Model Comparison
DeepSeek R1 Distill Qwen 1.5B vs Llama 4 Scout
Llama 4 Scout significantly outperforms across most benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek R1 Distill Qwen 1.5B outperforms in 0 benchmarks, while Llama 4 Scout is better at 2 benchmarks (GPQA, LiveCodeBench).
Llama 4 Scout significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Model Size
Parameter count comparison
Llama 4 Scout has 107.2B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 6023.6% larger.
Context Window
Maximum input and output token capacity
Only Llama 4 Scout specifies input context (10,000,000 tokens). Only Llama 4 Scout specifies output context (10,000,000 tokens).
Input Capabilities
Supported data types and modalities
Llama 4 Scout supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 1.5B does not.
Llama 4 Scout can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Distill Qwen 1.5B
Llama 4 Scout
License
Usage and distribution terms
DeepSeek R1 Distill Qwen 1.5B is licensed under MIT, while Llama 4 Scout uses Llama 4 Community License Agreement.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Llama 4 Community License Agreement
Open weights
Release Timeline
When each model was launched
DeepSeek R1 Distill Qwen 1.5B was released on 2025-01-20, while Llama 4 Scout was released on 2025-04-05.
Llama 4 Scout is 3 months newer than DeepSeek R1 Distill Qwen 1.5B.
Jan 20, 2025
1.3 years ago
Apr 5, 2025
1.1 years ago
2mo newerKnowledge 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
No standout differentiators in the data we have for this pair.
Detailed Comparison
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FAQ
Common questions about DeepSeek R1 Distill Qwen 1.5B vs Llama 4 Scout.