DeepSeek-R1 Chat vs GPT-4.1 Vision: which model should you choose?
We compared DeepSeek-R1 Chat and GPT-4.1 Vision on price, context window and 12 benchmarks. DeepSeek-R1 Chat has the stronger average benchmark score; DeepSeek-R1 Chat is cheaper on a blended 3:1 basis.
DeepSeek-R1 Chat
DeepSeek-R1 Chat is a multimodal model from DeepSeek. It offers a 400,000-token context window, costs $5.62 per million input tokens and $21.49 per million output tokens, and averages 82.4 across the index's benchmark suite.
- Input
- $5.62 / 1M
- Output
- $21.49 / 1M
- Context
- 400,000
- Avg score
- 82.4
- Open weights
- Yes
GPT-4.1 Vision
GPT-4.1 Vision is a multimodal model from OpenAI. It offers a 1,000,000-token context window, costs $14.88 per million input tokens and $81.24 per million output tokens, and averages 82.0 across the index's benchmark suite.
- Input
- $14.88 / 1M
- Output
- $81.24 / 1M
- Context
- 1,000,000
- Avg score
- 82.0
- Open weights
- No
Specification comparison
| Spec | DeepSeek-R1 Chat | GPT-4.1 Vision | Edge |
|---|---|---|---|
| Input price / 1M | $5.62 | $14.88 | A |
| Output price / 1M | $21.49 | $81.24 | A |
| Context window | 400,000 | 1,000,000 | B |
| Max output | 128,000 | 8,192 | A |
| Average score | 82.4 | 82.0 | A |
| Arena Elo | 1433.3 | 1451.8 | B |
| Open weights | Yes | No | A |
Benchmark comparison
DeepSeek-R1 Chat wins 6, GPT-4.1 Vision wins 6, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | DeepSeek-R1 Chat | GPT-4.1 Vision | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 83.4 | 84.0 | 0.6 | GPT-4.1 Vision |
| GPQA Diamond | 80.0 | 79.3 | 0.7 | DeepSeek-R1 Chat |
| SWE-bench Verified | 71.7 | 72.4 | 0.7 | GPT-4.1 Vision |
| HumanEval | 84.9 | 86.8 | 1.9 | GPT-4.1 Vision |
| MATH-500 | 89.1 | 87.5 | 1.6 | DeepSeek-R1 Chat |
| AIME 2025 | 78.6 | 77.2 | 1.4 | DeepSeek-R1 Chat |
| LiveCodeBench | 79.3 | 74.3 | 5.0 | DeepSeek-R1 Chat |
| IFEval | 89.5 | 88.7 | 0.8 | DeepSeek-R1 Chat |
| TruthfulQA | 82.3 | 84.4 | 2.1 | GPT-4.1 Vision |
| HellaSwag | 90.6 | 89.7 | 0.9 | DeepSeek-R1 Chat |
| MMMU | 77.1 | 77.5 | 0.4 | GPT-4.1 Vision |
| Arena Elo | 1433.3 | 1451.8 | 18.5 | GPT-4.1 Vision |
Price analysis
On a blended 3:1 input-to-output basis, DeepSeek-R1 Chat costs about $9.59 per million tokens and GPT-4.1 Vision costs about $31.47. DeepSeek-R1 Chat is roughly 70% cheaper than GPT-4.1 Vision. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
GPT-4.1 Vision has the larger context window at 1,000,000 tokens, compared with 400,000 for DeepSeek-R1 Chat. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, DeepSeek-R1 Chat wins 6, GPT-4.1 Vision wins 6, and 0 are tied. On the index average, DeepSeek-R1 Chat leads GPT-4.1 Vision by 0.4 points (82.4 versus 82.0).
The price picture favours DeepSeek-R1 Chat. The context picture favours GPT-4.1 Vision. 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 DeepSeek-R1 Chat for quality-sensitive work, and check whether its price holds at your expected volume before committing.
Choose DeepSeek-R1 Chat if
- You want the higher average benchmark score in this index.
- Unit cost matters and you want the cheaper blended price.
- You need the larger 128,000-token output limit.
- You need open weights for self-hosting or fine-tuning.
Choose GPT-4.1 Vision if
- You need the larger 1,000,000-token context window.
FAQ
Is DeepSeek-R1 Chat better than GPT-4.1 Vision?
On the index average, DeepSeek-R1 Chat leads GPT-4.1 Vision by 0.4 points (82.4 versus 82.0). The better choice depends on price, context and your task. DeepSeek-R1 Chat wins 6 benchmarks, GPT-4.1 Vision wins 6.
Which is cheaper, DeepSeek-R1 Chat or GPT-4.1 Vision?
DeepSeek-R1 Chat is cheaper on a blended 3:1 basis at about $9.59 per million tokens, versus $31.47 for GPT-4.1 Vision.
Which has the larger context window?
GPT-4.1 Vision has the larger context window at 1,000,000 tokens. DeepSeek-R1 Chat has 400,000 tokens.
Are these models open weights?
DeepSeek-R1 Chat is open weights; GPT-4.1 Vision is proprietary.
Which should I choose for production?
If you need a single default, start with DeepSeek-R1 Chat for quality-sensitive work, and check whether its price holds at your expected volume before committing.