Model Comparison
Magistral Medium vs Qwen3 VL 4B Thinking
Both models are evenly matched across the benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
Magistral Medium outperforms in 1 benchmarks (GPQA), while Qwen3 VL 4B Thinking is better at 1 benchmark (AIME 2025).
Both models are evenly matched across the benchmarks.
Arena Performance
Human preference votes
Model Size
Parameter count comparison
Magistral Medium has 20.0B more parameters than Qwen3 VL 4B Thinking, making it 500.0% larger.
Context Window
Maximum input and output token capacity
Only Qwen3 VL 4B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 4B Thinking specifies output context (262,144 tokens).
Input Capabilities
Supported data types and modalities
Both Magistral Medium and Qwen3 VL 4B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Magistral Medium
Qwen3 VL 4B Thinking
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Magistral Medium was released on 2025-06-10, while Qwen3 VL 4B Thinking was released on 2025-09-22.
Qwen3 VL 4B Thinking is 3 months newer than Magistral Medium.
Jun 10, 2025
11 months ago
Sep 22, 2025
7 months ago
3mo newerKnowledge Cutoff
When training data ends
Magistral Medium has a documented knowledge cutoff of 2025-06-01, while Qwen3 VL 4B Thinking's cutoff date is not specified.
We can confirm Magistral Medium's training data extends to 2025-06-01, but cannot make a direct comparison without Qwen3 VL 4B Thinking's cutoff date.
Jun 2025
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Outputs Comparison
Key Takeaways
Magistral Medium
View detailsMistral AI
Qwen3 VL 4B Thinking
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about Magistral Medium vs Qwen3 VL 4B Thinking.