What are GGUF Format Model Files?

GGUF, previously GGML, is a quantization method that allows users to use the CPU to run an LLM but also offload some of its layers to the GPU for a speed up. Although using the CPU is generally slower than using a GPU for inference, it is an incredible format for those running models on CPU or Apple devices.

GGUF (GPT-Generated Unified Format) is a file format designed specifically for storing and running large language models (LLMs) for inference tasks. It offers several advantages over previous formats like GGML, making it a promising choice for efficient LLM deployment.

Key features:

  • Single-file deployment: Models are contained in a single file, simplifying distribution and loading.

  • Extensible: New features can be added to GGML-based executors without breaking compatibility with existing models.

  • mmap compatibility: Models can be efficiently loaded using memory-mapped files for fast access.

  • Optimized for inference: Designed for efficient LLM inference, particularly on CPUs and GPUs.

  • Supports quantization: Models can be quantized to reduce file size and computational requirements.

  • Metadata support: Includes model metadata for better organization and understanding.

  • Improved tokenization: Handles special tokens more effectively than GGML.

Common uses:

  • Running large language models like GPT-4, Bloom, and Megatron-Turing NLG on various hardware platforms.

  • Powering text generation, translation, question answering, and other language-related tasks.


  • Supported executors: llama.cpp, text-generation-webui, KoboldCpp, GPT4All, LM Studio, LoLLMS Web UI, Faraday.dev, llama-cpp-python, candle, and ctransformers.

  • Supported model frameworks: PyTorch (via conversion).

While we cannot provide images directly, here are examples of tools and libraries that work with GGUF files:

  • lamma.cpp: The primary GGUF executor, offering command-line and server options.

  • text-generation-webui: A popular web interface for running GGUF models.

  • KoboldCpp: A full-featured web interface with GPU acceleration.

  • GPT4All: A free, open-source local GUI with GPU support.

  • LM Studio: A user-friendly local GUI for Windows and macOS.

  • LoLLMs Web UI: A web UI with various unique features and a full model library.

  • Faraday.dev: An attractive, character-based chat GUI.

  • llama-cpp-python: A Python library for using GGUF models with GPU acceleration and LangChain support.

  • candle: A Rust ML framework focused on performance and ease of use.

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