Install gemma-4-26B-A4B-it-qat-GGUF Locally via Ollama 2

June 28, 2026 · admin

Install gemma-4-26B-A4B-it-qat-GGUF Locally via Ollama 2

The most rapid route to a local installation of this model is through Docker.

Make sure to follow the instructions below.

To guarantee smooth performance, the installation process auto-selects the best possible options for your PC.

🔐 Hash sum: 7354c82f5d7311d33dfd9f55d1057c9e | 📅 Last update: 2026-06-26



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: enough space for background apps and OS overhead
  • Disk Space: at least 100 GB for multiple local LLM variants
  • 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.

Parameters 26 B
Context Length 8K tokens
Quantization QAT (GGUF)
Architecture Gemma‑4
Primary Use Text generation, code, QA
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