Run gemma-4-26B-A4B-it-qat-GGUF Windows 11 For Low VRAM (6GB/8GB)

par | Juin 28, 2026 | Embedders

Run gemma-4-26B-A4B-it-qat-GGUF Windows 11 For Low VRAM (6GB/8GB)

If you want the fastest local installation for this model, use Docker.

Please follow the instructions listed below to get started.

Upon successful execution, you will fully enjoy everything you expected to achieve with this model.

📎 HASH: 2ae95a5210aec8ef9cb924ec3cd05f6b | Updated: 2026-06-23
  • CPU: multi-threading optimized for fast prompt processing
  • RAM: 48 GB needed to prevent memory swapping to disk
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

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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