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llmfit

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A terminal tool that detects your hardware and right-sizes hundreds of LLM models to your RAM, CPU, and GPU. One command to find what runs on your machine. Supports multi-GPU, MoE architectures, and local providers. More practical than running benchmarks manually.

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Download Download Version

v1.1.6 · 6.1 MB

Scans your hardware and tells you which LLMs will run well — no downloading, no guessing.

Core Features

  • Auto-detects RAM, VRAM, CPU, and GPU backends — no manual configuration needed
  • Scores hundreds of models on fit, speed, quality, and context
  • Correctly handles MoE models (e.g., Mixtral, DeepSeek-V3) unlike alternatives that treat them as dense
  • Interactive TUI (default) plus classic CLI mode for scripting and automation
  • Built-in benchmark to measure real tok/s and contribute results back to the community

What It Can't Do

  • Speed estimates are based on a memory‑bandwidth model; real performance may vary due to system load. Use `llmfit bench` for actual numbers.
  • The model catalog is built-in; see custom-models docs to add models not in the database.
  • The TUI may require a modern terminal emulator (e.g., kitty) for full rendering.

Use Cases

  • Quickly find the best LLM for your laptop or desktop without downloading models blindly
  • Automate model selection in CI/CD pipelines or agent workflows using JSON output

Detailed Introduction

llmfit is a cross-platform terminal utility that solves the common pain point of figuring out which large language models can actually run on your local hardware. It scans your system (RAM, VRAM, CPU, GPU backends) and scores every model from its extensive catalog across four dimensions: memory fit, estimated speed, quality, and context length. Instead of guessing or downloading huge models only to find they won't load, you get an instant ranked list. It ships with a beautiful interactive TUI (default) and a CLI mode for scripting. Unique advantages: (1) it uses a memory-bandwidth model grounded in real community measurements, not just theoretical specs, so speed estimates are more accurate; (2) supports Mixture-of-Experts (MoE) models correctly, unlike alternatives like llm-checker which treat MoE as dense. llmfit also lets you benchmark real tok/s on your machine and share results back to the project via a PR, improving estimates for everyone.

Tags

LLMmodel selectionhardware compatibilityAI toolterminalbenchmarking

Getting Started

1

Download installer

Click the button above to download the installer for your system

2

Install the software

Double-click the downloaded installer and follow the prompts

3

Install: `scoop install llmfit` (Windows), `brew install AlexsJones/llmfit/llmfit` (macOS/Linux), or curl script

4

Run: type `llmfit` to open the interactive TUI showing hardware info and ranked models

5

Advanced: use `llmfit bench` to measure real speed, or `llmfit recommend --json` for machine-readable output

Install Guide
  1. Install: `scoop install llmfit` (Windows), `brew install AlexsJones/llmfit/llmfit` (macOS/Linux), or curl script
  2. Run: type `llmfit` to open the interactive TUI showing hardware info and ranked models
  3. Advanced: use `llmfit bench` to measure real speed, or `llmfit recommend --json` for machine-readable output
File Integrity

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SHA256 Checksum

1e09232a128455596a2d348ab5893741d04b94aa6d924f1253462dc13304f7c6

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Open Source Transparency

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Environment Guide

Uninstall Info

Uninstall depends on method: `scoop uninstall llmfit`, `brew uninstall llmfit`, or delete the binary and `~/.local/bin/llmfit` if installed manually.

No Extra Dependencies

Ready to use after download. No additional runtime required.

Project Info
LicenseMIT
Last Updated2026-07-22T05:25:24Z
GitHub RepositoryOfficial Website

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