GPT-4.1 Turbo vs o3 Turbo: which model should you choose?
We compared GPT-4.1 Turbo and o3 Turbo on price, context window and 12 benchmarks. o3 Turbo has the stronger average benchmark score; GPT-4.1 Turbo is cheaper on a blended 3:1 basis.
GPT-4.1 Turbo
GPT-4.1 Turbo is a frontier model from OpenAI. It offers a 1,000,000-token context window, costs $16.12 per million input tokens and $69.91 per million output tokens, and averages 82.9 across the index's benchmark suite.
- Input
- $16.12 / 1M
- Output
- $69.91 / 1M
- Context
- 1,000,000
- Avg score
- 82.9
- Open weights
- No
o3 Turbo
o3 Turbo is a frontier model from OpenAI. It offers a 200,000-token context window, costs $16.63 per million input tokens and $83.71 per million output tokens, and averages 83.4 across the index's benchmark suite.
- Input
- $16.63 / 1M
- Output
- $83.71 / 1M
- Context
- 200,000
- Avg score
- 83.4
- Open weights
- No
Specification comparison
| Spec | GPT-4.1 Turbo | o3 Turbo | Edge |
|---|---|---|---|
| Input price / 1M | $16.12 | $16.63 | A |
| Output price / 1M | $69.91 | $83.71 | A |
| Context window | 1,000,000 | 200,000 | A |
| Max output | 128,000 | 4,096 | A |
| Average score | 82.9 | 83.4 | B |
| Arena Elo | 1446.2 | 1456.2 | B |
| Open weights | No | No | Tie |
Benchmark comparison
GPT-4.1 Turbo wins 4, o3 Turbo wins 8, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | GPT-4.1 Turbo | o3 Turbo | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 84.6 | 82.7 | 1.9 | GPT-4.1 Turbo |
| GPQA Diamond | 76.1 | 77.7 | 1.6 | o3 Turbo |
| SWE-bench Verified | 74.7 | 70.7 | 4.0 | GPT-4.1 Turbo |
| HumanEval | 89.8 | 87.4 | 2.4 | GPT-4.1 Turbo |
| MATH-500 | 86.9 | 90.6 | 3.7 | o3 Turbo |
| AIME 2025 | 77.4 | 83.0 | 5.6 | o3 Turbo |
| LiveCodeBench | 78.7 | 80.7 | 2.0 | o3 Turbo |
| IFEval | 88.2 | 89.1 | 0.9 | o3 Turbo |
| TruthfulQA | 87.0 | 83.6 | 3.4 | GPT-4.1 Turbo |
| HellaSwag | 90.0 | 91.8 | 1.8 | o3 Turbo |
| MMMU | 78.5 | 79.7 | 1.2 | o3 Turbo |
| Arena Elo | 1446.2 | 1456.2 | 10.0 | o3 Turbo |
Price analysis
On a blended 3:1 input-to-output basis, GPT-4.1 Turbo costs about $29.57 per million tokens and o3 Turbo costs about $33.40. GPT-4.1 Turbo is roughly 11% cheaper than o3 Turbo. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
GPT-4.1 Turbo has the larger context window at 1,000,000 tokens, compared with 200,000 for o3 Turbo. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, GPT-4.1 Turbo wins 4, o3 Turbo wins 8, and 0 are tied. On the index average, o3 Turbo leads GPT-4.1 Turbo by 0.5 points (83.4 versus 82.9).
The price picture favours GPT-4.1 Turbo. The context picture favours GPT-4.1 Turbo. Those two dimensions often matter more than a few benchmark points once a model is good enough for the task.
If you need a single default, start with o3 Turbo for quality-sensitive work and GPT-4.1 Turbo for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose GPT-4.1 Turbo if
- Unit cost matters and you want the cheaper blended price.
- You need the larger 1,000,000-token context window.
- You need the larger 128,000-token output limit.
Choose o3 Turbo if
- You want the higher average benchmark score in this index.
FAQ
Is GPT-4.1 Turbo better than o3 Turbo?
On the index average, o3 Turbo leads GPT-4.1 Turbo by 0.5 points (83.4 versus 82.9). The better choice depends on price, context and your task. GPT-4.1 Turbo wins 4 benchmarks, o3 Turbo wins 8.
Which is cheaper, GPT-4.1 Turbo or o3 Turbo?
GPT-4.1 Turbo is cheaper on a blended 3:1 basis at about $29.57 per million tokens, versus $33.40 for o3 Turbo.
Which has the larger context window?
GPT-4.1 Turbo has the larger context window at 1,000,000 tokens. o3 Turbo has 200,000 tokens.
Are these models open weights?
GPT-4.1 Turbo is proprietary; o3 Turbo is proprietary.
Which should I choose for production?
If you need a single default, start with o3 Turbo for quality-sensitive work and GPT-4.1 Turbo for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.