Model Comparison
Qwen3.7 Max vs MiMo-V2.5Which is better in 2026?
Qwen3.7 Max significantly outperforms across most benchmarks. MiMo-V2.5 is 8.9x cheaper per token.
Verdict: Qwen3.7 Max vs MiMo-V2.5 — which is better?
Qwen3.7 Max (by Alibaba Cloud / Qwen Team) and MiMo-V2.5 (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.
Qwen3.7 Max outperforms in 4 benchmarks (Claw-Eval, Finance Agent v2, SWE-Bench Pro, Terminal-Bench 2.0), while MiMo-V2.5 is better at 0 benchmarks. Qwen3.7 Max significantly outperforms across most benchmarks.
On price, MiMo-V2.5 is roughly 8.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2.5 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose Qwen3.7 Max if…
- you want the strongest raw capability — it leads on 4 of 4 shared benchmarks
- you want the most recent training data — it shipped May 2026
Choose MiMo-V2.5 if…
- cost matters — it's about 8.9x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
Qwen3.7 Max outperforms in 4 benchmarks (Claw-Eval, Finance Agent v2, SWE-Bench Pro, Terminal-Bench 2.0), while MiMo-V2.5 is better at 0 benchmarks.
Qwen3.7 Max significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Qwen3.7 Max ($1.25/1M tokens) is 7.4x more expensive than MiMo-V2.5 ($0.17/1M tokens).
For output processing, Qwen3.7 Max ($3.75/1M tokens) is 11.2x more expensive than MiMo-V2.5 ($0.34/1M tokens).
In conclusion, Qwen3.7 Max is more expensive than MiMo-V2.5.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
MiMo-V2.5 accepts 1,048,576 input tokens compared to Qwen3.7 Max's 1,000,000 tokens. MiMo-V2.5 can generate longer responses up to 131,072 tokens, while Qwen3.7 Max is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
MiMo-V2.5 supports multimodal inputs, whereas Qwen3.7 Max does not.
MiMo-V2.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Qwen3.7 Max
MiMo-V2.5
License
Usage and distribution terms
Qwen3.7 Max is licensed under a proprietary license, while MiMo-V2.5 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
Qwen3.7 Max was released on 2026-05-19, while MiMo-V2.5 was released on 2026-04-22.
Qwen3.7 Max is 1 month newer than MiMo-V2.5.
May 19, 2026
1 months ago
3w newerApr 22, 2026
2 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
Qwen3.7 Max is available from Novita, Together. MiMo-V2.5 is available from Novita, DeepInfra.
Qwen3.7 Max
MiMo-V2.5
Outputs Comparison
Key Takeaways
Qwen3.7 Max
View detailsAlibaba Cloud / Qwen Team
MiMo-V2.5
View detailsXiaomi
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Qwen3.7 Max and MiMo-V2.5 side-by-side, then vote on the output you prefer.
| Feature | | |
|---|
FAQ
Common questions about Qwen3.7 Max vs MiMo-V2.5.