Claude Sonnet 4.5 vs o4: which model should you choose?
We compared Claude Sonnet 4.5 and o4 on price, context window and 12 benchmarks. Claude Sonnet 4.5 has the stronger average benchmark score; o4 is cheaper on a blended 3:1 basis.
Claude Sonnet 4.5
Claude Sonnet 4.5 is a frontier model from Anthropic. It offers a 400,000-token context window, costs $17.84 per million input tokens and $70.50 per million output tokens, and averages 86.0 across the index's benchmark suite.
- Input
- $17.84 / 1M
- Output
- $70.50 / 1M
- Context
- 400,000
- Avg score
- 86.0
- Open weights
- No
o4
o4 is a frontier model from OpenAI. It offers a 2,000,000-token context window, costs $17.74 per million input tokens and $66.00 per million output tokens, and averages 85.4 across the index's benchmark suite.
- Input
- $17.74 / 1M
- Output
- $66.00 / 1M
- Context
- 2,000,000
- Avg score
- 85.4
- Open weights
- No
Specification comparison
| Spec | Claude Sonnet 4.5 | o4 | Edge |
|---|---|---|---|
| Input price / 1M | $17.84 | $17.74 | B |
| Output price / 1M | $70.50 | $66.00 | B |
| Context window | 400,000 | 2,000,000 | B |
| Max output | 128,000 | 8,192 | A |
| Average score | 86.0 | 85.4 | A |
| Arena Elo | 1478.2 | 1469.4 | A |
| Open weights | No | No | Tie |
Benchmark comparison
Claude Sonnet 4.5 wins 8, o4 wins 3, and 1 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Claude Sonnet 4.5 | o4 | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 88.0 | 85.3 | 2.7 | Claude Sonnet 4.5 |
| GPQA Diamond | 82.6 | 82.3 | 0.3 | Claude Sonnet 4.5 |
| SWE-bench Verified | 74.2 | 74.8 | 0.6 | o4 |
| HumanEval | 92.7 | 89.6 | 3.1 | Claude Sonnet 4.5 |
| MATH-500 | 87.0 | 90.5 | 3.5 | o4 |
| AIME 2025 | 86.3 | 85.3 | 1.0 | Claude Sonnet 4.5 |
| LiveCodeBench | 82.5 | 81.4 | 1.1 | Claude Sonnet 4.5 |
| IFEval | 91.1 | 92.8 | 1.7 | o4 |
| TruthfulQA | 87.2 | 85.0 | 2.2 | Claude Sonnet 4.5 |
| HellaSwag | 93.0 | 91.0 | 2.0 | Claude Sonnet 4.5 |
| MMMU | 80.9 | 80.9 | 0.0 | Tie |
| Arena Elo | 1478.2 | 1469.4 | 8.8 | Claude Sonnet 4.5 |
Price analysis
On a blended 3:1 input-to-output basis, Claude Sonnet 4.5 costs about $31.00 per million tokens and o4 costs about $29.80. o4 is roughly 4% cheaper than Claude Sonnet 4.5. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
o4 has the larger context window at 2,000,000 tokens, compared with 400,000 for Claude Sonnet 4.5. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Claude Sonnet 4.5 wins 8, o4 wins 3, and 1 are tied. On the index average, Claude Sonnet 4.5 leads o4 by 0.6 points (86.0 versus 85.4).
The price picture favours o4. The context picture favours o4. 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 Claude Sonnet 4.5 for quality-sensitive work and o4 for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose Claude Sonnet 4.5 if
- You want the higher average benchmark score in this index.
- You need the larger 128,000-token output limit.
Choose o4 if
- Unit cost matters and you want the cheaper blended price.
- You need the larger 2,000,000-token context window.
FAQ
Is Claude Sonnet 4.5 better than o4?
On the index average, Claude Sonnet 4.5 leads o4 by 0.6 points (86.0 versus 85.4). The better choice depends on price, context and your task. Claude Sonnet 4.5 wins 8 benchmarks, o4 wins 3.
Which is cheaper, Claude Sonnet 4.5 or o4?
o4 is cheaper on a blended 3:1 basis at about $29.80 per million tokens, versus $31.00 for Claude Sonnet 4.5.
Which has the larger context window?
o4 has the larger context window at 2,000,000 tokens. Claude Sonnet 4.5 has 400,000 tokens.
Are these models open weights?
Claude Sonnet 4.5 is proprietary; o4 is proprietary.
Which should I choose for production?
If you need a single default, start with Claude Sonnet 4.5 for quality-sensitive work and o4 for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.