Claude Opus 4.5 Turbo vs o4 Turbo: which model should you choose?
We compared Claude Opus 4.5 Turbo and o4 Turbo on price, context window and 12 benchmarks. o4 Turbo has the stronger average benchmark score; o4 Turbo is cheaper on a blended 3:1 basis.
Claude Opus 4.5 Turbo
Claude Opus 4.5 Turbo is a frontier model from Anthropic. It offers a 2,000,000-token context window, costs $19.57 per million input tokens and $106.60 per million output tokens, and averages 85.7 across the index's benchmark suite.
- Input
- $19.57 / 1M
- Output
- $106.60 / 1M
- Context
- 2,000,000
- Avg score
- 85.7
- Open weights
- No
o4 Turbo
o4 Turbo is a frontier model from OpenAI. It offers a 2,000,000-token context window, costs $19.34 per million input tokens and $82.19 per million output tokens, and averages 86.6 across the index's benchmark suite.
- Input
- $19.34 / 1M
- Output
- $82.19 / 1M
- Context
- 2,000,000
- Avg score
- 86.6
- Open weights
- No
Specification comparison
| Spec | Claude Opus 4.5 Turbo | o4 Turbo | Edge |
|---|---|---|---|
| Input price / 1M | $19.57 | $19.34 | B |
| Output price / 1M | $106.60 | $82.19 | B |
| Context window | 2,000,000 | 2,000,000 | Tie |
| Max output | 65,536 | 8,192 | A |
| Average score | 85.7 | 86.6 | B |
| Arena Elo | 1469.3 | 1468.1 | A |
| Open weights | No | No | Tie |
Benchmark comparison
Claude Opus 4.5 Turbo wins 5, o4 Turbo wins 7, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Claude Opus 4.5 Turbo | o4 Turbo | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 85.8 | 88.1 | 2.3 | o4 Turbo |
| GPQA Diamond | 81.9 | 84.8 | 2.9 | o4 Turbo |
| SWE-bench Verified | 75.0 | 78.4 | 3.4 | o4 Turbo |
| HumanEval | 89.8 | 91.0 | 1.2 | o4 Turbo |
| MATH-500 | 93.2 | 91.7 | 1.5 | Claude Opus 4.5 Turbo |
| AIME 2025 | 87.2 | 85.9 | 1.3 | Claude Opus 4.5 Turbo |
| LiveCodeBench | 78.5 | 80.1 | 1.6 | o4 Turbo |
| IFEval | 92.2 | 92.6 | 0.4 | o4 Turbo |
| TruthfulQA | 85.5 | 88.8 | 3.3 | o4 Turbo |
| HellaSwag | 92.8 | 91.3 | 1.5 | Claude Opus 4.5 Turbo |
| MMMU | 80.5 | 79.6 | 0.9 | Claude Opus 4.5 Turbo |
| Arena Elo | 1469.3 | 1468.1 | 1.2 | Claude Opus 4.5 Turbo |
Price analysis
On a blended 3:1 input-to-output basis, Claude Opus 4.5 Turbo costs about $41.33 per million tokens and o4 Turbo costs about $35.05. o4 Turbo is roughly 15% cheaper than Claude Opus 4.5 Turbo. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Both models list a 2,000,000-token context window. That is enough for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Claude Opus 4.5 Turbo wins 5, o4 Turbo wins 7, and 0 are tied. On the index average, o4 Turbo leads Claude Opus 4.5 Turbo by 0.9 points (86.6 versus 85.7).
The price picture favours o4 Turbo. The context picture is effectively a tie. 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 o4 Turbo for quality-sensitive work, and check whether its price holds at your expected volume before committing.
Choose Claude Opus 4.5 Turbo if
- You need the larger 65,536-token output limit.
Choose o4 Turbo if
- You want the higher average benchmark score in this index.
- Unit cost matters and you want the cheaper blended price.
FAQ
Is Claude Opus 4.5 Turbo better than o4 Turbo?
On the index average, o4 Turbo leads Claude Opus 4.5 Turbo by 0.9 points (86.6 versus 85.7). The better choice depends on price, context and your task. Claude Opus 4.5 Turbo wins 5 benchmarks, o4 Turbo wins 7.
Which is cheaper, Claude Opus 4.5 Turbo or o4 Turbo?
o4 Turbo is cheaper on a blended 3:1 basis at about $35.05 per million tokens, versus $41.33 for Claude Opus 4.5 Turbo.
Which has the larger context window?
Both models list a 2,000,000-token context window.
Are these models open weights?
Claude Opus 4.5 Turbo is proprietary; o4 Turbo is proprietary.
Which should I choose for production?
If you need a single default, start with o4 Turbo for quality-sensitive work, and check whether its price holds at your expected volume before committing.