Model Comparison
MiMo-V2-Omni vs GLM-5.1Which is better in 2026?
MiMo-V2-Omni significantly outperforms across most benchmarks. MiMo-V2-Omni is 2.7x cheaper per token.
Verdict: MiMo-V2-Omni vs GLM-5.1 — which is better?
MiMo-V2-Omni (by Xiaomi) and GLM-5.1 (by Zhipu 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.
MiMo-V2-Omni outperforms in 1 benchmarks (GDPval-AA), while GLM-5.1 is better at 0 benchmarks. MiMo-V2-Omni significantly outperforms across most benchmarks.
On price, MiMo-V2-Omni is roughly 2.7x 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 MiMo-V2-Omni if…
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- cost matters — it's about 2.7x cheaper per token
- you process long inputs — it offers a 262,000 token context window
Choose GLM-5.1 if…
- you want the most recent training data — it shipped Apr 2026
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
MiMo-V2-Omni outperforms in 1 benchmarks (GDPval-AA), while GLM-5.1 is better at 0 benchmarks.
MiMo-V2-Omni significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, MiMo-V2-Omni ($0.40/1M tokens) is 3.5x cheaper than GLM-5.1 ($1.40/1M tokens).
For output processing, MiMo-V2-Omni ($2.00/1M tokens) is 2.2x cheaper than GLM-5.1 ($4.40/1M tokens).
In conclusion, GLM-5.1 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 GLM-5.1's 200,000 tokens. GLM-5.1 can generate longer responses up to 128,000 tokens, while MiMo-V2-Omni is limited to 16,384 tokens.
Input Capabilities
Supported data types and modalities
MiMo-V2-Omni supports multimodal inputs, whereas GLM-5.1 does not.
MiMo-V2-Omni can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiMo-V2-Omni
GLM-5.1
License
Usage and distribution terms
MiMo-V2-Omni is licensed under a proprietary license, while GLM-5.1 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
MiMo-V2-Omni was released on 2026-03-18, while GLM-5.1 was released on 2026-04-07.
GLM-5.1 is 1 month newer than MiMo-V2-Omni.
Mar 18, 2026
4 months ago
Apr 7, 2026
3 months ago
2w newerKnowledge 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-Omni is available from Xiaomi. GLM-5.1 is available from FriendliAI, ZAI.
MiMo-V2-Omni
GLM-5.1
Outputs Comparison
Key Takeaways
MiMo-V2-Omni
View detailsXiaomi
GLM-5.1
View detailsZhipu AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against MiMo-V2-Omni and GLM-5.1 side-by-side, then vote on the output you prefer.
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FAQ
Common questions about MiMo-V2-Omni vs GLM-5.1.