available in Tools
Availability
How to Use
Pros
- State-of-the-art reasoning — scored 96.7% on ARC-AGI benchmark, far exceeding other models
- Excels at mathematical proofs, scientific analysis, and multi-step logical deduction
- Top-tier competitive programming performance (Codeforces, IOI-level problems)
- Transparent chain-of-thought — you can see the reasoning steps in the output
- Handles ambiguous or under-specified problems better than non-reasoning models
Cons
- Significantly slower — responses can take 30s-2min due to internal reasoning steps
- 4-10x more expensive per query than GPT-4o due to reasoning token usage
- Overkill and wasteful for simple Q&A, summarization, or creative writing tasks
- Closed source — reasoning traces are shown but internals are opaque
- Limited availability — requires ChatGPT Pro ($200/mo) for web access
- Cannot browse the web or use tools during reasoning
What to Use It For
Perfect For
Chain-of-thought reasoning enables multi-step proofs and calculations other models cannot handle
Top-tier Codeforces and IOI-level performance thanks to deep logical reasoning
Can decompose complex scientific problems into verifiable reasoning chains
Good For
Reasoning steps help trace through complex bug chains that standard models miss
Can reason about time complexity, correctness proofs, and edge cases methodically
Not Recommended
Massive overkill at 10x the cost — reasoning overhead adds latency for no benefit
Try instead: GPT-4o, Claude Sonnet 4
Reasoning model optimized for logic, not prose style or narrative creativity
Try instead: Claude Opus 4
Do Not Use For
Responses take 30s-2min due to internal reasoning — completely unusable for interactive UIs
Try instead: GPT-4o
Extremely expensive per query — cost scales linearly and becomes prohibitive at volume
Try instead: DeepSeek V3