Install gemma-4-26B-A4B-it-qat-GGUF Using Pinokio with Native FP4

Docker offers the quickest path to setting up this model locally.

Make sure to follow the instructions below.

The loader auto-caches the model archive (several GBs included).

You don’t need to tweak anything, as the installer will automatically pick the highest performing setup for you.

📎 HASH: 8443710ecb200546dbaa4c1d54419d20 | Updated: 2026-06-22 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space: at least 100 GB for multiple local LLM variants Graphics: 12 GB VRAM minimum required for basic quantization

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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