To install this model locally in the shortest time, opt for Docker.

Use the instructions provided below to complete the setup.

The installer automatically pulls the model (could be multiple GBs).

The setup file includes an intelligent feature that instantly optimizes all configurations for your hardware profile.

📘 Build Hash: 0ab67e72776cbaf77d369ea4302fad32 • 🗓 2026-06-24 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: enough space for background apps and OS overhead Disk Space: free: 80 GB on system drive for scratch space GPU: modern architecture (Ada Lovelace / Ampere minimum)

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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