Model Comparison
MiniMax M2.1 vs Qwen2.5-Omni-7B
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-Omni-7B 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 223.0B more parameters than Qwen2.5-Omni-7B, making it 3185.7% 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-Omni-7B supports multimodal inputs, whereas MiniMax M2.1 does not.
Qwen2.5-Omni-7B can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiniMax M2.1
Qwen2.5-Omni-7B
License
Usage and distribution terms
MiniMax M2.1 is licensed under MIT, while Qwen2.5-Omni-7B 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-Omni-7B was released on 2025-03-27.
MiniMax M2.1 is 9 months newer than Qwen2.5-Omni-7B.
Dec 23, 2025
3 months ago
9mo newerMar 27, 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-Omni-7B
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about MiniMax M2.1 vs Qwen2.5-Omni-7B