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Google DeepMind has released DiffusionGemma, a new approach that claims to accelerate text generation by a factor of four compared to conventional methods. The blog post announcement provides a headline-level overview without disclosing technical architecture details, benchmark data, or specific use cases. The name suggests the method applies diffusion-model techniques to the Gemma family of language models.
Google DeepMind released Gemma 4 12B, a 12-billion-parameter open multimodal model. The model handles text and images without a separate vision encoder through a unified architecture. It is part of the Gemma family of open models. The announcement highlights the encoder-free design but provides no further performance or capability details.