LM Studio

Run Spaceduck with LM Studio for a GUI-based local model experience with chat and embeddings.

What it’s good for

The easiest local setup. LM Studio has a built-in model browser, one-click downloads, and runs an OpenAI-compatible server out of the box. Great if you want local models without managing GGUF files and command-line flags.

Requirements

• LM Studio installed
• A model downloaded through LM Studio’s model browser
• The local server started in LM Studio (Developer tab)

Configure in Spaceduck

Chat

1. Start the LM Studio server

   1. Open LM Studio
   2. Load a model (e.g., Qwen3, Llama 3.1, DeepSeek)
   3. Go to the Developer tab
   4. Click Start Server — it runs at http://localhost:1234 by default
2. Configure Spaceduck

   In Settings > Chat:

   • Provider: LM Studio
   • Base URL: http://localhost:1234/v1
   • Model: the model identifier shown in LM Studio (e.g., qwen/qwen3-4b-thinking-2507)

   Or via CLI:

   spaceduck config set /ai/provider lmstudio
   spaceduck config set /ai/model "qwen/qwen3-4b-thinking-2507"
   

   LM Studio doesn’t require an API key by default. Spaceduck sends a dummy key (lm-studio) for servers that require the Authorization header to be present.

3. Verify

   curl http://localhost:1234/v1/models
   

   You should see your loaded model listed.

Embeddings

LM Studio can serve embeddings from the same server, or you can run a second instance on a different port.

1. Load an embedding model

   In LM Studio, load an embedding model alongside your chat model, or start a second server instance on a different port.

2. Configure Spaceduck

   In Settings > Memory:

   • Toggle Semantic recall on
   • Provider: LM Studio
   • Server URL: http://localhost:1234/v1 (same server, or a different port if running separately)
   • Model: your embedding model identifier
   • Dimensions: match the model (e.g., 768 for nomic, 1024 for large models)

   Or via CLI:

   spaceduck config set /embedding/enabled true
   spaceduck config set /embedding/provider lmstudio
   spaceduck config set /embedding/model "nomic-ai/nomic-embed-text-v1.5"
   spaceduck config set /embedding/dimensions 768
   
3. Test

   Click the Test button in Settings > Memory to verify the embedding connection.

Test and troubleshoot

Problem	Cause	Fix
ECONNREFUSED on port 1234	LM Studio server not started	Go to Developer tab and click Start Server
Model not found	Model identifier doesn’t match	Check curl localhost:1234/v1/models for the exact name
Slow responses	Model too large for available RAM	Try a smaller model or lower quantization
<think> tags in output	Thinking model (Qwen3, DeepSeek)	Spaceduck strips these automatically — this is expected

LM Studio’s model browser makes it easy to try different models. Download a few, test them with Spaceduck, and keep the one that works best for your use case.