Model comparison
Kimi K2.5 vs MiniMax M2.1
- Input
- $0.60 / 1M tokens
- Output
- $2.50 / 1M tokens
- Context
- 256K
- Released
- 2026-01-27
- Input
- $0.30 / 1M tokens
- Output
- $1.20 / 1M tokens
- Context
- 205K
- Released
- 2025-12-23
Kimi K2.5 scores higher on 5 of the 6 benchmarks both models report (the other leads on 1); MiniMax M2.1 is cheaper on input tokens ($0.3 vs $0.6 per 1M, 2×); Kimi K2.5 has the larger context window (256K vs 205K).
Specs and pricing side by side
| Spec | Kimi K2.5 | MiniMax M2.1 |
|---|---|---|
| Maker | Moonshot AI (Kimi) | MiniMax |
| Released | 2026-01-27 | 2025-12-23 |
| Context window | 256K | 205K |
| Max output | 16K | 196,608 tokens |
| Input price | $0.60 / 1M tokens | $0.30 / 1M tokens |
| Output price | $2.50 / 1M tokens | $1.20 / 1M tokens |
| Parameters | 1T total, 32B active (MoE) | 230B total / 10B active (MoE) |
| License | Modified MIT License | Modified MIT |
| Weights | Open weights | Open weightssame |
| Modalities | Text, Vision, Video | Text |
Not published by either maker: knowledge cutoff.
Benchmarks both models report
| Benchmark | Kimi K2.5 | MiniMax M2.1 |
|---|---|---|
| SWE-bench Verified | 76.8% | 74% |
| SWE-bench Multilingual | 73% | 72.5% |
| Terminal-Bench 2.0 | 50.8% | 47.9% |
| AIME 2025 | 96.1% | 83% |
| GPQA-Diamond | 87.6% | 83% |
| MMLU-Pro | 87.1% | 88% |
Scores are as published by each maker or its cited source; harness, reasoning effort and date can differ between rows, so treat small gaps as ties. Sources are listed on each model page.
Which one should you pick?
Pick Kimi K2.5 if…
- You care about SWE-bench Verified, SWE-bench Multilingual, Terminal-Bench 2.0 (it scores higher on 5 shared benchmarks).
- You need the longer context (256K vs 205K).
- You need Vision / Video input, which MiniMax M2.1 lacks.
- Your use case is: agentic software engineering: multi-file bug fixes, refactors, and repo-level tasks.
Pick MiniMax M2.1 if…
- You care about MMLU-Pro (it scores higher on 1 shared benchmark).
- Cost matters: input tokens cost 2× less ($0.3 vs $0.6 per 1M).
- Your use case is: autonomous and assisted software engineering across many programming languages.
FAQ
Which is better, Kimi K2.5 or MiniMax M2.1?
Kimi K2.5 scores higher on 5 of the 6 benchmarks both models report (the other leads on 1); MiniMax M2.1 is cheaper on input tokens ($0.3 vs $0.6 per 1M, 2×); Kimi K2.5 has the larger context window (256K vs 205K). The better pick depends on whether you value benchmark scores, price per token, context length or openness for your workload.
How much cheaper is MiniMax M2.1?
Kimi K2.5: $0.60 / 1M tokens input, $2.50 / 1M tokens output. MiniMax M2.1: $0.30 / 1M tokens input, $1.20 / 1M tokens output (list API prices as published by each maker).
What are the context windows of Kimi K2.5 and MiniMax M2.1?
Kimi K2.5 offers 256K with up to 16K output; MiniMax M2.1 offers 205K with up to 196,608 tokens output.
Is Kimi K2.5 newer than MiniMax M2.1?
Kimi K2.5 was released 2026-01-27; MiniMax M2.1 was released 2025-12-23.