OpenAI o1

OpenAI's reasoning-focused model built for complex, multi-step problem solving.

4.8 (4)

审阅者 Daniel Nikulshyn·更新 2026年5月

Reasoning Research STEM Enterprise LLM API Coding

概览

OpenAI o1 is a large language model designed to think through problems step by step before responding. Unlike standard chat models that prioritize quick replies, o1 spends additional compute on internal reasoning, making it better suited for tasks like advanced math, scientific analysis, competitive coding, and intricate logical puzzles. The model is available through ChatGPT and the OpenAI API, where developers and researchers can use it for workflows that demand deeper deliberation. It typically outperforms earlier GPT models on reasoning-heavy benchmarks, though it trades off some response speed and cost in exchange for that depth. O1 is best used as a specialist tool for hard problems rather than a general everyday assistant, complementing faster models in a broader AI stack.

主要功能

Chain-of-thought style internal reasoning
Advanced math and coding problem solving
API access for developer integration
Available in ChatGPT for Plus and Pro users
Improved benchmark scores on STEM tasks
Suited for complex, multi-step prompts

使用场景

Solve Advanced Math Problems

Work through complex mathematical proofs, equations, and quantitative problems that require multi-step deliberation rather than quick pattern matching.

Competitive Coding Assistance

Tackle intricate algorithmic challenges and debugging tasks where chain-of-thought reasoning helps produce more reliable solutions than standard chat models.

Scientific Analysis and Research

Support researchers in reasoning through STEM problems, hypothesis evaluation, and technical workflows that benefit from deeper deliberation.

Logical Puzzle and Decision Workflows

Integrate via the OpenAI API into developer workflows that require multi-step logical reasoning, such as planning, structured analysis, or complex prompt chains.

优点 & 缺点

优点

Strong performance on math, science, and coding tasks
Handles multi-step reasoning more reliably than prior models
Available in both ChatGPT and the API
Useful for research and technical workflows

缺点

Slower responses than standard chat models
Higher token cost per query
Overkill for simple or conversational tasks
Limited tool and multimodal support compared to GPT-4o

评测

4.8

4 个评分的平均值。

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Margaret Whitfield

Years in this space

I've evaluated a lot of these over the years. What stands out here is advanced math and coding problem solving — handled better than most — and useful for research and technical workflows. Worth the time if this is your use case.

Pierre Dubois

Use it every day

Honestly didn't expect to like it this much. API access for developer integration is exactly what I needed, and useful for research and technical workflows. but I reach for it almost every day now and it just clicks.

Wei Chen

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on suited for complex, multi-step prompts, and available in both ChatGPT and the API caught me off guard. Overkill for simple or conversational tasks is why this isn't a perfect score, still, I'd recommend giving it a real trial.

Victor Nguyen

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on aPI access for developer integration, and strong performance on math, science, and coding tasks caught me off guard. still, I'd recommend giving it a real trial.

问答

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