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DeepSeek R1 Distill Qwen 1.5B vs Gemma 3 4B
Comprehensive side-by-side LLM comparison
DeepSeek R1 Distill Qwen 1.5B leads with 3.7% higher average benchmark score. Gemma 3 4B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-R1-Distill-Qwen-1.5B was created through distillation into an ultra-compact Qwen architecture, designed to enable reasoning capabilities on resource-constrained devices. Built with just 1.5 billion parameters, it brings advanced analytical techniques to edge computing and mobile scenarios.
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Gemma 3 4B was developed as a compact yet capable open-source model, designed to strike a balance between performance and resource efficiency. Built with 4 billion parameters and instruction tuning, it provides a practical option for applications requiring moderate capability with manageable computational costs.
1 month newer
DeepSeek R1 Distill Qwen 1.5B
DeepSeek
2025-01-20
Gemma 3 4B
2025-03-12
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Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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DeepSeek R1 Distill Qwen 1.5B
Average Score:25.4%(+3.7%)
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Gemma 3 4B
Average Score:21.7%
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Knowledge Cutoff
Training data recency comparison
Gemma 3 4B
2024-08-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek R1 Distill Qwen 1.5B
0 providers
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Gemma 3 4B
1 providers
DeepInfra
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DeepSeek R1 Distill Qwen 1.5B
Avg Score:25.4%(+3.7%)
Providers:0
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Gemma 3 4B
Avg Score:21.7%
Providers:1