Kimi K2.6 vs MiniMax M3
Kimi K2.6 and MiniMax M3 are closely matched at 43.4 and 40.7 on the LLM Stats Score. MiniMax M3 is 3.0x cheaper per token.
Moonshot AI · MiniMax · Updated for 2026
Which is better?
Kimi K2.6 and MiniMax M3 are closely matched on the overall LLM Stats Score at 43.4 and 40.7.
In the 9 individual benchmarks reported for both models, Kimi K2.6 wins 6; this is a narrower head-to-head signal than the composite indexes.
On price, MiniMax M3 is roughly 3.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiniMax M3 also accepts a larger context window (524,288 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Kimi K2.6
- you value its reported benchmark strengths — it wins 6 of 9 exact shared results
Choose MiniMax M3
- cost matters — it's about 3.0x cheaper per token
- you process long inputs — it offers a 524,288 token context window
- you want the most recent training data — it shipped Jun 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
28 reported for Kimi K2.6 · 35 for MiniMax M3
Kimi K2.6 outperforms in 6 benchmarks (APEX-Agents, BrowseComp, Claw-Eval, LiveBench, MMMU-Pro, OSWorld-Verified), while MiniMax M3 is better at 3 benchmarks (Finance Agent v2, SWE-Bench Pro, SWE-Bench Verified).
Kimi K2.6 shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Kimi K2.6 ($0.75/1M tokens) is 2.7x more expensive than MiniMax M3 ($0.28/1M tokens).
For output processing, Kimi K2.6 ($3.50/1M tokens) is 3.2x more expensive than MiniMax M3 ($1.10/1M tokens).
In conclusion, Kimi K2.6 is more expensive than MiniMax M3.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2.6 has 572.0B more parameters than MiniMax M3, making it 133.6% larger.
Context Window
Maximum input and output token capacity
MiniMax M3 accepts 524,288 input tokens compared to Kimi K2.6's 262,144 tokens. MiniMax M3 can generate longer responses up to 524,288 tokens, while Kimi K2.6 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Both Kimi K2.6 and MiniMax M3 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Kimi K2.6
MiniMax M3
License
Usage and distribution terms
Kimi K2.6 is licensed under Modified MIT License, while MiniMax M3 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Modified MIT License
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Kimi K2.6 was released on 2026-04-20, while MiniMax M3 was released on 2026-06-01.
MiniMax M3 is 1 month newer than Kimi K2.6.
Apr 20, 2026
6 months ago
Jun 1, 2026
4 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
Kimi K2.6 is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together. MiniMax M3 is available from DeepInfra, Fireworks, MiniMax, Novita, Together.
Kimi K2.6
MiniMax M3
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2.6 and MiniMax M3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2.6 vs MiniMax M3.