Local Model RuntimeBeginner

LM Studio

LM StudiomacOS · Windows · Linux

GUI to download, manage, and run local models; supports GGUF and MLX

Go to official site Compare with Ollama

Good for

Local models without touching a terminal
MLX acceleration on Apple Silicon
Comparing real performance across quantisations

Not for

Production services shared by many users (use a vLLM-class server instead)

We deliberately put “not for” on the same screen — a review that only lists strengths carries no information.

Pricing

FreemiumFree tier

Free for personal use; commercial use requires a licence. See the official site for current terms.

Amounts not yet manually verified. The above is a qualitative description of the billing model — defer to the official site for numbers.

Official pricing page

Junze editorial rating

Capability: 33/5
Ease of use: 55/5
Cost value: 44/5
Privacy control: 55/5

Editorial opinion, not an aggregated user rating. Data last verified: 2026-09-29.

What you can finish with LM Studio

Each scenario is a full recipe: pain point → tool stack → steps → outcome.

Run an LLM Locally: A Privacy Setup Where Data Never Leaves the Machine
Sensitive data cannot go to a cloud API, yet you still need AI to process it — a seeming dead end.
A local model running in 2 hours6 steps

Our articles about LM Studio

Tools it is often compared with

Alternatives

Ollama

4.8/5

Run open models locally with one command, exposing an OpenAI-compatible API

Local Model RuntimeBeginner

Open sourceFree tierPrice verified 2026-09-29

Entirely free and open source; your only cost is hardware and electricity.

Good for

Privacy settings where data cannot leave the network
Driving token cost to zero at high call volume
Offline or unreliable-network environments

4 site articles1 scenariosOfficial site View tool

vLLM

開源社群（源於 UC Berkeley）

4.3/5

High-throughput LLM inference server — the default choice for self-hosted production

Local Model RuntimeAdvanced

Open sourceFree tierPrice verified 2026-09-29

Open source and free (Apache-2.0); cost is GPU hardware or cloud rental. This site publishes deployment tests and performance numbers.

Good for

Self-hosted inference shared by many users
Continuous batching to maximise GPU utilisation
An OpenAI-compatible endpoint for existing code

4 site articles2 scenariosOfficial site View tool

Jan

開源社群

4.5/5

Open-source desktop app for local LLMs, emphasising offline use and privacy

Local Model RuntimeBeginner

Open sourceFree tierSee official pricing

Entirely free and open source; your only cost is hardware.

Good for

Fully offline, data never leaves the machine
Preferring open source you can inspect
Wanting a simple desktop interface

Official site View tool

Learning tracks that include this tool

This page is an editorial summary, not an official page. Trademarks and product names belong to their respective owners. If anything here is wrong or out of date, tell us and we will correct it. Last verified: 2026-09-29.