Initial release of DiffusionGemma, a discrete diffusion-based text generation model built on Gemma 4 26B A4B MoE architecture with encoder-decoder design for parallel token generation.
Google releases DiffusionGemma 26B as open-weight model under Apache 2 license, bringing diffusion-based text generation to production with 500+ tokens/second inference speed.
Google has released DiffusionGemma 26B, an open-weight text generation model under Apache 2 license. The model generates over 500 tokens/second according to testing on NVIDIA's free NIM API, where it produced 2,409 tokens in 4.4 seconds.
Google DeepMind released DiffusionGemma, a 26B parameter mixture-of-experts model that generates text using discrete diffusion instead of autoregression. The model processes blocks of 256 tokens in parallel, achieving generation speeds exceeding 1100 tokens per second on H100 GPUs in low-batch settings.