Model Comparison
DeepSeek R1 Zero vs Gemma 3 4B
DeepSeek R1 Zero significantly outperforms across most benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek R1 Zero outperforms in 2 benchmarks (GPQA, LiveCodeBench), while Gemma 3 4B is better at 0 benchmarks.
DeepSeek R1 Zero significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Model Size
Parameter count comparison
DeepSeek R1 Zero has 667.0B more parameters than Gemma 3 4B, making it 16675.0% larger.
Context Window
Maximum input and output token capacity
Only Gemma 3 4B specifies input context (131,072 tokens). Only Gemma 3 4B specifies output context (131,072 tokens).
Input Capabilities
Supported data types and modalities
Gemma 3 4B supports multimodal inputs, whereas DeepSeek R1 Zero does not.
Gemma 3 4B can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Zero
Gemma 3 4B
License
Usage and distribution terms
DeepSeek R1 Zero is licensed under MIT, while Gemma 3 4B uses Gemma.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Gemma
Open weights
Release Timeline
When each model was launched
DeepSeek R1 Zero was released on 2025-01-20, while Gemma 3 4B was released on 2025-03-12.
Gemma 3 4B is 2 months newer than DeepSeek R1 Zero.
Jan 20, 2025
1.3 years ago
Mar 12, 2025
1.2 years ago
1mo newerKnowledge Cutoff
When training data ends
Gemma 3 4B has a documented knowledge cutoff of 2024-08-01, while DeepSeek R1 Zero's cutoff date is not specified.
We can confirm Gemma 3 4B's training data extends to 2024-08-01, but cannot make a direct comparison without DeepSeek R1 Zero's cutoff date.
—
Aug 2024
Outputs Comparison
Key Takeaways
DeepSeek R1 Zero
View detailsDeepSeek
Gemma 3 4B
View detailsDetailed Comparison
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FAQ
Common questions about DeepSeek R1 Zero vs Gemma 3 4B.