unsloth/gemma-4-26B-A4B-it-qat-GGUF · Hugging Face
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AI Model Release
Summary
Google's full release of Gemma 3n, a mobile-first multimodal AI model designed for on-device deployment. The developer guide details architectural innovations like MatFormer, Per-Layer Embeddings, and KV Cache Sharing that enable 5B and 8B parameter models to run with memory footprints comparable to 2B and 4B models.
Highlights
- MatFormer architecture provides compute flexibility, while Per-Layer Embeddings (PLE) and KV Cache Sharing dramatically reduce memory footprint
- Natively multimodal: supports image, audio, video, and text inputs with text outputs
- Two model sizes (E2B and E4B) operate with as little as 2GB and 3GB of memory respectively
- Supports 140 languages for text and 35 languages for multimodal understanding
- Broad ecosystem support including Hugging Face Transformers, llama.cpp, Ollama, MLX, and Google AI Edge
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Context
Audience
Developers building on-device or edge AI applications, mobile app developers seeking multimodal capabilities, and ML engineers interested in efficient model architectures
DomainOn-Device Machine Learning
Formatdeveloper guide / technical blog post
Accessfree online, open source model weights
Topics
Related
Gemma 3MatFormerPer-Layer EmbeddingsMobileNet-V5llama.cppOllama MLX backend for on-device inference
