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GitHub · AlexsJones/llmfit↑ +129 today

Find AI models that fit your hardware

Developed with the Rust language, llmfit scans hundreds of large language models and providers and allows you to identify those compatible with your hardware with a single command. The tool automates the process of finding models that best suit local system resources.

Updates

  • November 4, 2026: Stars 38,459 → 38,631, latest release v1.1.20 (November 3, 2026).
  • October 29, 2026: Stars 37,724 → 38,459, latest release v1.1.18 (October 28, 2026).
  • October 8, 2026: Stars 37,196 → 37,724, latest release v1.1.17 (October 8, 2026).
  • September 27, 2026: Stars 35,465 → 37,196, latest release v1.1.16 (September 19, 2026).

What you get

  • Automatically detects models compatible with your system
  • Sorts by memory, speed and quality
  • Provides easy management with interactive interface

Installation

Installation for macOS or Linux
brew install AlexsJones/llmfit/llmfit
Quick installation
curl -fsSL https://llmfit.axjns.dev/install.sh | sh

Running it

Starting the interactive interface
llmfit

If you don't write code

Paste this into your AI agent (Claude Code · Codex · Antigravity)

Analyze my system's hardware specifications and recommend the best AI models to run based on my available RAM, CPU and GPU capacity. Sort the models according to performance, memory usage and quality criteria and list the ones that suit me best.

Repository: https://github.com/AlexsJones/llmfit. Follow the official instructions in the README of this repository for setup and execution.

Before starting, check which OS we are on and if the necessary tools (e.g., Python, Node.js, Git, Docker) are installed. Install any missing ones step-by-step according to this system.

Create a new, empty folder to work in. Do not touch any files outside this folder and do not delete anything. Tell me what you are going to do in one sentence before running each command.

Tell me what I should see on the screen at the end of each step. If an error occurs, I will paste the error message to you exactly as it is, and we will fix it together.

Related dictionary terms

Who it is forIt is for users who are wondering which AI models will run efficiently on their local computer.
LicenseMIT

Links

TreScout did not build this tool · we found it in GitHub trends and wrote it up. This page describes the repository as of 2026-07-22: The star count and our text belong to that day, the repository may have changed since. Check the repository link for the current state. The introductory text was prepared with AI from the repository's own documentation, and this page was machine-translated from the Turkish original · the Turkish version prevails.