gemma-4-26B-A4B-it-qat-GGUF Windows 11

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🧩 Hash sum → e42f41287298e49ecfd790572b3c3fbd — Update date: 2026-06-25

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Processor: 4.0 GHz+ boost clock recommended for CPU inference
RAM: at least 32 GB in dual-channel mode for bandwidth
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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