DeepSeek R1 Zero vs Gemma 3 4B Comparison
Comparing DeepSeek R1 Zero and Gemma 3 4B across benchmarks, pricing, and capabilities.
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
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
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
1.1 years ago
Mar 12, 2025
1.0 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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