MiMo-V2.6-Pro vs Mistral Medium 3.5
MiMo-V2.6-Pro leads the LLM Stats Score 49.9 to 26.9. MiMo-V2.6-Pro is 5.5x cheaper per token.
Xiaomi · Mistral AI · Updated for 2026
Which is better?
MiMo-V2.6-Pro leads the overall LLM Stats Score 49.9 to 26.9, ranking #20 overall.
On price, MiMo-V2.6-Pro is roughly 5.5x 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 MiMo-V2.6-Pro
- overall performance matters — it scores 49.9 and ranks #20 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- cost matters — it's about 5.5x 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
Choose Mistral Medium 3.5
- you want predictable pricing at $1.50/M input and $7.50/M output
At a glance
The differences that matter most.
Individual benchmarks
18 reported for MiMo-V2.6-Pro · 11 for Mistral Medium 3.5
MiMo-V2.6-Pro and Mistral Medium 3.5don'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, MiMo-V2.6-Pro ($0.43/1M tokens) is 3.4x cheaper than Mistral Medium 3.5 ($1.50/1M tokens).
For output processing, MiMo-V2.6-Pro ($0.87/1M tokens) is 8.6x cheaper than Mistral Medium 3.5 ($7.50/1M tokens).
In conclusion, Mistral Medium 3.5 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 892.0B more parameters than Mistral Medium 3.5, making it 696.9% larger.
Context Window
Maximum input and output token capacity
MiMo-V2.6-Pro accepts 1,048,576 input tokens compared to Mistral Medium 3.5's 256,000 tokens. Only Mistral Medium 3.5 specifies output context (256,000 tokens).
Input capabilities
Documented input modalities across available providers
Both MiMo-V2.6-Pro and Mistral Medium 3.5 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
MiMo-V2.6-Pro
Mistral Medium 3.5
License
Usage and distribution terms
MiMo-V2.6-Pro is licensed under MIT, while Mistral Medium 3.5 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
MiMo-V2.6-Pro was released on 2026-09-22, while Mistral Medium 3.5 was released on 2026-04-29.
MiMo-V2.6-Pro is 5 months newer than Mistral Medium 3.5.
Sep 22, 2026
1 weeks ago
4mo newerApr 29, 2026
5 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
MiMo-V2.6-Pro is available from Xiaomi. Mistral Medium 3.5 is available from Mistral AI.
MiMo-V2.6-Pro
Mistral Medium 3.5
Outputs Comparison
Judge for yourself.
Run your own prompts against MiMo-V2.6-Pro and Mistral Medium 3.5 side-by-side, then vote on the output you prefer.
FAQ
Common questions about MiMo-V2.6-Pro vs Mistral Medium 3.5.