Kimi K1.5 Instruct vs MiniMax-M2 Instruct: which model should you choose?
We compared Kimi K1.5 Instruct and MiniMax-M2 Instruct on price, context window and 12 benchmarks. Kimi K1.5 Instruct has the stronger average benchmark score; MiniMax-M2 Instruct is cheaper on a blended 3:1 basis.
Kimi K1.5 Instruct
Kimi K1.5 Instruct is a multimodal model from Moonshot AI. It offers a 200,000-token context window, costs $5.15 per million input tokens and $28.20 per million output tokens, and averages 80.5 across the index's benchmark suite.
- Input
- $5.15 / 1M
- Output
- $28.20 / 1M
- Context
- 200,000
- Avg score
- 80.5
- Open weights
- Yes
MiniMax-M2 Instruct
MiniMax-M2 Instruct is a multimodal model from MiniMax. It offers a 128,000-token context window, costs $5.11 per million input tokens and $25.04 per million output tokens, and averages 79.4 across the index's benchmark suite.
- Input
- $5.11 / 1M
- Output
- $25.04 / 1M
- Context
- 128,000
- Avg score
- 79.4
- Open weights
- Yes
Specification comparison
| Spec | Kimi K1.5 Instruct | MiniMax-M2 Instruct | Edge |
|---|---|---|---|
| Input price / 1M | $5.15 | $5.11 | B |
| Output price / 1M | $28.20 | $25.04 | B |
| Context window | 200,000 | 128,000 | A |
| Max output | 4,096 | 4,096 | Tie |
| Average score | 80.5 | 79.4 | A |
| Arena Elo | 1431.8 | 1442.2 | B |
| Open weights | Yes | Yes | Tie |
Benchmark comparison
Kimi K1.5 Instruct wins 7, MiniMax-M2 Instruct wins 4, and 1 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Kimi K1.5 Instruct | MiniMax-M2 Instruct | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 83.0 | 82.1 | 0.9 | Kimi K1.5 Instruct |
| GPQA Diamond | 77.4 | 73.7 | 3.7 | Kimi K1.5 Instruct |
| SWE-bench Verified | 67.8 | 69.9 | 2.1 | MiniMax-M2 Instruct |
| HumanEval | 84.0 | 86.7 | 2.7 | MiniMax-M2 Instruct |
| MATH-500 | 82.6 | 82.1 | 0.5 | Kimi K1.5 Instruct |
| AIME 2025 | 80.4 | 77.8 | 2.6 | Kimi K1.5 Instruct |
| LiveCodeBench | 71.1 | 71.1 | 0.0 | Tie |
| IFEval | 86.2 | 87.3 | 1.1 | MiniMax-M2 Instruct |
| TruthfulQA | 84.3 | 80.0 | 4.3 | Kimi K1.5 Instruct |
| HellaSwag | 90.2 | 88.5 | 1.7 | Kimi K1.5 Instruct |
| MMMU | 78.6 | 74.1 | 4.5 | Kimi K1.5 Instruct |
| Arena Elo | 1431.8 | 1442.2 | 10.4 | MiniMax-M2 Instruct |
Price analysis
On a blended 3:1 input-to-output basis, Kimi K1.5 Instruct costs about $10.91 per million tokens and MiniMax-M2 Instruct costs about $10.09. MiniMax-M2 Instruct is roughly 8% cheaper than Kimi K1.5 Instruct. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Kimi K1.5 Instruct has the larger context window at 200,000 tokens, compared with 128,000 for MiniMax-M2 Instruct. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Kimi K1.5 Instruct wins 7, MiniMax-M2 Instruct wins 4, and 1 are tied. On the index average, Kimi K1.5 Instruct leads MiniMax-M2 Instruct by 1.1 points (80.5 versus 79.4).
The price picture favours MiniMax-M2 Instruct. The context picture favours Kimi K1.5 Instruct. 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 Instruct for quality-sensitive work and MiniMax-M2 Instruct for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose Kimi K1.5 Instruct if
- You want the higher average benchmark score in this index.
- You need the larger 200,000-token context window.
Choose MiniMax-M2 Instruct if
- Unit cost matters and you want the cheaper blended price.
FAQ
Is Kimi K1.5 Instruct better than MiniMax-M2 Instruct?
On the index average, Kimi K1.5 Instruct leads MiniMax-M2 Instruct by 1.1 points (80.5 versus 79.4). The better choice depends on price, context and your task. Kimi K1.5 Instruct wins 7 benchmarks, MiniMax-M2 Instruct wins 4.
Which is cheaper, Kimi K1.5 Instruct or MiniMax-M2 Instruct?
MiniMax-M2 Instruct is cheaper on a blended 3:1 basis at about $10.09 per million tokens, versus $10.91 for Kimi K1.5 Instruct.
Which has the larger context window?
Kimi K1.5 Instruct has the larger context window at 200,000 tokens. MiniMax-M2 Instruct has 128,000 tokens.
Are these models open weights?
Kimi K1.5 Instruct is open weights; MiniMax-M2 Instruct is open weights.
Which should I choose for production?
If you need a single default, start with Kimi K1.5 Instruct for quality-sensitive work and MiniMax-M2 Instruct for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.