Model Comparison
Mistral Medium 3.5 vs MiMo-V2-OmniWhich is better in 2026?
Both models are evenly matched across the benchmarks. MiMo-V2-Omni is 3.8x cheaper per token.
Verdict: Mistral Medium 3.5 vs MiMo-V2-Omni — which is better?
Mistral Medium 3.5 (by Mistral AI) and MiMo-V2-Omni (by Xiaomi) 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.
Mistral Medium 3.5 outperforms in 1 benchmarks (SWE-Bench Verified), while MiMo-V2-Omni is better at 1 benchmark (GDPval-AA). Both models are evenly matched across the benchmarks.
On price, MiMo-V2-Omni is roughly 3.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2-Omni also accepts a larger context window (262,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose Mistral Medium 3.5 if…
- you want the most recent training data — it shipped Apr 2026
- you need open weights you can self-host or fine-tune
Choose MiMo-V2-Omni if…
- cost matters — it's about 3.8x cheaper per token
- you process long inputs — it offers a 262,000 token context window
Performance Benchmarks
Comparative analysis across standard metrics
Mistral Medium 3.5 outperforms in 1 benchmarks (SWE-Bench Verified), while MiMo-V2-Omni is better at 1 benchmark (GDPval-AA).
Both models are evenly matched across the benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Mistral Medium 3.5 ($1.50/1M tokens) is 3.8x more expensive than MiMo-V2-Omni ($0.40/1M tokens).
For output processing, Mistral Medium 3.5 ($7.50/1M tokens) is 3.8x more expensive than MiMo-V2-Omni ($2.00/1M tokens).
In conclusion, Mistral Medium 3.5 is more expensive than MiMo-V2-Omni.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
MiMo-V2-Omni accepts 262,000 input tokens compared to Mistral Medium 3.5's 256,000 tokens. Mistral Medium 3.5 can generate longer responses up to 256,000 tokens, while MiMo-V2-Omni is limited to 16,384 tokens.
Input Capabilities
Supported data types and modalities
Both Mistral Medium 3.5 and MiMo-V2-Omni support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Mistral Medium 3.5
MiMo-V2-Omni
License
Usage and distribution terms
Mistral Medium 3.5 is licensed under Modified MIT License, while MiMo-V2-Omni uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Modified MIT License
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Mistral Medium 3.5 was released on 2026-04-29, while MiMo-V2-Omni was released on 2026-03-18.
Mistral Medium 3.5 is 1 month newer than MiMo-V2-Omni.
Apr 29, 2026
2 months ago
1mo newerMar 18, 2026
4 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
Mistral Medium 3.5 is available from Mistral AI. MiMo-V2-Omni is available from Xiaomi.
Mistral Medium 3.5
MiMo-V2-Omni
Outputs Comparison
Key Takeaways
Mistral Medium 3.5
View detailsMistral AI
MiMo-V2-Omni
View detailsXiaomi
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Mistral Medium 3.5 and MiMo-V2-Omni side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Mistral Medium 3.5 vs MiMo-V2-Omni.