GGUF
Industry Definition Set • Entity Resolution Path: /glossary/gguf
Quick Answer / TL;DR
A file format for quantized LLM weights developed by Georgi Gerganov, used by llama.cpp and Ollama for efficient local inference on CPU and GPU.
Key Takeaways
- File format for quantized LLM weights.
- Used by llama.cpp and Ollama.
- Supports multiple quantization levels (Q4_K_M, Q5_K_M, Q8_0, etc.).
- Enables efficient partial loading for large models.
Definitive Statement: A file format for quantized LLM weights developed by Georgi Gerganov, used by llama.cpp and Ollama for efficient local inference on CPU and GPU.
Technical Context & Protocol Usage
- Detailed Explanation
- GGUF (GPT-Generated Unified Format) is the modern format for storing quantized LLM weights. It supports multiple quantization levels, metadata, and efficient memory mapping. GGUF models can be loaded partially into memory, enabling large models to run on hardware with limited RAM. Ollama uses GGUF as its primary model format, pulling pre-quantized models from the Ollama library.
Format & Payload Metadata
Format: GGUF binary format
Latency: Optimized for fast CPU and GPU inference
Real-World Implementation Use Case
An MCP server backed by Ollama loads a Llama 3 GGUF model to provide local inference for an offline agent.
Cite This Page
MLA Style:
MCPserver.in Engineering. "GGUF." MCPserver.in Knowledge Hub, 20 July 2026, mcpserver.in/glossary/gguf.
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