gemma-4-26B-A4B-it-AWQ-4bit

Version 26.05.01 Calibration STEM and Agentic Languages EN ZH HI AR RU JA KO NL FR ES Model Size 17.19 GB Contact Email Hugging Face | GitHub | Launch Blog | Documentation License : Apache 2.0 | Authors : Google DeepMind Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on small models) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context window of up to 256K tokens and maintains multilingual support in over 140 languages. Featuring both Dense and Mixture-of-Experts (MoE) architectures, Gemma 4 is well-suited for tasks like text generation, coding, and reasoning. The models are available in four distinct sizes: **E2B**, **E4B**, **26B A4B**, and **31B**. Their diverse sizes make them deployable in environments ranging from high-end phones to laptops and servers, democratizing access to state-of-the-art AI. Gemma 4 introduces key **capability and architectural advancements**: **Reasoning** – All models in the family are designed as highly capable reasoners, with configurable thinking modes. **Extended Multimodalities** – Processes Text, Image with variable aspect ratio and resolution support (all models), Video, and Audio (featured natively on the E2B and E4B models). **Diverse & Efficient Architectures** – Offers Dense and Mixture-of-Experts (MoE) variants of different sizes for scalable deployment. **Optimized for On-Device** – Smaller models are specifically designed for efficient local execution on laptops and mobile devices. **Increased Context Window** – The small models feature a 128K context window, while the medium models support 256K. **Enhanced Coding & Agentic Capabilities** – Achieves notable improvements in coding benchmarks alongside native function-calling support, powering highly capable autonomous agents. **Native System Prompt Support** – Gemma 4 introduces native