DiffusionGemma 26B-A4B
DiffusionGemma 26B-A4B is Google DeepMind's experimental open-weights text diffusion model based on the Gemma 4 26B-A4B Mixture-of-Experts architecture. It uses discrete diffusion to denoise 256-token canvases in parallel, targeting low-latency local and low-concurrency generation workloads with up to 4x faster text generation on dedicated GPUs. The model has 25.2 billion total parameters, 3.8 billion active parameters, a 256K context window, and multimodal text and image inputs.