DeepSeek-R1 vs Gemini 2.5 Pro: which model should you choose?
We compared DeepSeek-R1 and Gemini 2.5 Pro on price, context window and 12 benchmarks. DeepSeek-R1 has the stronger average benchmark score; DeepSeek-R1 is cheaper on a blended 3:1 basis.
DeepSeek-R1
DeepSeek-R1 is a multimodal model from DeepSeek. It offers a 128,000-token context window, costs $5.83 per million input tokens and $25.23 per million output tokens, and averages 82.8 across the index's benchmark suite.
- Input
- $5.83 / 1M
- Output
- $25.23 / 1M
- Context
- 128,000
- Avg score
- 82.8
- Open weights
- Yes
Gemini 2.5 Pro
Gemini 2.5 Pro is a multimodal model from Google DeepMind. It offers a 200,000-token context window, costs $15.20 per million input tokens and $57.83 per million output tokens, and averages 81.6 across the index's benchmark suite.
- Input
- $15.20 / 1M
- Output
- $57.83 / 1M
- Context
- 200,000
- Avg score
- 81.6
- Open weights
- No
Specification comparison
| Spec | DeepSeek-R1 | Gemini 2.5 Pro | Edge |
|---|---|---|---|
| Input price / 1M | $5.83 | $15.20 | A |
| Output price / 1M | $25.23 | $57.83 | A |
| Context window | 128,000 | 200,000 | B |
| Max output | 4,096 | 16,384 | B |
| Average score | 82.8 | 81.6 | A |
| Arena Elo | 1454.1 | 1455.0 | B |
| Open weights | Yes | No | A |
Benchmark comparison
DeepSeek-R1 wins 9, Gemini 2.5 Pro wins 3, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | DeepSeek-R1 | Gemini 2.5 Pro | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 83.8 | 83.6 | 0.2 | DeepSeek-R1 |
| GPQA Diamond | 77.8 | 76.5 | 1.3 | DeepSeek-R1 |
| SWE-bench Verified | 72.2 | 70.2 | 2.0 | DeepSeek-R1 |
| HumanEval | 86.4 | 87.7 | 1.3 | Gemini 2.5 Pro |
| MATH-500 | 89.1 | 86.8 | 2.3 | DeepSeek-R1 |
| AIME 2025 | 81.1 | 76.1 | 5.0 | DeepSeek-R1 |
| LiveCodeBench | 77.4 | 76.2 | 1.2 | DeepSeek-R1 |
| IFEval | 91.0 | 87.6 | 3.4 | DeepSeek-R1 |
| TruthfulQA | 82.9 | 82.8 | 0.1 | DeepSeek-R1 |
| HellaSwag | 89.8 | 89.7 | 0.1 | DeepSeek-R1 |
| MMMU | 79.5 | 80.5 | 1.0 | Gemini 2.5 Pro |
| Arena Elo | 1454.1 | 1455.0 | 0.9 | Gemini 2.5 Pro |
Price analysis
On a blended 3:1 input-to-output basis, DeepSeek-R1 costs about $10.68 per million tokens and Gemini 2.5 Pro costs about $25.86. DeepSeek-R1 is roughly 59% cheaper than Gemini 2.5 Pro. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Gemini 2.5 Pro has the larger context window at 200,000 tokens, compared with 128,000 for DeepSeek-R1. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, DeepSeek-R1 wins 9, Gemini 2.5 Pro wins 3, and 0 are tied. On the index average, DeepSeek-R1 leads Gemini 2.5 Pro by 1.2 points (82.8 versus 81.6).
The price picture favours DeepSeek-R1. The context picture favours Gemini 2.5 Pro. 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 for quality-sensitive work, and check whether its price holds at your expected volume before committing.
Choose DeepSeek-R1 if
- You want the higher average benchmark score in this index.
- Unit cost matters and you want the cheaper blended price.
- You need open weights for self-hosting or fine-tuning.
Choose Gemini 2.5 Pro if
- You need the larger 200,000-token context window.
- You need the larger 16,384-token output limit.
FAQ
Is DeepSeek-R1 better than Gemini 2.5 Pro?
On the index average, DeepSeek-R1 leads Gemini 2.5 Pro by 1.2 points (82.8 versus 81.6). The better choice depends on price, context and your task. DeepSeek-R1 wins 9 benchmarks, Gemini 2.5 Pro wins 3.
Which is cheaper, DeepSeek-R1 or Gemini 2.5 Pro?
DeepSeek-R1 is cheaper on a blended 3:1 basis at about $10.68 per million tokens, versus $25.86 for Gemini 2.5 Pro.
Which has the larger context window?
Gemini 2.5 Pro has the larger context window at 200,000 tokens. DeepSeek-R1 has 128,000 tokens.
Are these models open weights?
DeepSeek-R1 is open weights; Gemini 2.5 Pro is proprietary.
Which should I choose for production?
If you need a single default, start with DeepSeek-R1 for quality-sensitive work, and check whether its price holds at your expected volume before committing.