LM Studio

Qwen

Alibaba's LLM family, from sub-1B models to a 2.4-trillion-parameter flagship, covering reasoning, coding, vision, and long context, mostly under Apache 2.0 open weights with a hosted API on Alibaba Cloud.

Freemium

LLM

3/5

Qwen's open-weight models, including its coding variants, run locally in LM Studio as GGUF or MLX builds and can be served through its OpenAI-compatible API.

Google Gemma

Google DeepMind's family of open-weight LLMs, from compact edge models to a 31B dense flagship and a 26B MoE, built for self-hosting, on-device use, and fine-tuning under Apache 2.0.

Open Source

LLM

3/5

Gemma's small open-weight models fit on consumer laptops, and LM Studio downloads and runs them locally with a chat interface and a local API server.

Meta Llama

Meta's open-weight LLM family, from compact 1B edge models to the Llama 4 mixture-of-experts models Scout and Maverick; download the weights and self-host, or call them through dozens of managed API providers.

Open Source

LLM

3/5

LM Studio downloads quantized Llama builds sized for the machine's memory and runs them locally through llama.cpp, or MLX on Apple Silicon.

Open WebUI

The most widely deployed self-hosted chat UI (149K+ GitHub stars), a feature-rich frontend for Ollama or any OpenAI-compatible API with RAG, RBAC, and enterprise auth — doesn't serve inference itself, just the interface to talk to whatever does.

Open Source

AI Infrastructure

3/5

Open WebUI can use LM Studio's local OpenAI-compatible server as a backend, adding a multi-user browser chat interface over models loaded in LM Studio.

Hugging Face

The largest model hub and ecosystem in AI — 2M+ models, 500K+ datasets, and 1M+ Spaces, with three distinct ways to run inference (Serverless API, dedicated Inference Endpoints, or 200+ third-party Inference Providers).

Freemium

AI Infrastructure

4/5

LM Studio's built-in model browser searches and downloads GGUF and MLX models directly from the Hugging Face Hub, and Hugging Face model pages offer LM Studio as a local app to open them in.

LiteLLM

The self-hosted, MIT-licensed counterpart to OpenRouter, 56K+ stars, an OpenAI-compatible gateway to 100+ providers you run yourself, trading zero-ops for full control over routing, spend, and data.

Open Source

AI Infrastructure

3/5

LiteLLM has an LM Studio provider, so a LiteLLM gateway can route requests to models running in LM Studio's local server alongside hosted APIs.

AnythingLLM

Self-hosted chat UI built around RAG from the ground up: MIT licensed, with per-workspace document sets and vector DB settings, plus a desktop app that skips Docker entirely.

Open Source

AI Infrastructure

3/5

AnythingLLM lists LM Studio as a built-in LLM and embedding provider, so its workspaces and RAG can run on models loaded in LM Studio's local server.

Unsloth

Open-source desktop app, web UI, and Python library for running and fine-tuning open-weight models locally. It serves models through an OpenAI-compatible API and trains them about twice as fast with roughly 70% less memory than standard pipelines.

Freemium

Data & ML Libraries

3/5

LM Studio is a polished desktop app for finding, chatting with, and serving local models; Unsloth covers the same ground and adds fine-tuning, dataset building, and export under an open-source licence. Choose LM Studio to run models, Unsloth when you also want to train them.

Ollama

The most widely used way to run open-weight LLMs locally — one command downloads and serves models like Llama, Qwen, DeepSeek, GLM, and MiniMax through an OpenAI-compatible API, with an optional paid Ollama Cloud tier for larger models than local hardware can handle.

Freemium

AI Infrastructure

5/5

LM Studio leads with a graphical app for finding, downloading, and chatting with local models; Ollama is open source and CLI- and server-first, which suits scripts and headless machines.

llama.cpp

Open-source C/C++ engine that runs GGUF language and vision models on CPUs, Apple Silicon, and consumer GPUs. Its llama-server binary serves them through an OpenAI-compatible API with a built-in web UI.

Open Source

AI Infrastructure

4/5

LM Studio is a closed-source desktop app that finds, downloads, and chats with local models and runs GGUF files on llama.cpp under the hood; llama.cpp is the open-source engine used directly from the command line or as a server. Pick LM Studio for a graphical app, llama.cpp for scripting and headless machines.

vLLM

Open-source, high-throughput inference and serving engine for large language models, exposing an OpenAI-compatible API. It is the most common way to self-host open-weight models in production on GPU and accelerator clusters.

Open Source

AI Infrastructure

3/5

vLLM serves open-weight models to many concurrent users on GPU servers; LM Studio is a desktop app for one person to download and chat with local models. They mark the production and personal ends of self-hosted inference.

Groq

Fast LLM inference on Groq's own LPU hardware: unlike aggregators such as OpenRouter, Groq runs the compute itself, with low time-to-first-token and per-token pricing among the lowest of the major providers.

Usage Based

AI Infrastructure

2/5

LM Studio runs open-weight models privately on your own computer at whatever speed the hardware allows; Groq serves them as a very fast hosted API, with no local setup but with data leaving the machine.