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DeepSeek R1 Zero vs Gemma 3 4B
Comprehensive side-by-side LLM comparison
Gemma 3 4B leads with 38.3% higher average benchmark score. Gemma 3 4B supports multimodal inputs. Overall, Gemma 3 4B is the stronger choice for coding tasks.
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DeepSeek
DeepSeek R1 Zero is a language model developed by DeepSeek. It achieves strong performance with an average score of 76.5% across 4 benchmarks. It excels particularly in MATH-500 (95.9%), AIME 2024 (86.7%), GPQA (73.3%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.
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Gemma 3 4B is a multimodal language model developed by Google. The model shows competitive results across 26 benchmarks. It excels particularly in IFEval (90.2%), GSM8k (89.2%), DocVQA (75.8%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Google's latest advancement in AI technology.
1 month newer
DeepSeek R1 Zero
DeepSeek
2025-01-20
Gemma 3 4B
2025-03-12
Performance Metrics
Context window and performance specifications
Average performance across 28 common benchmarks
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DeepSeek R1 Zero
Average Score:10.9%
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Gemma 3 4B
Average Score:49.2%(+38.3%)
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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 Zero
0 providers
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Gemma 3 4B
1 providers
DeepInfra
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DeepSeek R1 Zero
Avg Score:10.9%
Providers:0
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Gemma 3 4B
Avg Score:49.2%(+38.3%)
Providers:1