MiniMax M2.1 vs Qwen3.5-0.8B
MiniMax M2.1 leads the LLM Stats Score 31.9 to -6.2.
MiniMax · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
MiniMax M2.1 leads the overall LLM Stats Score 31.9 to -6.2, ranking #108 overall.
In the 4 individual benchmarks reported for both models, MiniMax M2.1 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 MiniMax M2.1
- overall performance matters — it scores 31.9 and ranks #108 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
Choose Qwen3.5-0.8B
- you want the most recent training data — it shipped Mar 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
25 reported for MiniMax M2.1 · 20 for Qwen3.5-0.8B
MiniMax M2.1 outperforms in 4 benchmarks (AA-LCR, GPQA, IFBench, MMLU-Pro), while Qwen3.5-0.8B is better at 0 benchmarks.
MiniMax M2.1 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
MiniMax M2.1 has 229.2B more parameters than Qwen3.5-0.8B, making it 28650.0% larger.
Context Window
Maximum input and output token capacity
Only MiniMax M2.1 specifies input context (1,000,000 tokens). Only MiniMax M2.1 specifies output context (1,000,000 tokens).
Input capabilities
Documented input modalities across available providers
Qwen3.5-0.8B supports multimodal inputs, whereas MiniMax M2.1 does not.
Qwen3.5-0.8B can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiniMax M2.1
Qwen3.5-0.8B
License
Usage and distribution terms
MiniMax M2.1 is licensed under MIT, while Qwen3.5-0.8B 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
MiniMax M2.1 was released on 2025-12-23, while Qwen3.5-0.8B was released on 2026-03-02.
Qwen3.5-0.8B is 2 months newer than MiniMax M2.1.
Dec 23, 2025
8 months ago
Mar 2, 2026
6 months ago
2mo 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 MiniMax M2.1 and Qwen3.5-0.8B side-by-side, then vote on the output you prefer.
FAQ
Common questions about MiniMax M2.1 vs Qwen3.5-0.8B.