Google's new open model DiffusionGemma generates text from noise instead of word by word

In three linesGoogle releases DiffusionGemma, a 26B-parameter model generating text via diffusion (noise → text) rather than token-by-token. Achieves ~1,000 tokens/sec on H100 (4× faster than comparable autoregressive models), but lower output quality. Positioned as experimental tool for developers.

Summary generated by Claude — human-verified