Claude Haiku 4.5 vs Nova Pro Max: which model should you choose?
We compared Claude Haiku 4.5 and Nova Pro Max on price, context window and 12 benchmarks. Nova Pro Max has the stronger average benchmark score; Nova Pro Max is cheaper on a blended 3:1 basis.
Claude Haiku 4.5
Claude Haiku 4.5 is a multimodal model from Anthropic. It offers a 1,000,000-token context window, costs $13.86 per million input tokens and $74.67 per million output tokens, and averages 79.4 across the index's benchmark suite.
- Input
- $13.86 / 1M
- Output
- $74.67 / 1M
- Context
- 1,000,000
- Avg score
- 79.4
- Open weights
- No
Nova Pro Max
Nova Pro Max is a multimodal model from Amazon. It offers a 1,000,000-token context window, costs $14.05 per million input tokens and $71.59 per million output tokens, and averages 81.2 across the index's benchmark suite.
- Input
- $14.05 / 1M
- Output
- $71.59 / 1M
- Context
- 1,000,000
- Avg score
- 81.2
- Open weights
- No
Specification comparison
| Spec | Claude Haiku 4.5 | Nova Pro Max | Edge |
|---|---|---|---|
| Input price / 1M | $13.86 | $14.05 | A |
| Output price / 1M | $74.67 | $71.59 | B |
| Context window | 1,000,000 | 1,000,000 | Tie |
| Max output | 128,000 | 16,384 | A |
| Average score | 79.4 | 81.2 | B |
| Arena Elo | 1421.8 | 1423.2 | B |
| Open weights | No | No | Tie |
Benchmark comparison
Claude Haiku 4.5 wins 3, Nova Pro Max wins 9, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Claude Haiku 4.5 | Nova Pro Max | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 84.1 | 84.2 | 0.1 | Nova Pro Max |
| GPQA Diamond | 74.1 | 78.3 | 4.2 | Nova Pro Max |
| SWE-bench Verified | 69.2 | 67.4 | 1.8 | Claude Haiku 4.5 |
| HumanEval | 84.7 | 87.5 | 2.8 | Nova Pro Max |
| MATH-500 | 81.4 | 83.8 | 2.4 | Nova Pro Max |
| AIME 2025 | 76.5 | 79.3 | 2.8 | Nova Pro Max |
| LiveCodeBench | 71.6 | 77.0 | 5.4 | Nova Pro Max |
| IFEval | 85.2 | 86.4 | 1.2 | Nova Pro Max |
| TruthfulQA | 79.6 | 83.4 | 3.8 | Nova Pro Max |
| HellaSwag | 89.6 | 88.9 | 0.7 | Claude Haiku 4.5 |
| MMMU | 77.6 | 77.2 | 0.4 | Claude Haiku 4.5 |
| Arena Elo | 1421.8 | 1423.2 | 1.4 | Nova Pro Max |
Price analysis
On a blended 3:1 input-to-output basis, Claude Haiku 4.5 costs about $29.06 per million tokens and Nova Pro Max costs about $28.44. Nova Pro Max is roughly 2% cheaper than Claude Haiku 4.5. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Both models list a 1,000,000-token context window. That is enough for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Claude Haiku 4.5 wins 3, Nova Pro Max wins 9, and 0 are tied. On the index average, Nova Pro Max leads Claude Haiku 4.5 by 1.8 points (81.2 versus 79.4).
The price picture favours Nova Pro Max. 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 Nova Pro Max for quality-sensitive work, and check whether its price holds at your expected volume before committing.
Choose Claude Haiku 4.5 if
- You need the larger 128,000-token output limit.
Choose Nova Pro Max if
- You want the higher average benchmark score in this index.
- Unit cost matters and you want the cheaper blended price.
FAQ
Is Claude Haiku 4.5 better than Nova Pro Max?
On the index average, Nova Pro Max leads Claude Haiku 4.5 by 1.8 points (81.2 versus 79.4). The better choice depends on price, context and your task. Claude Haiku 4.5 wins 3 benchmarks, Nova Pro Max wins 9.
Which is cheaper, Claude Haiku 4.5 or Nova Pro Max?
Nova Pro Max is cheaper on a blended 3:1 basis at about $28.44 per million tokens, versus $29.06 for Claude Haiku 4.5.
Which has the larger context window?
Both models list a 1,000,000-token context window.
Are these models open weights?
Claude Haiku 4.5 is proprietary; Nova Pro Max is proprietary.
Which should I choose for production?
If you need a single default, start with Nova Pro Max for quality-sensitive work, and check whether its price holds at your expected volume before committing.