MiMo-V2-Flash vs Qwen3-Next-80B-A3B-Thinking
MiMo-V2-Flash leads the LLM Stats Score 30.7 to 23.8. MiMo-V2-Flash is 3.2x cheaper per token.
Xiaomi · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
MiMo-V2-Flash leads the overall LLM Stats Score 30.7 to 23.8, ranking #117 overall.
In the 5 individual benchmarks reported for both models, MiMo-V2-Flash wins 5; this is a narrower head-to-head signal than the composite indexes.
On price, MiMo-V2-Flash is roughly 3.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2-Flash also accepts a larger context window (256,000 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-Flash
- overall performance matters — it scores 30.7 and ranks #117 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 5 of 5 exact shared results
- cost matters — it's about 3.2x cheaper per token
- you process long inputs — it offers a 256,000 token context window
- you want the most recent training data — it shipped Dec 2025
Choose Qwen3-Next-80B-A3B-Thinking
- you want predictable pricing at $0.15/M input and $1.50/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
15 reported for MiMo-V2-Flash · 23 for Qwen3-Next-80B-A3B-Thinking
MiMo-V2-Flash outperforms in 5 benchmarks (AIME 2025, Arena-Hard v2, GPQA, LiveCodeBench v6, MMLU-Pro), while Qwen3-Next-80B-A3B-Thinking is better at 0 benchmarks.
MiMo-V2-Flash significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, MiMo-V2-Flash ($0.10/1M tokens) is 1.5x cheaper than Qwen3-Next-80B-A3B-Thinking ($0.15/1M tokens).
For output processing, MiMo-V2-Flash ($0.30/1M tokens) is 5.0x cheaper than Qwen3-Next-80B-A3B-Thinking ($1.50/1M tokens).
In conclusion, Qwen3-Next-80B-A3B-Thinking is more expensive than MiMo-V2-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2-Flash has 229.0B more parameters than Qwen3-Next-80B-A3B-Thinking, making it 286.3% larger.
Context Window
Maximum input and output token capacity
MiMo-V2-Flash accepts 256,000 input tokens compared to Qwen3-Next-80B-A3B-Thinking's 65,536 tokens. Qwen3-Next-80B-A3B-Thinking can generate longer responses up to 65,536 tokens, while MiMo-V2-Flash is limited to 16,384 tokens.
License
Usage and distribution terms
MiMo-V2-Flash is licensed under MIT, while Qwen3-Next-80B-A3B-Thinking uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
MiMo-V2-Flash was released on 2025-12-16, while Qwen3-Next-80B-A3B-Thinking was released on 2025-09-10.
MiMo-V2-Flash is 3 months newer than Qwen3-Next-80B-A3B-Thinking.
Dec 16, 2025
9 months ago
3mo newerSep 10, 2025
1.0 years 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-Flash is available from Xiaomi. Qwen3-Next-80B-A3B-Thinking is available from Novita.
MiMo-V2-Flash
Qwen3-Next-80B-A3B-Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against MiMo-V2-Flash and Qwen3-Next-80B-A3B-Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about MiMo-V2-Flash vs Qwen3-Next-80B-A3B-Thinking.