GGUF

GGUF, short for GPT-Generated Unified Format, is the binary file format used by Llama.cpp and Ollama to store quantized LLM weights, metadata, and tokenizer configuration in a single self-contained file. The format succeeded the original GGML format in 2023, adding richer metadata, better forward compatibility, and support for more quantization schemes. GGUF supports quantization precisions including Q2_K, Q3_K, Q4_K_M, Q4_K_S, Q5_K_M, Q6_K, Q8_0, and full FP16/BF16, with the K-quant family offering best quality-per-bit through mixed-precision block quantization. A 70B-parameter model in Q4_K_M is roughly 42GB, runnable on a 64GB-RAM workstation; the same model in FP16 would be 140GB. The Hugging Face Hub hosts thousands of GGUF model files for popular open-source LLMs, often with multiple quantization levels per model. GGUF's metadata fields capture tokenizer configuration, chat templates, and model parameters in a self-contained way that simplifies deployment. AI governance teams document the GGUF quantization level alongside the base model for AI compliance traceability.

GGUF-quantized models through Centralpoint: Centralpoint routes generation to GGUF-quantized models served via Llama.cpp, Ollama, or other backends alongside cloud LLMs in one model-agnostic platform. The platform meters tokens per skill, keeps prompts local, and deploys chatbots through one line of JavaScript with audit-ready governance.


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