DeepSeek R1 Distill Qwen 14B vs Gemma 3 27B Comparison
Comparing DeepSeek R1 Distill Qwen 14B and Gemma 3 27B across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek R1 Distill Qwen 14B outperforms in 2 benchmarks (GPQA, LiveCodeBench), while Gemma 3 27B is better at 0 benchmarks.
DeepSeek R1 Distill Qwen 14B 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 12.2B more parameters than DeepSeek R1 Distill Qwen 14B, making it 82.4% 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 14B 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 14B
Gemma 3 27B
License
Usage and distribution terms
DeepSeek R1 Distill Qwen 14B 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 14B 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 14B.
Jan 20, 2025
1.1 years ago
Mar 12, 2025
1.0 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
| Feature | | |
|---|