Comprehensive side-by-side LLM comparison
Gemini Diffusion leads with 3.0% higher average benchmark score. Gemma 3 12B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Google DeepMind
Gemini Diffusion is an experimental text and code generation model from Google DeepMind, announced at Google I/O in May 2025 as the first diffusion-based language model to achieve quality comparable to autoregressive models on standard benchmarks. Unlike transformer-based models that predict tokens sequentially left-to-right, it generates entire blocks of text by iteratively refining noise — the paradigm used in image and video generation models — enabling faster sampling speeds and stronger mid-generation error correction for code and mathematical editing tasks. At announcement it was available only as an experimental demo via waitlist, with no public API, marking it as a research milestone rather than a production deployment.
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.
2 months newer

Gemma 3 12B
Google DeepMind
2025-03-12

Gemini Diffusion
Google DeepMind
2025-05-20
Average performance across 1 common benchmarks
Gemini Diffusion
Gemma 3 12B
Performance comparison across key benchmark categories
Gemini Diffusion
Gemma 3 12B
Available providers and their performance metrics
Gemini Diffusion
Gemma 3 12B
Gemini Diffusion
Gemma 3 12B