Desktop apps for local LLMs

A desktop app for local language models wraps everything a beginner would otherwise do by hand. It finds a model, downloads the right file for your machine, loads it into memory and gives you a chat window, so the first conversation with a model running on your own computer takes minutes instead of an evening of setup.

The apps differ mostly in what they add around the chat. Some keep things deliberately simple, with a model list and a conversation history. Others add document upload, prompt templates, split views for comparing two models, or a mix of local and hosted models in the same window. A few are web interfaces you host yourself and open in a browser, which suits a household or small office sharing one capable computer.

Many of these apps can also start a local server. That matters more than it first appears. Once a model is running behind a local API, editor extensions, note apps and your own scripts can use it too, and you only have to keep one copy of the model in memory.

Before you choose, check how the app handles model files. Some store downloads in their own folder, which can fill a small laptop drive quickly when you try several models. Others let you point at a shared folder so two apps can use the same files. Look for clear controls over context length and over how much of the model is placed on the graphics card, since those two settings decide whether a model runs smoothly or crawls.

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9 local AI tools in desktop apps for local llms

Jan

by Menlo Research

An open-source desktop chat app that runs models offline, keeps conversations as local files and can expose a local API.

  • Open source
  • Works offline after setup
  • Local API server

GPT4All

by Nomic AI

A free desktop app for running open models on ordinary laptops, with a feature for chatting with folders of local documents.

  • Open source
  • Works offline after setup
  • Local API server

Text Generation Web UI

by oobabooga

A browser-based interface for running local language models with many loaders, sampling settings and extensions.

  • Open source
  • Works offline after setup
  • Local API server

LibreChat

An open-source, self-hosted chat interface that can connect to local model servers and hosted APIs from one place.

  • Open source

LM Studio

by Element Labs

A desktop app for finding, downloading and chatting with open language models, with a built-in local server for other apps.

  • Works offline after setup
  • Local API server
  • Runs on macOS

Msty

A desktop chat app that runs local models and online ones side by side, with split chats for comparing answers.

  • Runs on macOS
  • Runs on Windows
  • Runs on Linux

Open WebUI

A self-hosted web chat interface for local model runners such as Ollama, with users, document upload and model switching.

  • Works offline after setup
  • Runs on macOS
  • Runs on Windows

Chatbox

A desktop and mobile chat client that can talk to a local Ollama server as well as hosted model APIs.

  • Runs on macOS
  • Runs on Windows
  • Runs on Linux

Pinokio

A launcher that installs and runs open-source AI apps on your computer with one click, each in its own folder.

  • Runs on macOS
  • Runs on Windows
  • Runs on Linux

Privacy settings deserve a careful read. An app that runs models locally may still check for updates, send crash reports or offer hosted models through an account. None of that is wrong, but if offline use matters to you, turn the network off and confirm the app still works the way you expect.

Updates are worth a thought too. Local model support moves quickly, and a new model family often needs a newer version of the app before it will load. Apps that update themselves keep up easily; ones you update by hand can fall behind without telling you. If a freshly downloaded model fails to load or produces garbled text, an outdated app is the first thing to check, before you blame the model or your hardware.

Finally, remember that the app and the model are separate things. The app may be open source while the model you load into it has its own license, and that license decides what you can do with the output at work. The app makes running a model easy; reading the model's terms is still up to you.

Questions about desktop apps for local llms

Which desktop app is easiest for a first try?

Pick one that installs like a normal program and offers a built-in model list, then start with a small model. Ease of use varies more with your hardware than with the app, so a small model on a modest laptop is a better first test than a large one.

Can two apps share the same downloaded models?

Sometimes. Several apps can read GGUF files from a folder you choose, and some apps connect to a runner such as Ollama instead of storing their own copies. Others keep models in a private folder, which means downloading the same model twice.

Why is a model slow in the app even though it loaded?

Usually it does not fit fully in video memory, so part of it runs on the CPU. Try a smaller quantized file, shorten the context length, or close other programs that use the graphics card. On a Mac, check that enough free RAM is left.

Do I need an account to use these apps?

Most local apps work without one for local models. An account is usually needed only for hosted models, sync or paid features. Check each app's settings if you want to be sure nothing is sent anywhere.

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