Quick Run gemma-4-26B-A4B-it-qat-GGUF Offline on PC No Python Required

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

Refer to the instructions below to proceed.

The setup auto-streams the model assets (expect a multi-GB download).

The installer will automatically analyze your hardware and select the optimal configuration for your system.

📎 HASH: 3813a9918b74b3dd9bb7f50d73ccfc19 | Updated: 2026-06-27 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: fast 5600MHz+ required to avoid memory bottlenecks Disk: 150+ GB for high-context vector database storage Graphics: CUDA Compute Capability 8.0+ required for flash-attention

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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