Model Comparison
MiniMax M2.1 vs Qwen2.5 VL 32B Instruct
MiniMax M2.1 significantly outperforms across most benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
MiniMax M2.1 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Qwen2.5 VL 32B Instruct is better at 0 benchmarks.
MiniMax M2.1 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Model Size
Parameter count comparison
MiniMax M2.1 has 196.5B more parameters than Qwen2.5 VL 32B Instruct, making it 586.6% 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
Supported data types and modalities
Qwen2.5 VL 32B Instruct supports multimodal inputs, whereas MiniMax M2.1 does not.
Qwen2.5 VL 32B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiniMax M2.1
Qwen2.5 VL 32B Instruct
License
Usage and distribution terms
MiniMax M2.1 is licensed under MIT, while Qwen2.5 VL 32B 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 Qwen2.5 VL 32B Instruct was released on 2025-02-28.
MiniMax M2.1 is 10 months newer than Qwen2.5 VL 32B Instruct.
Dec 23, 2025
3 months ago
9mo newerFeb 28, 2025
1.1 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Key Takeaways
MiniMax M2.1
View detailsMiniMax
Qwen2.5 VL 32B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about MiniMax M2.1 vs Qwen2.5 VL 32B Instruct