PulseAugur
EN
LIVE 09:23:52

DiffusionGemma language model achieves 1,500 tokens/sec speed

Researchers have introduced DiffusionGemma, an experimental open-weight language model designed for high-speed text generation. Unlike traditional autoregressive models that process tokens sequentially, DiffusionGemma refines blocks of 256 tokens in parallel using discrete diffusion. This model is derived from the Gemma 4 mixture-of-experts model and achieves approximately 1,500 output tokens per second on a single NVIDIA H100 GPU, significantly outperforming conventional methods. AI

IMPACT Establishes a new Pareto frontier for generation speed and model capability, potentially accelerating AI applications requiring rapid text output.

RANK_REASON Publication of a technical report detailing a new experimental language model on arXiv.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

DiffusionGemma language model achieves 1,500 tokens/sec speed

COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · DiffusionGemma Team, Adrien Ali Ta\"iga, James Assiene, Daniele Calandriello, Rahma Chaabouni, Jo\~ao Gante, Tamara von Glehn, Nate Keating, Chris Knutsen, Martin Kukla, Tianlin Liu, Ivan Lobov, Ofir Nabati, Jo\~ao Gabriel Oliveira, Nicolas Perez-Nieves,… ·

    DiffusionGemma Technical Report

    arXiv:2608.00146v1 Announce Type: new Abstract: We introduce DiffusionGemma, an experimental open-weight language model that uses discrete diffusion to generate text at exceptionally high speed. Rather than decoding one token at a time, DiffusionGemma iteratively refines blocks o…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    DiffusionGemma Technical Report

    We introduce DiffusionGemma, an experimental open-weight language model that uses discrete diffusion to generate text at exceptionally high speed. Rather than decoding one token at a time, DiffusionGemma iteratively refines blocks of 256 tokens in parallel, avoiding the sequentia…