LM Studio

LM Studio is a popularlocal LLM GUIsupports downloading, quantizing, and running inference on various open-source models locally. Cherry Studio can act as a frontend connected to LM Studio's local service, giving you a better chat experience while preserving local privacy.

Prerequisites

1. From LM Studio official website Download and install the client
2. Download at least one model in LM Studio (Llama 3.x 8B or the Qwen series is recommended to try first)
3. Open the top of LM Studio Server Tab, click Start Server(default port 1234)

Configure in Cherry Studio

• Open Settings → Model Services, find LM Studio Provider to enter the details page
• API address Default http://localhost:1234, if you have changed LM Studio's port, please update it accordingly
• API key Can be left blank (local inference does not require authentication), or fill it in after enabling authentication in LM Studio
• Click Get model list, Cherry Studio will automatically fetch the models loaded in LM Studio

Model list empty? LM Studio only exposesAlready Load into memorymodels; those not loaded will not appear in the list. Go back to LM Studio, load the model first, then "Get model list".

Recommended usage

Scenario	Recommendation
Privacy-sensitive conversations	Choose a small model (under 8B) to run locally, completely offline
Apple Silicon (M-series chips)	LM Studio uses the MLX backend, which is significantly more efficient than llama.cpp
embedding model	LM Studio can also load embedding models for global memory and knowledge bases

Differences from Ollama

	LM Studio	Ollama
Form	Graphical interface + Server	Command line / background service
Model management	GUI browse/download	ollama pull
API	OpenAI-compatible	OpenAI-compatible
Suitable for	Users who prefer graphical interaction	Users who prefer command line / Docker deployment

Both can be connected to Cherry Studio; just choose according to your preference.

Frequently asked questions

• Cherry Studio can't connect: Check whether Server in LM Studio has been Started (green dot status)
• Responses are very slow: The model is too large / not enough VRAM; switch to a smaller model or a higher quantization (e.g. Q4 → Q3)
• Garbled text / truncated output: The context length exceeds the model limit; increase it in LM Studio n_ctx

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💡 Get help and submit feedback

If you encounter any questions, bugs, or have suggestions for feature improvements during configuration or use, please refer to Feedback and Suggestions the official channels provided there.