DeepSeek-R1 Chat vs Doubao 1.5 Pro Max: which model should you choose?
We compared DeepSeek-R1 Chat and Doubao 1.5 Pro Max 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
Doubao 1.5 Pro Max
Doubao 1.5 Pro Max is a multimodal model from ByteDance. It offers a 400,000-token context window, costs $14.93 per million input tokens and $73.69 per million output tokens, and averages 81.2 across the index's benchmark suite.
- Input
- $14.93 / 1M
- Output
- $73.69 / 1M
- Context
- 400,000
- Avg score
- 81.2
- Open weights
- No
Specification comparison
| Spec | DeepSeek-R1 Chat | Doubao 1.5 Pro Max | Edge |
|---|---|---|---|
| Input price / 1M | $5.62 | $14.93 | A |
| Output price / 1M | $21.49 | $73.69 | A |
| Context window | 400,000 | 400,000 | Tie |
| Max output | 128,000 | 4,096 | A |
| Average score | 82.4 | 81.2 | A |
| Arena Elo | 1433.3 | 1447.5 | B |
| Open weights | Yes | No | A |
Benchmark comparison
DeepSeek-R1 Chat wins 7, Doubao 1.5 Pro Max wins 5, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | DeepSeek-R1 Chat | Doubao 1.5 Pro Max | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 83.4 | 81.1 | 2.3 | DeepSeek-R1 Chat |
| GPQA Diamond | 80.0 | 76.1 | 3.9 | DeepSeek-R1 Chat |
| SWE-bench Verified | 71.7 | 70.7 | 1.0 | DeepSeek-R1 Chat |
| HumanEval | 84.9 | 84.0 | 0.9 | DeepSeek-R1 Chat |
| MATH-500 | 89.1 | 85.3 | 3.8 | DeepSeek-R1 Chat |
| AIME 2025 | 78.6 | 80.4 | 1.8 | Doubao 1.5 Pro Max |
| LiveCodeBench | 79.3 | 73.5 | 5.8 | DeepSeek-R1 Chat |
| IFEval | 89.5 | 90.2 | 0.7 | Doubao 1.5 Pro Max |
| TruthfulQA | 82.3 | 84.4 | 2.1 | Doubao 1.5 Pro Max |
| HellaSwag | 90.6 | 87.8 | 2.8 | DeepSeek-R1 Chat |
| MMMU | 77.1 | 79.3 | 2.2 | Doubao 1.5 Pro Max |
| Arena Elo | 1433.3 | 1447.5 | 14.2 | Doubao 1.5 Pro Max |
Price analysis
On a blended 3:1 input-to-output basis, DeepSeek-R1 Chat costs about $9.59 per million tokens and Doubao 1.5 Pro Max costs about $29.62. DeepSeek-R1 Chat is roughly 68% cheaper than Doubao 1.5 Pro Max. 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, DeepSeek-R1 Chat wins 7, Doubao 1.5 Pro Max wins 5, and 0 are tied. On the index average, DeepSeek-R1 Chat leads Doubao 1.5 Pro Max by 1.2 points (82.4 versus 81.2).
The price picture favours DeepSeek-R1 Chat. 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 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 Doubao 1.5 Pro Max if
- You prefer ByteDance's tooling or already use it.
FAQ
Is DeepSeek-R1 Chat better than Doubao 1.5 Pro Max?
On the index average, DeepSeek-R1 Chat leads Doubao 1.5 Pro Max by 1.2 points (82.4 versus 81.2). The better choice depends on price, context and your task. DeepSeek-R1 Chat wins 7 benchmarks, Doubao 1.5 Pro Max wins 5.
Which is cheaper, DeepSeek-R1 Chat or Doubao 1.5 Pro Max?
DeepSeek-R1 Chat is cheaper on a blended 3:1 basis at about $9.59 per million tokens, versus $29.62 for Doubao 1.5 Pro Max.
Which has the larger context window?
Both models list a 400,000-token context window.
Are these models open weights?
DeepSeek-R1 Chat is open weights; Doubao 1.5 Pro Max 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.