LM Studio vs Ollama: Picking the Right Tool for Local LLM Use
- Philip Moses
- Apr 24
- 3 min read
Updated: 3 days ago
As more companies start exploring large language models (LLMs), many still depend on cloud-based tools. But using LLMs locally on your own computer has several advantages. It keeps your data private, reduces wait times, and gives you better control over how the model runs.
Two popular platforms that help you run LLMs locally are LM Studio and Ollama. LM Studio offers a simple, beginner-friendly experience with a graphical interface. On the other hand, Ollama is built for developers and tech-savvy users who prefer command-line tools and want more control.
This blog breaks down the key features, benefits, and drawbacks of both platforms to help you decide which is best for your needs.
What Are LM Studio and Ollama?
Both tools let you run open-source LLMs directly on your system—no need for cloud servers. This is ideal for people or teams who want to keep sensitive data safe and avoid internet-based tools.
LM Studio: A desktop app available for Windows, macOS, and Linux. It has a visual interface (GUI), a built-in chat option, and a library to easily download different models. It’s designed for those who are new to LLMs.
Ollama: A command-line-based tool, also available for Windows, macOS, and Linux. It’s built for advanced users who are comfortable with coding and want deeper control. It also supports a REST API for building integrations with other software.
Comparing the Key Features
Feature | LM Studio | Ollama |
| Visual (GUI) | Command-Line + REST API |
| Very easy for beginners | Requires technical knowledge |
| Basic custom settings | High-level customization |
| Built-in model library | Model setup via commands |
| Runs on CPU/GPU | Runs on CPU/GPU |
| Windows, macOS, Linux | Windows, macOS, Linux |
| Basic local server use | Full REST API for integrations |
| Limited options | Extensive through Modelfiles |
| Active, growing user base | Large community with strong documentation |
LM Studio: Pros and Cons 👍 What’s Good:
Easy to use for anyone, even without technical knowledge.
Models can be found and installed directly within the app.
Built-in chat makes it quick to start using LLMs.
Great choice for students, beginners, or non-technical users.
👎 What’s Not:
Lacks deeper customization for advanced tasks.
Not suitable if you need fine-tuned control over models.
Limited API capabilities.
Ollama: Pros and Cons 👍 What’s Good:
Total control over how models run, including system and parameter settings.
REST API helps you connect the tool with your own applications or workflows.
You can build and run custom models using “Modelfiles”.
Preferred by developers, engineers, and researchers.
👎 What’s Not:
Requires comfort with command-line tools.
May be difficult to set up for non-technical users.
No built-in chat—you’ll need to create your own interface or use external tools.
When to Use Which?
🔹 Go with LM Studio if:
You’re just getting started with LLMs.
You prefer visual tools over coding.
You want a simple, ready-to-use experience.
You don’t need heavy customization.
🔹 Choose Ollama if:
You’re a developer or advanced user.
You want to connect LLMs with your own apps.
You need fine control over model behavior.
You’re okay using the terminal and writing config files.
Final Thoughts
Both LM Studio and Ollama are solid choices for using LLMs locally, but they serve different users.
LM Studio is beginner-friendly and ideal for quick, no-fuss usage.
Ollama is made for users who want full control, deep customization, and seamless integration with their own systems.
Comments