Kimi K2 0905 vs MiMo-V2.6-Pro
MiMo-V2.6-Pro leads the LLM Stats Score 49.8 to 21.6. MiMo-V2.6-Pro is 2.0x cheaper per token.
Moonshot AI · Xiaomi · Updated for 2026
Which is better?
MiMo-V2.6-Pro leads the overall LLM Stats Score 49.8 to 21.6, ranking #19 overall.
On price, MiMo-V2.6-Pro is roughly 2.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2.6-Pro also accepts a larger context window (1,048,576 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 0905
- you want predictable pricing at $0.60/M input and $2.50/M output
Choose MiMo-V2.6-Pro
- overall performance matters — it scores 49.8 and ranks #19 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- cost matters — it's about 2.0x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Sep 2026
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
6 reported for Kimi K2 0905 · 18 for MiMo-V2.6-Pro
Kimi K2 0905 and MiMo-V2.6-Prodon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Kimi K2 0905 ($0.60/1M tokens) is 1.4x more expensive than MiMo-V2.6-Pro ($0.43/1M tokens).
For output processing, Kimi K2 0905 ($2.50/1M tokens) is 2.9x more expensive than MiMo-V2.6-Pro ($0.87/1M tokens).
In conclusion, Kimi K2 0905 is more expensive than MiMo-V2.6-Pro.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2.6-Pro has 20.0B more parameters than Kimi K2 0905, making it 2.0% larger.
Context Window
Maximum input and output token capacity
MiMo-V2.6-Pro accepts 1,048,576 input tokens compared to Kimi K2 0905's 262,144 tokens. Only Kimi K2 0905 specifies output context (262,144 tokens).
Input capabilities
Documented input modalities across available providers
MiMo-V2.6-Pro supports multimodal inputs, whereas Kimi K2 0905 does not.
MiMo-V2.6-Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
Kimi K2 0905
MiMo-V2.6-Pro
License
Usage and distribution terms
Kimi K2 0905 is licensed under a proprietary license, while MiMo-V2.6-Pro uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
Kimi K2 0905 was released on 2025-09-05, while MiMo-V2.6-Pro was released on 2026-09-22.
MiMo-V2.6-Pro is 13 months newer than Kimi K2 0905.
Sep 5, 2025
1.0 years ago
Sep 22, 2026
-1 days ago
1.0yr 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 0905 is available from Novita. MiMo-V2.6-Pro is available from Xiaomi.
Kimi K2 0905
MiMo-V2.6-Pro
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2 0905 and MiMo-V2.6-Pro side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2 0905 vs MiMo-V2.6-Pro.