Doubao 1.5 Pro Pro vs Kimi K1.5: which model should you choose?
We compared Doubao 1.5 Pro Pro and Kimi K1.5 on price, context window and 12 benchmarks. Kimi K1.5 has the stronger average benchmark score; Kimi K1.5 is cheaper on a blended 3:1 basis.
Doubao 1.5 Pro Pro
Doubao 1.5 Pro Pro is a multimodal model from ByteDance. It offers a 128,000-token context window, costs $14.10 per million input tokens and $54.74 per million output tokens, and averages 80.2 across the index's benchmark suite.
- Input
- $14.10 / 1M
- Output
- $54.74 / 1M
- Context
- 128,000
- Avg score
- 80.2
- Open weights
- No
Kimi K1.5
Kimi K1.5 is a multimodal model from Moonshot AI. It offers a 128,000-token context window, costs $5.19 per million input tokens and $21.20 per million output tokens, and averages 80.7 across the index's benchmark suite.
- Input
- $5.19 / 1M
- Output
- $21.20 / 1M
- Context
- 128,000
- Avg score
- 80.7
- Open weights
- Yes
Specification comparison
| Spec | Doubao 1.5 Pro Pro | Kimi K1.5 | Edge |
|---|---|---|---|
| Input price / 1M | $14.10 | $5.19 | B |
| Output price / 1M | $54.74 | $21.20 | B |
| Context window | 128,000 | 128,000 | Tie |
| Max output | 8,192 | 4,096 | A |
| Average score | 80.2 | 80.7 | B |
| Arena Elo | 1443.4 | 1432.2 | A |
| Open weights | No | Yes | B |
Benchmark comparison
Doubao 1.5 Pro Pro wins 6, Kimi K1.5 wins 5, and 1 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Doubao 1.5 Pro Pro | Kimi K1.5 | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 80.2 | 82.7 | 2.5 | Kimi K1.5 |
| GPQA Diamond | 74.5 | 74.4 | 0.1 | Doubao 1.5 Pro Pro |
| SWE-bench Verified | 71.2 | 68.2 | 3.0 | Doubao 1.5 Pro Pro |
| HumanEval | 84.4 | 87.1 | 2.7 | Kimi K1.5 |
| MATH-500 | 85.4 | 85.3 | 0.1 | Doubao 1.5 Pro Pro |
| AIME 2025 | 77.7 | 80.8 | 3.1 | Kimi K1.5 |
| LiveCodeBench | 71.6 | 71.1 | 0.5 | Doubao 1.5 Pro Pro |
| IFEval | 87.8 | 87.9 | 0.1 | Kimi K1.5 |
| TruthfulQA | 84.6 | 84.7 | 0.1 | Kimi K1.5 |
| HellaSwag | 87.2 | 87.2 | 0.0 | Tie |
| MMMU | 78.1 | 77.8 | 0.3 | Doubao 1.5 Pro Pro |
| Arena Elo | 1443.4 | 1432.2 | 11.2 | Doubao 1.5 Pro Pro |
Price analysis
On a blended 3:1 input-to-output basis, Doubao 1.5 Pro Pro costs about $24.26 per million tokens and Kimi K1.5 costs about $9.19. Kimi K1.5 is roughly 62% cheaper than Doubao 1.5 Pro Pro. 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, Doubao 1.5 Pro Pro wins 6, Kimi K1.5 wins 5, and 1 are tied. On the index average, Kimi K1.5 leads Doubao 1.5 Pro Pro by 0.5 points (80.7 versus 80.2).
The price picture favours Kimi K1.5. 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 Kimi K1.5 for quality-sensitive work, and check whether its price holds at your expected volume before committing.
Choose Doubao 1.5 Pro Pro if
- You need the larger 8,192-token output limit.
Choose Kimi K1.5 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.
FAQ
Is Doubao 1.5 Pro Pro better than Kimi K1.5?
On the index average, Kimi K1.5 leads Doubao 1.5 Pro Pro by 0.5 points (80.7 versus 80.2). The better choice depends on price, context and your task. Doubao 1.5 Pro Pro wins 6 benchmarks, Kimi K1.5 wins 5.
Which is cheaper, Doubao 1.5 Pro Pro or Kimi K1.5?
Kimi K1.5 is cheaper on a blended 3:1 basis at about $9.19 per million tokens, versus $24.26 for Doubao 1.5 Pro Pro.
Which has the larger context window?
Both models list a 128,000-token context window.
Are these models open weights?
Doubao 1.5 Pro Pro is proprietary; Kimi K1.5 is open weights.
Which should I choose for production?
If you need a single default, start with Kimi K1.5 for quality-sensitive work, and check whether its price holds at your expected volume before committing.