Welcome Gemma 4: Frontier Multimodal Intelligence on Device
Google has released Gemma 4, a new open-weights multimodal model family announced via the Hugging Face blog. The release positions Gemma 4 as capable of frontier-level multimodal intelligence while being deployable on-device. As a tier-2 source commentary, the post likely covers model capabilities, availability on Hugging Face Hub, and integration details.
Related guides (4)
Related events (8)
Welcome Gemma 3: Google's All-New Multimodal, Multilingual, Long-Context Open LLM
Google has released Gemma 3, a new family of open-weights large language models featuring multimodal capabilities, multilingual support, and extended context windows. The Hugging Face blog post introduces the model family and its key features. Gemma 3 represents a significant update to Google's open-weights model line, expanding beyond text-only capabilities to include vision and broader language coverage.
Gemma 3n Fully Available in the Open-Source Ecosystem
Google's Gemma 3n model has been integrated into the open-source ecosystem via Hugging Face, making it broadly accessible for developers and researchers. The announcement covers availability of the model weights and tooling support within the Hugging Face platform. Gemma 3n is designed for efficient on-device inference, targeting mobile and edge deployment scenarios. This release extends the open-weights frontier model landscape with a multimodal-capable, efficiency-focused architecture.
Google DeepMind releases Gemma 4 12B, a unified encoder-free multimodal open model
Google DeepMind has released Gemma 4 12B, a new open-weights multimodal model that uses a unified, encoder-free architecture. The model is positioned as a capable multimodal system at the 12B parameter scale. This is notable as an open-weights release from a frontier lab with an architectural distinction — eliminating the separate vision encoder common in most multimodal models.
Announcing Gemma 3n Preview: Powerful, Efficient, Mobile-First AI
Google DeepMind has released a preview of Gemma 3n, an open-weights model optimized for on-device multimodal inference. The model features a 2-in-1 architecture for flexible deployment and adds audio understanding to its multimodal capabilities. It is designed for mobile and edge environments, targeting developers building real-time interactive applications.
Welcome Gemma 2 - Google's new open LLM
Google released Gemma 2, a new open-weights large language model, announced via the Hugging Face blog. The post covers integration with the Hugging Face ecosystem and highlights the model's capabilities. Gemma 2 represents Google's continued investment in open-weight model releases to compete in the open-source LLM space.
Welcome PaliGemma 2 – New vision language models by Google
Google has released PaliGemma 2, a new family of vision-language models announced via the Hugging Face blog. The release follows the original PaliGemma and represents an updated generation of Google's open-weights multimodal models. The blog post covers model capabilities, sizes, and integration with the Hugging Face ecosystem.
Welcome Gemma - Google's new open LLM
Google released Gemma, a family of open-weight large language models, announced via the Hugging Face blog. The models are positioned as Google's entry into the open-weights LLM space, following the success of models like Llama 2. This release marks a significant strategic move by Google to compete in the open-source AI ecosystem.
Google releases Gemma 2 2B, ShieldGemma and Gemma Scope
Google released three new additions to the Gemma ecosystem: Gemma 2 2B, a small open-weights language model; ShieldGemma, a safety-focused classifier model; and Gemma Scope, an interpretability toolset. These releases expand the Gemma family with a smaller, more accessible model alongside dedicated safety and interpretability infrastructure. The announcement was published on the Hugging Face blog, indicating integration with the HF ecosystem.