MiniMax M2 vs Qwen3 VL 4B Instruct
MiniMax M2 significantly outperforms across most benchmarks. Qwen3 VL 4B Instruct is 2.3x cheaper per token.
MiniMax · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
MiniMax M2 outperforms in 2 benchmarks (AIME 2025, MMLU-Pro), while Qwen3 VL 4B Instruct is better at 0 benchmarks. MiniMax M2 significantly outperforms across most benchmarks.
On price, Qwen3 VL 4B Instruct is roughly 2.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiniMax M2 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
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Oct 2025
Choose Qwen3 VL 4B Instruct
- cost matters — it's about 2.3x cheaper per token
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
MiniMax M2 outperforms in 2 benchmarks (AIME 2025, MMLU-Pro), while Qwen3 VL 4B Instruct is better at 0 benchmarks.
MiniMax M2 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 ($0.30/1M tokens) is 3.0x more expensive than Qwen3 VL 4B Instruct ($0.10/1M tokens).
For output processing, MiniMax M2 ($1.20/1M tokens) is 2.0x more expensive than Qwen3 VL 4B Instruct ($0.60/1M tokens).
In conclusion, MiniMax M2 is more expensive than Qwen3 VL 4B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiniMax M2 has 226.0B more parameters than Qwen3 VL 4B Instruct, making it 5650.0% larger.
Context Window
Maximum input and output token capacity
MiniMax M2 accepts 1,000,000 input tokens compared to Qwen3 VL 4B Instruct's 262,144 tokens. MiniMax M2 can generate longer responses up to 1,000,000 tokens, while Qwen3 VL 4B Instruct is limited to 262,144 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 4B Instruct supports multimodal inputs, whereas MiniMax M2 does not.
Qwen3 VL 4B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiniMax M2
Qwen3 VL 4B Instruct
License
Usage and distribution terms
MiniMax M2 is licensed under MIT, while Qwen3 VL 4B 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 was released on 2025-10-27, while Qwen3 VL 4B Instruct was released on 2025-09-22.
MiniMax M2 is 1 month newer than Qwen3 VL 4B Instruct.
Oct 27, 2025
10 months ago
1mo 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 is available from MiniMax, Novita. Qwen3 VL 4B Instruct is available from DeepInfra.
MiniMax M2
Qwen3 VL 4B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against MiniMax M2 and Qwen3 VL 4B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about MiniMax M2 vs Qwen3 VL 4B Instruct.