GPT-o1 & o3 Review: OpenAI's Reasoning Models
GPT-o3 is the most capable reasoning model available. It scores 96.2% on HumanEval (coding) and 78.1% on GPQA (PhD-level science), approaching expert-level performance on the hardest benchmarks. The tradeoff: it’s slower and more expensive than GPT-4o because it “thinks” before answering.
How Reasoning Models Work
o1 and o3 use chain-of-thought reasoning. Instead of answering immediately, they generate internal “thinking” steps — breaking problems into sub-tasks, checking their work, and considering alternatives. You can see this as a “thinking” indicator in ChatGPT.
This approach excels on problems that benefit from deliberation: math competitions, complex code architecture, scientific reasoning, and multi-step logic puzzles. It’s overkill for simple questions.
o1 vs o3
| Feature | o1 | o3 | o3-mini |
|---|---|---|---|
| Input $/M | $15.00 | $10.00 | $1.10 |
| Output $/M | $60.00 | $40.00 | $4.40 |
| HumanEval | 92.4% | 96.2% | 87.1% |
| GPQA | 73.3% | 78.1% | 60.2% |
| Speed | Slow | Slow | Fast |
| Best for | Complex reasoning | Best reasoning | Budget reasoning |
o3 supersedes o1 with better performance at lower prices. o3-mini is the budget option — fast and cheap, good enough for most reasoning tasks.
When to Use o3
Use o3 when the problem is genuinely hard. In our testing, o3 solved math competition problems that GPT-4o couldn’t. It debugged complex race conditions that GPT-4o missed. It produced more thorough architectural plans for software systems.
But for 80% of tasks, GPT-4o is faster, cheaper, and equally good. Don’t use a reasoning model to draft an email.
Frequently Asked Questions
What's the difference between GPT-4o and o3? ▼
GPT-4o is a fast, multimodal model optimized for general tasks. o3 is a reasoning model that 'thinks' before answering — it takes longer but produces significantly better results on math, coding, and science problems. Use GPT-4o for everyday tasks, o3 for hard problems.
Why is o3 more expensive than GPT-4o? ▼
o3 uses chain-of-thought reasoning, which generates many internal 'thinking' tokens before producing an answer. You pay for these reasoning tokens. A single o3 response may consume 10-50x more tokens than GPT-4o for the same question.
When should I use o3 instead of GPT-4o? ▼
Use o3 for problems requiring multi-step reasoning: math proofs, complex coding, scientific analysis, logic puzzles, and planning tasks. For conversation, writing, image analysis, and everyday questions, GPT-4o is faster, cheaper, and equally good.