gemma-4-26B-A4B-it-qat-GGUF Uncensored Edition Easy Build

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🧩 Hash sum → a034ed6bd6f7a597b9b36ed3bd075a44 — Update date: 2026-06-25

CPU: multi-threading optimized for fast prompt processing
RAM: minimum 16 GB for stable 8B model loading
Disk: 150+ GB for high-context vector database storage
GPU: high memory bandwidth GPU for next-gen local AI pipeline

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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