Setup gemma-4-26B-A4B-it-qat-GGUF with 1M Context 2026/2027 Tutorial

The fastest way to get this model running locally is via Docker.

Simply follow the directions outlined below.

Just proceed with the basic instructions provided below to complete the process.

🔐 Hash sum: 595ef3a88e4ba9643233db514e83b9d2 | 📅 Last update: 2026-06-23 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: at least 32 GB in dual-channel mode for bandwidth Disk Space: required: fast PCIe 4.0 drive for instant boots Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

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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