Claude 3.7 Sonnet Vision vs DeepSeek-R1 Base: which model should you choose?
We compared Claude 3.7 Sonnet Vision and DeepSeek-R1 Base on price, context window and 12 benchmarks. Claude 3.7 Sonnet Vision has the stronger average benchmark score; DeepSeek-R1 Base is cheaper on a blended 3:1 basis.
Claude 3.7 Sonnet Vision
Claude 3.7 Sonnet Vision is a multimodal model from Anthropic. It offers a 400,000-token context window, costs $13.96 per million input tokens and $56.28 per million output tokens, and averages 81.0 across the index's benchmark suite.
- Input
- $13.96 / 1M
- Output
- $56.28 / 1M
- Context
- 400,000
- Avg score
- 81.0
- Open weights
- No
DeepSeek-R1 Base
DeepSeek-R1 Base is a multimodal model from DeepSeek. It offers a 400,000-token context window, costs $5.05 per million input tokens and $26.24 per million output tokens, and averages 80.1 across the index's benchmark suite.
- Input
- $5.05 / 1M
- Output
- $26.24 / 1M
- Context
- 400,000
- Avg score
- 80.1
- Open weights
- Yes
Specification comparison
| Spec | Claude 3.7 Sonnet Vision | DeepSeek-R1 Base | Edge |
|---|---|---|---|
| Input price / 1M | $13.96 | $5.05 | B |
| Output price / 1M | $56.28 | $26.24 | B |
| Context window | 400,000 | 400,000 | Tie |
| Max output | 8,192 | 65,536 | B |
| Average score | 81.0 | 80.1 | A |
| Arena Elo | 1429.6 | 1442.9 | B |
| Open weights | No | Yes | B |
Benchmark comparison
Claude 3.7 Sonnet Vision wins 5, DeepSeek-R1 Base wins 7, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Claude 3.7 Sonnet Vision | DeepSeek-R1 Base | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 82.5 | 81.0 | 1.5 | Claude 3.7 Sonnet Vision |
| GPQA Diamond | 77.3 | 76.2 | 1.1 | Claude 3.7 Sonnet Vision |
| SWE-bench Verified | 72.2 | 71.2 | 1.0 | Claude 3.7 Sonnet Vision |
| HumanEval | 85.4 | 83.4 | 2.0 | Claude 3.7 Sonnet Vision |
| MATH-500 | 84.8 | 84.9 | 0.1 | DeepSeek-R1 Base |
| AIME 2025 | 80.9 | 73.8 | 7.1 | Claude 3.7 Sonnet Vision |
| LiveCodeBench | 75.7 | 76.0 | 0.3 | DeepSeek-R1 Base |
| IFEval | 87.9 | 88.2 | 0.3 | DeepSeek-R1 Base |
| TruthfulQA | 81.6 | 82.2 | 0.6 | DeepSeek-R1 Base |
| HellaSwag | 89.4 | 90.0 | 0.6 | DeepSeek-R1 Base |
| MMMU | 73.8 | 74.2 | 0.4 | DeepSeek-R1 Base |
| Arena Elo | 1429.6 | 1442.9 | 13.3 | DeepSeek-R1 Base |
Price analysis
On a blended 3:1 input-to-output basis, Claude 3.7 Sonnet Vision costs about $24.54 per million tokens and DeepSeek-R1 Base costs about $10.35. DeepSeek-R1 Base is roughly 58% cheaper than Claude 3.7 Sonnet Vision. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Both models list a 400,000-token context window. That is enough for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Claude 3.7 Sonnet Vision wins 5, DeepSeek-R1 Base wins 7, and 0 are tied. On the index average, Claude 3.7 Sonnet Vision leads DeepSeek-R1 Base by 0.9 points (81.0 versus 80.1).
The price picture favours DeepSeek-R1 Base. 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 Claude 3.7 Sonnet Vision for quality-sensitive work and DeepSeek-R1 Base for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose Claude 3.7 Sonnet Vision if
- You want the higher average benchmark score in this index.
Choose DeepSeek-R1 Base if
- Unit cost matters and you want the cheaper blended price.
- You need the larger 65,536-token output limit.
- You need open weights for self-hosting or fine-tuning.
FAQ
Is Claude 3.7 Sonnet Vision better than DeepSeek-R1 Base?
On the index average, Claude 3.7 Sonnet Vision leads DeepSeek-R1 Base by 0.9 points (81.0 versus 80.1). The better choice depends on price, context and your task. Claude 3.7 Sonnet Vision wins 5 benchmarks, DeepSeek-R1 Base wins 7.
Which is cheaper, Claude 3.7 Sonnet Vision or DeepSeek-R1 Base?
DeepSeek-R1 Base is cheaper on a blended 3:1 basis at about $10.35 per million tokens, versus $24.54 for Claude 3.7 Sonnet Vision.
Which has the larger context window?
Both models list a 400,000-token context window.
Are these models open weights?
Claude 3.7 Sonnet Vision is proprietary; DeepSeek-R1 Base is open weights.
Which should I choose for production?
If you need a single default, start with Claude 3.7 Sonnet Vision for quality-sensitive work and DeepSeek-R1 Base for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.