Model Comparison
MiniMax M2.7 vs Kimi K2.6Which is better in 2026?
Kimi K2.6 significantly outperforms across most benchmarks. MiniMax M2.7 is 2.7x cheaper per token.
Verdict: MiniMax M2.7 vs Kimi K2.6 — which is better?
MiniMax M2.7 (by MiniMax) and Kimi K2.6 (by Moonshot AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
MiniMax M2.7 outperforms in 0 benchmarks, while Kimi K2.6 is better at 6 benchmarks (Finance Agent v2, GDPval-AA, SWE-bench Multilingual, SWE-Bench Pro, Terminal-Bench 2.0, Toolathlon). Kimi K2.6 significantly outperforms across most benchmarks.
On price, MiniMax M2.7 is roughly 2.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Kimi K2.6 also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Choose MiniMax M2.7 if…
- cost matters — it's about 2.7x cheaper per token
Choose Kimi K2.6 if…
- you want the strongest raw capability — it leads on 6 of 6 shared benchmarks
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Apr 2026
Performance Benchmarks
Comparative analysis across standard metrics
MiniMax M2.7 outperforms in 0 benchmarks, while Kimi K2.6 is better at 6 benchmarks (Finance Agent v2, GDPval-AA, SWE-bench Multilingual, SWE-Bench Pro, Terminal-Bench 2.0, Toolathlon).
Kimi K2.6 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, MiniMax M2.7 ($0.30/1M tokens) is 2.5x cheaper than Kimi K2.6 ($0.75/1M tokens).
For output processing, MiniMax M2.7 ($1.20/1M tokens) is 2.9x cheaper than Kimi K2.6 ($3.50/1M tokens).
In conclusion, Kimi K2.6 is more expensive than MiniMax M2.7.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Kimi K2.6 accepts 262,144 input tokens compared to MiniMax M2.7's 196,608 tokens. MiniMax M2.7 can generate longer responses up to 196,608 tokens, while Kimi K2.6 is limited to 131,072 tokens.
Input Capabilities
Supported data types and modalities
Kimi K2.6 supports multimodal inputs, whereas MiniMax M2.7 does not.
Kimi K2.6 can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiniMax M2.7
Kimi K2.6
License
Usage and distribution terms
MiniMax M2.7 is licensed under MIT, while Kimi K2.6 uses Modified MIT License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Modified MIT License
Open weights
Release Timeline
When each model was launched
MiniMax M2.7 was released on 2026-03-18, while Kimi K2.6 was released on 2026-04-20.
Kimi K2.6 is 1 month newer than MiniMax M2.7.
Mar 18, 2026
4 months ago
Apr 20, 2026
2 months ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
MiniMax M2.7 is available from Fireworks, MiniMax, Novita. Kimi K2.6 is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together.
MiniMax M2.7
Kimi K2.6
Outputs Comparison
Key Takeaways
MiniMax M2.7
View detailsMiniMax
Kimi K2.6
View detailsMoonshot AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against MiniMax M2.7 and Kimi K2.6 side-by-side, then vote on the output you prefer.
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FAQ
Common questions about MiniMax M2.7 vs Kimi K2.6.