gemma-4-26B-A4B-it-qat-GGUF Locally via LM Studio Direct EXE Setup

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🔒 Hash checksum: 97d74a1ed4b696b569c6efa8697fd86b • 📆 Last updated: 2026-06-29

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CPU: 8-core / 16-thread recommended for orchestration
RAM: minimum 16 GB for stable 8B model loading
Disk Space: 80 GB NVMe SSD required for fast model weights loading
GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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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gemma-4-26B-A4B-it-qat-GGUF Locally via LM Studio Direct EXE Setup

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