MiniMax M2.1 vs Qwen3 VL 30B A3B Thinking
MiniMax M2.1 leads the LLM Stats Score 31.9 to 18.3. Qwen3 VL 30B A3B Thinking is 1.3x cheaper per token.
MiniMax · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
MiniMax M2.1 leads the overall LLM Stats Score 31.9 to 18.3, ranking #110 overall.
In the 3 individual benchmarks reported for both models, MiniMax M2.1 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3 VL 30B A3B Thinking is roughly 1.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiniMax M2.1 also accepts a larger context window (1,000,000 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 MiniMax M2.1
- overall performance matters — it scores 31.9 and ranks #110 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Dec 2025
Choose Qwen3 VL 30B A3B Thinking
- cost matters — it's about 1.3x cheaper per token
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 · 50 for Qwen3 VL 30B A3B Thinking
MiniMax M2.1 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Qwen3 VL 30B A3B Thinking is better at 1 benchmark (AIME 2025).
MiniMax M2.1 shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, MiniMax M2.1 ($0.30/1M tokens) is 1.5x more expensive than Qwen3 VL 30B A3B Thinking ($0.20/1M tokens).
For output processing, MiniMax M2.1 ($1.20/1M tokens) is 1.2x more expensive than Qwen3 VL 30B A3B Thinking ($0.99/1M tokens).
In conclusion, MiniMax M2.1 is more expensive than Qwen3 VL 30B A3B Thinking.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiniMax M2.1 has 199.0B more parameters than Qwen3 VL 30B A3B Thinking, making it 641.9% larger.
Context Window
Maximum input and output token capacity
MiniMax M2.1 accepts 1,000,000 input tokens compared to Qwen3 VL 30B A3B Thinking's 131,072 tokens. MiniMax M2.1 can generate longer responses up to 1,000,000 tokens, while Qwen3 VL 30B A3B Thinking is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Qwen3 VL 30B A3B Thinking supports multimodal inputs, whereas MiniMax M2.1 does not.
Qwen3 VL 30B A3B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiniMax M2.1
Qwen3 VL 30B A3B Thinking
License
Usage and distribution terms
MiniMax M2.1 is licensed under MIT, while Qwen3 VL 30B 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
MiniMax M2.1 was released on 2025-12-23, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.
MiniMax M2.1 is 3 months newer than Qwen3 VL 30B A3B Thinking.
Dec 23, 2025
9 months ago
3mo newerSep 22, 2025
12 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
MiniMax M2.1 is available from MiniMax. Qwen3 VL 30B A3B Thinking is available from Novita, DeepInfra.
MiniMax M2.1
Qwen3 VL 30B A3B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against MiniMax M2.1 and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about MiniMax M2.1 vs Qwen3 VL 30B A3B Thinking.