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DeepSeek-R1 vs Gemma 3 27B
Comprehensive side-by-side LLM comparison
Gemma 3 27B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-R1, released by DeepSeek on January 20, 2025, is a large reasoning model with 671 billion total parameters (37 billion active in its MoE architecture) designed for extended chain-of-thought reasoning. It features a 128K token context window and demonstrated strong performance on mathematics, coding, and scientific reasoning benchmarks at its release. DeepSeek-R1 targets complex analytical tasks, competitive programming, and applications requiring deep deliberative reasoning under an open MIT license.
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Google DeepMind
Gemma 3 27B is a 27-billion-parameter open-weight model from Google DeepMind, released in March 2025 alongside the Gemma 3 12B as the higher-capability variant in the series, built with native vision-language support for text and image inputs across a 128K token context window. Among the Gemma 3 releases, the 27B delivered the strongest results on instruction-following and knowledge-intensive reasoning tasks, making it the preferred option for developers needing greater accuracy from a self-hostable model. Its open-weight availability under a permissive license made it a common starting point for vision-language fine-tuning projects.
1 month newer
DeepSeek-R1
DeepSeek
2025-01-20
Gemma 3 27B
Google DeepMind
2025-03-12
Performance Metrics
Context window and performance specifications
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-R1
1 providers
DeepSeek
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Gemma 3 27B
0 providers
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DeepSeek-R1
Avg Score:0.0%
Providers:1
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Gemma 3 27B
Avg Score:0.0%
Providers:0