DeepSeek-V3.2 Base vs Doubao 1.5 Pro Turbo: which model should you choose?
We compared DeepSeek-V3.2 Base and Doubao 1.5 Pro Turbo on price, context window and 12 benchmarks. DeepSeek-V3.2 Base has the stronger average benchmark score; DeepSeek-V3.2 Base is cheaper on a blended 3:1 basis.
DeepSeek-V3.2 Base
DeepSeek-V3.2 Base is a multimodal model from DeepSeek. It offers a 128,000-token context window, costs $5.05 per million input tokens and $27.10 per million output tokens, and averages 80.2 across the index's benchmark suite.
- Input
- $5.05 / 1M
- Output
- $27.10 / 1M
- Context
- 128,000
- Avg score
- 80.2
- Open weights
- Yes
Doubao 1.5 Pro Turbo
Doubao 1.5 Pro Turbo is a multimodal model from ByteDance. It offers a 128,000-token context window, costs $13.81 per million input tokens and $71.10 per million output tokens, and averages 79.4 across the index's benchmark suite.
- Input
- $13.81 / 1M
- Output
- $71.10 / 1M
- Context
- 128,000
- Avg score
- 79.4
- Open weights
- No
Specification comparison
| Spec | DeepSeek-V3.2 Base | Doubao 1.5 Pro Turbo | Edge |
|---|---|---|---|
| Input price / 1M | $5.05 | $13.81 | A |
| Output price / 1M | $27.10 | $71.10 | A |
| Context window | 128,000 | 128,000 | Tie |
| Max output | 128,000 | 65,536 | A |
| Average score | 80.2 | 79.4 | A |
| Arena Elo | 1417.9 | 1433.0 | B |
| Open weights | Yes | No | A |
Benchmark comparison
DeepSeek-V3.2 Base wins 7, Doubao 1.5 Pro Turbo wins 5, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | DeepSeek-V3.2 Base | Doubao 1.5 Pro Turbo | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 84.3 | 80.3 | 4.0 | DeepSeek-V3.2 Base |
| GPQA Diamond | 77.1 | 75.4 | 1.7 | DeepSeek-V3.2 Base |
| SWE-bench Verified | 69.1 | 67.7 | 1.4 | DeepSeek-V3.2 Base |
| HumanEval | 82.8 | 85.0 | 2.2 | Doubao 1.5 Pro Turbo |
| MATH-500 | 83.7 | 81.4 | 2.3 | DeepSeek-V3.2 Base |
| AIME 2025 | 74.3 | 75.6 | 1.3 | Doubao 1.5 Pro Turbo |
| LiveCodeBench | 73.1 | 72.3 | 0.8 | DeepSeek-V3.2 Base |
| IFEval | 86.9 | 88.9 | 2.0 | Doubao 1.5 Pro Turbo |
| TruthfulQA | 83.5 | 80.9 | 2.6 | DeepSeek-V3.2 Base |
| HellaSwag | 90.2 | 88.2 | 2.0 | DeepSeek-V3.2 Base |
| MMMU | 76.7 | 77.6 | 0.9 | Doubao 1.5 Pro Turbo |
| Arena Elo | 1417.9 | 1433.0 | 15.1 | Doubao 1.5 Pro Turbo |
Price analysis
On a blended 3:1 input-to-output basis, DeepSeek-V3.2 Base costs about $10.56 per million tokens and Doubao 1.5 Pro Turbo costs about $28.13. DeepSeek-V3.2 Base is roughly 62% cheaper than Doubao 1.5 Pro Turbo. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Both models list a 128,000-token context window. That is enough for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, DeepSeek-V3.2 Base wins 7, Doubao 1.5 Pro Turbo wins 5, and 0 are tied. On the index average, DeepSeek-V3.2 Base leads Doubao 1.5 Pro Turbo by 0.8 points (80.2 versus 79.4).
The price picture favours DeepSeek-V3.2 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 DeepSeek-V3.2 Base for quality-sensitive work, and check whether its price holds at your expected volume before committing.
Choose DeepSeek-V3.2 Base 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 Turbo if
- You prefer ByteDance's tooling or already use it.
FAQ
Is DeepSeek-V3.2 Base better than Doubao 1.5 Pro Turbo?
On the index average, DeepSeek-V3.2 Base leads Doubao 1.5 Pro Turbo by 0.8 points (80.2 versus 79.4). The better choice depends on price, context and your task. DeepSeek-V3.2 Base wins 7 benchmarks, Doubao 1.5 Pro Turbo wins 5.
Which is cheaper, DeepSeek-V3.2 Base or Doubao 1.5 Pro Turbo?
DeepSeek-V3.2 Base is cheaper on a blended 3:1 basis at about $10.56 per million tokens, versus $28.13 for Doubao 1.5 Pro Turbo.
Which has the larger context window?
Both models list a 128,000-token context window.
Are these models open weights?
DeepSeek-V3.2 Base is open weights; Doubao 1.5 Pro Turbo is proprietary.
Which should I choose for production?
If you need a single default, start with DeepSeek-V3.2 Base for quality-sensitive work, and check whether its price holds at your expected volume before committing.