MiMo-V2.5-Pro vs Qwen3.8-Flash-Next
Qwen3.8-Flash-Next leads the LLM Stats Score 49.7 to 25.1.
Xiaomi · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3.8-Flash-Next leads the overall LLM Stats Score 49.7 to 25.1, ranking #15 overall.
In the 4 individual benchmarks reported for both models, Qwen3.8-Flash-Next wins 4; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose MiMo-V2.5-Pro
- you want predictable pricing at $0.43/M input and $0.87/M output
Choose Qwen3.8-Flash-Next
- overall performance matters — it scores 49.7 and ranks #15 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
31 reported for MiMo-V2.5-Pro · 22 for Qwen3.8-Flash-Next
MiMo-V2.5-Pro outperforms in 0 benchmarks, while Qwen3.8-Flash-Next is better at 4 benchmarks (GPQA, Humanity's Last Exam, LiveCodeBench v6, SWE-Bench Pro).
Qwen3.8-Flash-Next significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
MiMo-V2.5-Pro has 898.2B more parameters than Qwen3.8-Flash-Next, making it 718.6% larger.
Context Window
Maximum input and output token capacity
Only MiMo-V2.5-Pro specifies input context (1,048,576 tokens). Only MiMo-V2.5-Pro specifies output context (131,072 tokens).
Input capabilities
Documented input modalities across available providers
Qwen3.8-Flash-Next supports multimodal inputs, whereas MiMo-V2.5-Pro does not.
Qwen3.8-Flash-Next can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiMo-V2.5-Pro
Qwen3.8-Flash-Next
License
Usage and distribution terms
MiMo-V2.5-Pro is licensed under MIT, while Qwen3.8-Flash-Next uses Qwen Community License 1.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Qwen Community License 1.0
Open weights
Release Timeline
When each model was launched
MiMo-V2.5-Pro was released on 2026-04-27, while Qwen3.8-Flash-Next was released on 2026-08-26.
Qwen3.8-Flash-Next is 4 months newer than MiMo-V2.5-Pro.
Apr 27, 2026
4 months ago
Aug 26, 2026
5 days ago
4mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against MiMo-V2.5-Pro and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.
FAQ
Common questions about MiMo-V2.5-Pro vs Qwen3.8-Flash-Next.