Google's new open model DiffusionGemma generates text from noise instead of word by word
Google releases DiffusionGemma, a 26B-parameter diffusion-based text model that generates roughly 1,000 tokens per second on a single H100, about four times faster than comparable autoregressive models.
Google released DiffusionGemma, a 26-billion-parameter model that generates text not token by token but through diffusion, similar to how image AI turns noise into a picture. According to Nvidia, it hits about 1,000 tokens per second on a single H100 GPU, roughly four times faster than comparable autoregressive models.
The speed comes at a cost, though. Output quality is lower, so Google is positioning it as an experimental tool for developers for now. The article Google's new open model DiffusionGemma generates text from noise instead of word by word appeared first on The Decoder.
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