DeepSeek-R1 Chat vs Grok 3 Turbo: which model should you choose?
We compared DeepSeek-R1 Chat and Grok 3 Turbo on price, context window and 12 benchmarks. Grok 3 Turbo 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
Grok 3 Turbo
Grok 3 Turbo is a multimodal model from xAI. It offers a 128,000-token context window, costs $15.97 per million input tokens and $70.13 per million output tokens, and averages 83.1 across the index's benchmark suite.
- Input
- $15.97 / 1M
- Output
- $70.13 / 1M
- Context
- 128,000
- Avg score
- 83.1
- Open weights
- No
Specification comparison
| Spec | DeepSeek-R1 Chat | Grok 3 Turbo | Edge |
|---|---|---|---|
| Input price / 1M | $5.62 | $15.97 | A |
| Output price / 1M | $21.49 | $70.13 | A |
| Context window | 400,000 | 128,000 | A |
| Max output | 128,000 | 65,536 | A |
| Average score | 82.4 | 83.1 | B |
| Arena Elo | 1433.3 | 1438.4 | B |
| Open weights | Yes | No | A |
Benchmark comparison
DeepSeek-R1 Chat wins 5, Grok 3 Turbo wins 7, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | DeepSeek-R1 Chat | Grok 3 Turbo | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 83.4 | 83.7 | 0.3 | Grok 3 Turbo |
| GPQA Diamond | 80.0 | 79.1 | 0.9 | DeepSeek-R1 Chat |
| SWE-bench Verified | 71.7 | 71.4 | 0.3 | DeepSeek-R1 Chat |
| HumanEval | 84.9 | 86.8 | 1.9 | Grok 3 Turbo |
| MATH-500 | 89.1 | 85.6 | 3.5 | DeepSeek-R1 Chat |
| AIME 2025 | 78.6 | 83.1 | 4.5 | Grok 3 Turbo |
| LiveCodeBench | 79.3 | 76.4 | 2.9 | DeepSeek-R1 Chat |
| IFEval | 89.5 | 90.7 | 1.2 | Grok 3 Turbo |
| TruthfulQA | 82.3 | 86.0 | 3.7 | Grok 3 Turbo |
| HellaSwag | 90.6 | 90.2 | 0.4 | DeepSeek-R1 Chat |
| MMMU | 77.1 | 81.3 | 4.2 | Grok 3 Turbo |
| Arena Elo | 1433.3 | 1438.4 | 5.1 | Grok 3 Turbo |
Price analysis
On a blended 3:1 input-to-output basis, DeepSeek-R1 Chat costs about $9.59 per million tokens and Grok 3 Turbo costs about $29.51. DeepSeek-R1 Chat is roughly 68% cheaper than Grok 3 Turbo. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
DeepSeek-R1 Chat has the larger context window at 400,000 tokens, compared with 128,000 for Grok 3 Turbo. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, DeepSeek-R1 Chat wins 5, Grok 3 Turbo wins 7, and 0 are tied. On the index average, Grok 3 Turbo leads DeepSeek-R1 Chat by 0.7 points (83.1 versus 82.4).
The price picture favours DeepSeek-R1 Chat. The context picture favours DeepSeek-R1 Chat. 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 Grok 3 Turbo for quality-sensitive work and DeepSeek-R1 Chat for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose DeepSeek-R1 Chat if
- Unit cost matters and you want the cheaper blended price.
- You need the larger 400,000-token context window.
- You need the larger 128,000-token output limit.
- You need open weights for self-hosting or fine-tuning.
Choose Grok 3 Turbo if
- You want the higher average benchmark score in this index.
FAQ
Is DeepSeek-R1 Chat better than Grok 3 Turbo?
On the index average, Grok 3 Turbo leads DeepSeek-R1 Chat by 0.7 points (83.1 versus 82.4). The better choice depends on price, context and your task. DeepSeek-R1 Chat wins 5 benchmarks, Grok 3 Turbo wins 7.
Which is cheaper, DeepSeek-R1 Chat or Grok 3 Turbo?
DeepSeek-R1 Chat is cheaper on a blended 3:1 basis at about $9.59 per million tokens, versus $29.51 for Grok 3 Turbo.
Which has the larger context window?
DeepSeek-R1 Chat has the larger context window at 400,000 tokens. Grok 3 Turbo has 128,000 tokens.
Are these models open weights?
DeepSeek-R1 Chat is open weights; Grok 3 Turbo is proprietary.
Which should I choose for production?
If you need a single default, start with Grok 3 Turbo for quality-sensitive work and DeepSeek-R1 Chat for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.