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oam/knowledge base/ai/lmstudio.md
2026-02-11 01:14:19 +01:00

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# LMStudio
Allows running LLMs locally.<br/>
Considered the most accessible tool for local LLM deployment, particularly for users with no technical background.
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## Table of contents <!-- omit in toc -->
1. [TL;DR](#tldr)
1. [Further readings](#further-readings)
1. [Sources](#sources)
## TL;DR
Focused on single-user scenarios without built-in rate limiting or authentication.
Offers highly mature and stable OpenAI-compatible API.
Supports full streaming, embeddings API, experimental function calling for compatible models, and limited multimodal
support.
Supports GGUF and Hugging Face Safetensors formats.<br/>
Has a built-in converter for some models, and can run split GGUF models.
Implements experimental tool calling support following the OpenAI function calling API format.<br/>
Models trained on function calling (e.g., Hermes 2 Pro, Llama 3.1, and Functionary) can invoke external tools through
the local API server. However, tool calling should **not** yet be considered suitable for production.<br/>
Streaming tool calls or advanced features like parallel function invocation are not currently supported.<br/>
Some models show better tool calling behavior than others.
The UI eases defining function schemas and test tool calls interactively
Considered ideal for:
- Beginners new to local LLM deployment.
- Users who prefer graphical interfaces over command-line tools.
- Developers needing good performance on lower-spec hardware (especially with integrated GPUs).
- Anyone wanting a polished professional user experience.
<details>
<summary>Setup</summary>
```sh
brew install --cask 'lm-studio'
```
</details>
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<details>
<summary>Usage</summary>
```sh
```
</details>
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<details>
<summary>Real world use cases</summary>
```sh
```
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## Further readings
- [Website]
- [Codebase]
- [Blog]
### Sources
- [Documentation]
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[Blog]: https://lmstudio.ai/blog
[Codebase]: https://github.com/lmstudio-ai
[Documentation]: https://lmstudio.ai/docs/
[Website]: https://lmstudio.ai/
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