Comprehensive side-by-side LLM comparison
Gemma 3 27B leads with 1.4% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
Google DeepMind
Gemma 3 12B is a 12-billion-parameter open-weight model from Google DeepMind, released in March 2025 as part of the Gemma 3 series designed to bring multimodal reasoning to accessible hardware. The model supports both text and image inputs across a 128K token context window, extending the vision capabilities that defined the Gemma 3 generation compared to earlier text-only Gemma releases. It became widely adopted for domain-specific fine-tuning in research and enterprise settings where full multimodal capability was needed without the infrastructure demands of larger frontier models.
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.
Launched on the same date

Gemma 3 12B
Google DeepMind
2025-03-12

Gemma 3 27B
Google DeepMind
2025-03-12
Average performance across 1 common benchmarks
Gemma 3 12B
Gemma 3 27B
Performance comparison across key benchmark categories
Gemma 3 12B
Gemma 3 27B
Available providers and their performance metrics
Gemma 3 12B
Gemma 3 27B
Gemma 3 12B
Gemma 3 27B