llmfit profiles your computer's RAM, CPU, GPU VRAM, and installed runtime providers. It then ranks LLMs by fit, speed, quality, and context length to help identify models that may run well on the system.

Is llmfit free to use?

llmfit is listed as free and open source. The provided information does not state whether the project offers paid support, hosted services, or other commercial plans.

Can llmfit run language models itself?

llmfit is described as a model-fit and hardware-recommendation tool rather than an LLM runtime. It detects installed runtime providers and can expose recommendations through its API and dashboard, but users may need a compatible runtime to actually run a selected model.

What is llmfit Plan mode?

Plan mode estimates the VRAM and RAM requirements for a model you choose. This can help you assess hardware needs before trying to run that model locally.

Does llmfit have a web interface?

Yes. The llmfit serve command exposes a local REST API and web dashboard in addition to the interactive terminal interface and CLI modes.

Who should use llmfit?

llmfit is aimed at developers, local AI users, and technical teams comparing models for a specific computer. It is particularly useful for people who want terminal access, model filters, comparisons, JSON output, or hardware-aware recommendations.

Last updated: 11/3/2026Last verified: 2026-10-24

llmfit Review

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Open-source terminal tool that detects your RAM, CPU, and GPU, then scores hundreds of LLMs by fit, speed, quality, and context length to show which models actually run well on your machine.

Free

What is llmfit?

llmfit is a free, open-source terminal tool for finding language models that are likely to run well on your computer. It detects hardware such as RAM, CPU cores, and GPU VRAM, then scores hundreds of LLMs across fit, speed, quality, and context length. Users can browse recommendations through an interactive terminal interface, command-line options, or a local web dashboard.

Key Features

Detects system RAM, CPU cores, GPU VRAM, and installed runtime providers to create a hardware profile
Scores and ranks hundreds of models by hardware fit, expected speed, quality, and context length
Provides interactive TUI and CLI modes with search, filters, model comparison, and JSON output
Plan mode estimates the VRAM and RAM requirements for a selected model
llmfit serve exposes a local REST API and web dashboard
Supports scripting and automation through structured JSON output

Best For

Users who want to select local LLMs based on their available hardwareDevelopers comparing models for local coding assistants and AI development workflowsPeople evaluating GPU VRAM, system RAM, and CPU capacity before downloading a modelTechnical users who prefer terminal-based tools and command-line automationTeams or individuals building scripts around local model recommendations through JSON or a REST API

Pricing

llmfit is listed as free and open source. The provided information does not specify paid plans, usage limits, or commercial support options.

Pros & Cons

Pros

Uses the computer's detected hardware to make model recommendations more relevant
Combines fit, speed, quality, and context length rather than ranking models on a single factor
Offers both an interactive terminal interface and script-friendly CLI output
Plan mode can help estimate memory requirements before attempting to run a model
Local REST API and web dashboard options extend the tool beyond the terminal
Open-source distribution allows users to inspect and work with the project

Cons

The tool is primarily oriented toward users who are comfortable with terminals and local AI software
Scores and hardware estimates are guidance rather than a guarantee of real-world performance
Recommendations depend on the accuracy of detected hardware and installed runtime provider information
The provided information does not describe supported operating systems, runtime providers, or model update frequency
Users may still need to install and configure a separate local LLM runtime

Alternatives

Ollama

Ollama is a local LLM runtime and model management tool that can be used to download and run models from a terminal.

LM Studio

LM Studio provides a graphical desktop experience for discovering, downloading, and running local language models.

llama.cpp

llama.cpp is an open-source inference project for running compatible language models locally across a range of hardware.

Jan

Jan is a desktop application for using local AI models and can suit users who want a graphical interface for local LLM workflows.

FAQ

View all llmfit alternatives →

Details

Platform

macOSWindowsLinux

Features

Detects system RAM, CPU cores, GPU VRAM, and installed runtime providers to build a hardware profile
Scores models across fit, quality, speed, and context to rank what runs well on your machine
Interactive TUI plus CLI modes with search, filters, model comparison, and JSON output for scripting
Plan mode estimates VRAM/RAM needs for a chosen model, and llmfit serve exposes a local REST API and web dashboard

Languages

Known limitations

Licensed under MIT but provided as-is; fit and speed numbers are estimates computed from hardware specs, not real benchmarks
Model scores depend on the bundled Hugging Face model database, so very new models may be missing until the catalog updates
Runs in the terminal only (TUI/CLI/REST); there is no hosted web app, no Chinese UI, and no mobile version