A Gentle Guide to LLM Inference and GGUF
rseroter · x · 2026-07-20
A repost of a technical explainer on LLM inference.
The article’s core mental model is that inference is just nextToken(input, frozenWeights) repeated in a loop: you feed the prompt through a fixed set of weights, get the next token, and continue until the output is complete. It emphasizes that inference does not involve learning or changing the model weights.
It also digs into GGUF, describing it as the file format that can carry the entire model inside it, making the piece useful as a gentle introduction to how local/packaged LLMs actually run.
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