Launch gemma-4-26B-A4B-it-qat-GGUF Quantized GGUF Local Guide

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

Refer to the instructions below to proceed.

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🔐 Hash sum: ab84fd15c89b5cd1985ebf48ec6c53c7 | 📅 Last update: 2026-06-24 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: 64 GB to avoid OOM crashes on large contexts 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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