Model Comparison
DeepSeek R1 Distill Qwen 1.5B vs Magistral Medium
Magistral Medium significantly outperforms across most benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek R1 Distill Qwen 1.5B outperforms in 0 benchmarks, while Magistral Medium is better at 3 benchmarks (AIME 2024, GPQA, LiveCodeBench).
Magistral Medium 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
Magistral Medium has 22.2B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 1248.3% larger.
Input Capabilities
Supported data types and modalities
Magistral Medium supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 1.5B does not.
Magistral Medium can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Distill Qwen 1.5B
Magistral Medium
License
Usage and distribution terms
DeepSeek R1 Distill Qwen 1.5B is licensed under MIT, while Magistral Medium 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
DeepSeek R1 Distill Qwen 1.5B was released on 2025-01-20, while Magistral Medium was released on 2025-06-10.
Magistral Medium is 5 months newer than DeepSeek R1 Distill Qwen 1.5B.
Jan 20, 2025
1.3 years ago
Jun 10, 2025
10 months ago
4mo newerKnowledge Cutoff
When training data ends
Magistral Medium has a documented knowledge cutoff of 2025-06-01, while DeepSeek R1 Distill Qwen 1.5B'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 DeepSeek R1 Distill Qwen 1.5B's cutoff date.
—
Jun 2025
Outputs Comparison
Key Takeaways
Magistral Medium
View detailsMistral AI
Detailed Comparison
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FAQ
Common questions about DeepSeek R1 Distill Qwen 1.5B vs Magistral Medium