Model Comparison
DeepSeek R1 Distill Qwen 1.5B vs Gemma 3 27B
Gemma 3 27B significantly outperforms across most benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek R1 Distill Qwen 1.5B outperforms in 0 benchmarks, while Gemma 3 27B is better at 2 benchmarks (GPQA, LiveCodeBench).
Gemma 3 27B 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
Gemma 3 27B has 25.2B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 1416.9% larger.
Context Window
Maximum input and output token capacity
Only Gemma 3 27B specifies input context (131,072 tokens). Only Gemma 3 27B specifies output context (131,072 tokens).
Input Capabilities
Supported data types and modalities
Gemma 3 27B supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 1.5B does not.
Gemma 3 27B can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Distill Qwen 1.5B
Gemma 3 27B
License
Usage and distribution terms
DeepSeek R1 Distill Qwen 1.5B is licensed under MIT, while Gemma 3 27B 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 Distill Qwen 1.5B was released on 2025-01-20, while Gemma 3 27B was released on 2025-03-12.
Gemma 3 27B is 2 months newer than DeepSeek R1 Distill Qwen 1.5B.
Jan 20, 2025
1.2 years ago
Mar 12, 2025
1.1 years ago
1mo 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
Gemma 3 27B
View detailsDetailed Comparison
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FAQ
Common questions about DeepSeek R1 Distill Qwen 1.5B vs Gemma 3 27B