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LM Studio vs Ollama

Two fact sheets from our own research, side by side — pricing, platforms, API access and status re-checked by us rather than quoted from the vendors.

The short answer

Entry price
The same for both — $20/mo
Free plan
Both have one
Public API
Both have one
Best fit
LM Studio: Developers testing open-weight models behind an OpenAI-compatible local endpoint · Ollama: developers prototyping against local models
Platforms
LM Studio: macOS, Windows, Linux · Ollama: macOS, Windows, Linux, Web

From our own records as of each tool's last check. Anything we have not confirmed is left out rather than guessed. How we verify

LM StudioDesktop app for downloading and running open-weight LLMs locally, now with a Bionic agent and optional US-hosted cloud models.OllamaRuns open-weight language models locally from one command, with a hosted tier for larger models

Side by side

FactLM StudioOllama
CategoryModel Hosting & InferenceModel Hosting & Inference
Pricing modelFreemiumFreemium
Starts at$20/mo$20/mo
Public APIYesYes
Trust score91 / 10093 / 100
PlatformsmacOS, Windows, Linux, APImacOS, Windows, Linux, API, Web
CompanyElement Labs, Inc.Ollama Inc.
Launched20232023
Last verifiedOct 2, 2026Sep 6, 2026

What our research says

LM Studio

The easiest graphical way to try open models on a laptop or workstation, with a built-in model browser, chat window and local API server. Bionic extends it into an agent, which is useful if you want open models to do real work, though it is newer than the core app. Teams that need centralized controls will have to wait for the organization plans that are still being rolled out.

Pros

  • Free for personal and work use with local models
  • Runs llama.cpp and MLX engines with a simple model browser
  • Local API server plus CLI and JS and Python SDKs
  • Cloud tier states zero data retention and US hosting

Cons

  • Closed-source desktop app, unlike some local-model runners
  • Large models still need a lot of memory and a good GPU or Apple Silicon
  • Bionic cloud plans are new and usage limits are described only loosely

Ollama

The simplest way to get an open-weight model answering on your own hardware, and its local API has become a default target that most agent frameworks already speak. The cloud tier is the practical escape hatch when a model will not fit in your RAM. What you do not get is fleet-scale serving: this is a single-node runtime, not an inference platform with autoscaling and usage metering.

Pros

  • One command pulls and runs a model, with no environment wrangling
  • Local HTTP API that most agent frameworks already support
  • Works fully offline once weights are downloaded
  • Cloud tier covers models too large for local hardware, in US, EU and Singapore regions
  • Runtime is open source under a permissive licence

Cons

  • Single-node runtime with no autoscaling or multi-tenant serving
  • Max tier signups were paused for capacity when checked
  • Local speed is capped by your own GPU or RAM

Which one fits

Choose LM Studio if you need

  • Developers testing open-weight models behind an OpenAI-compatible local endpoint
  • Privacy-conscious users who want chat and documents to stay on their own computer

Choose Ollama if you need

  • developers prototyping against local models
  • privacy-constrained work that cannot leave the machine
  • running an offline model behind an existing OpenAI-shaped client

LM Studio vs Ollama: the questions people ask

Is LM Studio cheaper than Ollama?

Both publish the same entry price, $20/mo. The difference is what each plan includes, which the fact table above sets side by side.

Does LM Studio or Ollama have a free tier?

Both: LM Studio has a free tier, and Ollama has a free tier.

Which has a public API, LM Studio or Ollama?

Both ship a public API, so either can be built on; the fact table above shows the platforms each one runs on.

More comparisons

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