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Google DeepMind unveils DiffusionGemma with parallel token refinement

Google DeepMind has released DiffusionGemma, a novel Mixture-of-Experts (MoE) model that utilizes a technique borrowed from image generation to iteratively refine blocks of tokens in parallel. This approach allows the 26 billion parameter model to activate only 4 billion parameters at a time, resulting in processing speeds exceeding 1,000 tokens per second on consumer hardware. DiffusionGemma's unique architecture and parallel processing capabilities contribute to more dynamic and creative output compared to traditional autoregressive models. AI

IMPACT Sets a new precedent for LLM inference speed and output creativity through parallel token refinement.

RANK_REASON Frontier-lab model release with system card. [lever_c_demoted from frontier_release: ic=1 ai=1.0]

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Google DeepMind unveils DiffusionGemma with parallel token refinement

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0 / 100
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Significant
Frontier-lab model release with system card. [lever_c_demoted from frontier_release: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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model release, infra
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High
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3 days old
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COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    DiffusionGemma from Google DeepMind One of the most interesting new # AI models this year is DiffusionGemma , a Mixture-of-Experts (MoE) model from Google DeepM

    DiffusionGemma from Google DeepMind One of the most interesting new # AI models this year is DiffusionGemma , a Mixture-of-Experts (MoE) model from Google DeepMind. While its architecture isn't well-supported by all engines yet, variants currently work on Ollama and LM Studio. Wh…