Gemini 2.5 Pro Vision vs Kimi K1.5: which model should you choose?
We compared Gemini 2.5 Pro Vision and Kimi K1.5 on price, context window and 12 benchmarks. Gemini 2.5 Pro Vision has the stronger average benchmark score; Kimi K1.5 is cheaper on a blended 3:1 basis.
Gemini 2.5 Pro Vision
Gemini 2.5 Pro Vision is a multimodal model from Google DeepMind. It offers a 200,000-token context window, costs $14.91 per million input tokens and $71.00 per million output tokens, and averages 82.0 across the index's benchmark suite.
- Input
- $14.91 / 1M
- Output
- $71.00 / 1M
- Context
- 200,000
- Avg score
- 82.0
- 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 | Gemini 2.5 Pro Vision | Kimi K1.5 | Edge |
|---|---|---|---|
| Input price / 1M | $14.91 | $5.19 | B |
| Output price / 1M | $71.00 | $21.20 | B |
| Context window | 200,000 | 128,000 | A |
| Max output | 4,096 | 4,096 | Tie |
| Average score | 82.0 | 80.7 | A |
| Arena Elo | 1451.3 | 1432.2 | A |
| Open weights | No | Yes | B |
Benchmark comparison
Gemini 2.5 Pro Vision wins 8, Kimi K1.5 wins 4, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Gemini 2.5 Pro Vision | Kimi K1.5 | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 83.9 | 82.7 | 1.2 | Gemini 2.5 Pro Vision |
| GPQA Diamond | 78.0 | 74.4 | 3.6 | Gemini 2.5 Pro Vision |
| SWE-bench Verified | 72.4 | 68.2 | 4.2 | Gemini 2.5 Pro Vision |
| HumanEval | 85.8 | 87.1 | 1.3 | Kimi K1.5 |
| MATH-500 | 82.9 | 85.3 | 2.4 | Kimi K1.5 |
| AIME 2025 | 80.0 | 80.8 | 0.8 | Kimi K1.5 |
| LiveCodeBench | 76.0 | 71.1 | 4.9 | Gemini 2.5 Pro Vision |
| IFEval | 90.2 | 87.9 | 2.3 | Gemini 2.5 Pro Vision |
| TruthfulQA | 84.1 | 84.7 | 0.6 | Kimi K1.5 |
| HellaSwag | 90.8 | 87.2 | 3.6 | Gemini 2.5 Pro Vision |
| MMMU | 78.2 | 77.8 | 0.4 | Gemini 2.5 Pro Vision |
| Arena Elo | 1451.3 | 1432.2 | 19.1 | Gemini 2.5 Pro Vision |
Price analysis
On a blended 3:1 input-to-output basis, Gemini 2.5 Pro Vision costs about $28.93 per million tokens and Kimi K1.5 costs about $9.19. Kimi K1.5 is roughly 68% cheaper than Gemini 2.5 Pro Vision. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Gemini 2.5 Pro Vision has the larger context window at 200,000 tokens, compared with 128,000 for Kimi K1.5. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Gemini 2.5 Pro Vision wins 8, Kimi K1.5 wins 4, and 0 are tied. On the index average, Gemini 2.5 Pro Vision leads Kimi K1.5 by 1.3 points (82.0 versus 80.7).
The price picture favours Kimi K1.5. The context picture favours Gemini 2.5 Pro Vision. 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 Gemini 2.5 Pro Vision for quality-sensitive work and Kimi K1.5 for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose Gemini 2.5 Pro Vision if
- You want the higher average benchmark score in this index.
- You need the larger 200,000-token context window.
Choose Kimi K1.5 if
- Unit cost matters and you want the cheaper blended price.
- You need open weights for self-hosting or fine-tuning.
FAQ
Is Gemini 2.5 Pro Vision better than Kimi K1.5?
On the index average, Gemini 2.5 Pro Vision leads Kimi K1.5 by 1.3 points (82.0 versus 80.7). The better choice depends on price, context and your task. Gemini 2.5 Pro Vision wins 8 benchmarks, Kimi K1.5 wins 4.
Which is cheaper, Gemini 2.5 Pro Vision or Kimi K1.5?
Kimi K1.5 is cheaper on a blended 3:1 basis at about $9.19 per million tokens, versus $28.93 for Gemini 2.5 Pro Vision.
Which has the larger context window?
Gemini 2.5 Pro Vision has the larger context window at 200,000 tokens. Kimi K1.5 has 128,000 tokens.
Are these models open weights?
Gemini 2.5 Pro Vision is proprietary; Kimi K1.5 is open weights.
Which should I choose for production?
If you need a single default, start with Gemini 2.5 Pro Vision for quality-sensitive work and Kimi K1.5 for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.