MiniMax M2.1 vs Qwen3 VL 30B A3B Instruct
MiniMax M2.1 significantly outperforms across most benchmarks. Qwen3 VL 30B A3B Instruct is 1.6x cheaper per token.
MiniMax · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
MiniMax M2.1 outperforms in 3 benchmarks (AIME 2025, GPQA, MMLU-Pro), while Qwen3 VL 30B A3B Instruct is better at 0 benchmarks. MiniMax M2.1 significantly outperforms across most benchmarks.
On price, Qwen3 VL 30B A3B Instruct is roughly 1.6x 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 benchmark, pricing, and model metadata for 2026.
Choose MiniMax M2.1
- you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
- 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 Instruct
- cost matters — it's about 1.6x cheaper per token
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
MiniMax M2.1 outperforms in 3 benchmarks (AIME 2025, GPQA, MMLU-Pro), while Qwen3 VL 30B A3B Instruct is better at 0 benchmarks.
MiniMax M2.1 significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind 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 Instruct ($0.20/1M tokens).
For output processing, MiniMax M2.1 ($1.20/1M tokens) is 1.7x more expensive than Qwen3 VL 30B A3B Instruct ($0.70/1M tokens).
In conclusion, MiniMax M2.1 is more expensive than Qwen3 VL 30B A3B Instruct.*
* 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 Instruct, 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 Instruct's 131,072 tokens. MiniMax M2.1 can generate longer responses up to 1,000,000 tokens, while Qwen3 VL 30B A3B Instruct is limited to 32,768 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 30B A3B Instruct supports multimodal inputs, whereas MiniMax M2.1 does not.
Qwen3 VL 30B A3B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiniMax M2.1
Qwen3 VL 30B A3B Instruct
License
Usage and distribution terms
MiniMax M2.1 is licensed under MIT, while Qwen3 VL 30B A3B Instruct 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 Instruct was released on 2025-09-22.
MiniMax M2.1 is 3 months newer than Qwen3 VL 30B A3B Instruct.
Dec 23, 2025
8 months ago
3mo newerSep 22, 2025
11 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 Instruct is available from Novita, DeepInfra.
MiniMax M2.1
Qwen3 VL 30B A3B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against MiniMax M2.1 and Qwen3 VL 30B A3B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about MiniMax M2.1 vs Qwen3 VL 30B A3B Instruct.