MiMo-V2-Flash vs Qwen3.6-27B
MiMo-V2-Flash and Qwen3.6-27B are closely matched at 30.7 and 35.5 on the LLM Stats Score. MiMo-V2-Flash is 6.9x cheaper per token.
Xiaomi · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
MiMo-V2-Flash and Qwen3.6-27B are closely matched on the overall LLM Stats Score at 30.7 and 35.5.
In the 8 individual benchmarks reported for both models, Qwen3.6-27B wins 7; this is a narrower head-to-head signal than the composite indexes.
On price, MiMo-V2-Flash is roughly 6.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3.6-27B also accepts a larger context window (262,144 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
- cost matters — it's about 6.9x cheaper per token
Choose Qwen3.6-27B
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 7 of 8 exact shared results
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Apr 2026
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 · 44 for Qwen3.6-27B
MiMo-V2-Flash outperforms in 1 benchmarks (SWE-bench Multilingual), while Qwen3.6-27B is better at 7 benchmarks (GPQA, HMMT 2025, Humanity's Last Exam, LiveCodeBench v6, MMLU-Pro, SWE-Bench Verified, Terminal-Bench 2.0).
Qwen3.6-27B 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 3.2x cheaper than Qwen3.6-27B ($0.32/1M tokens).
For output processing, MiMo-V2-Flash ($0.30/1M tokens) is 10.7x cheaper than Qwen3.6-27B ($3.20/1M tokens).
In conclusion, Qwen3.6-27B 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 281.2B more parameters than Qwen3.6-27B, making it 1012.3% larger.
Context Window
Maximum input and output token capacity
Qwen3.6-27B accepts 262,144 input tokens compared to MiMo-V2-Flash's 256,000 tokens. Qwen3.6-27B can generate longer responses up to 262,144 tokens, while MiMo-V2-Flash is limited to 16,384 tokens.
Input capabilities
Documented input modalities across available providers
Qwen3.6-27B supports multimodal inputs, whereas MiMo-V2-Flash does not.
Qwen3.6-27B can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiMo-V2-Flash
Qwen3.6-27B
License
Usage and distribution terms
MiMo-V2-Flash is licensed under MIT, while Qwen3.6-27B 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 Qwen3.6-27B was released on 2026-04-21.
Qwen3.6-27B is 4 months newer than MiMo-V2-Flash.
Dec 16, 2025
9 months ago
Apr 21, 2026
5 months ago
4mo 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-Flash is available from Xiaomi. Qwen3.6-27B is available from DeepInfra, Novita.
MiMo-V2-Flash
Qwen3.6-27B
Outputs Comparison
Judge for yourself.
Run your own prompts against MiMo-V2-Flash and Qwen3.6-27B side-by-side, then vote on the output you prefer.
FAQ
Common questions about MiMo-V2-Flash vs Qwen3.6-27B.