GPT4All vs LM Studio

GPT4All

MIT, with installers for Windows x64 and ARM64, macOS 12.6 or later and Linux, and published minimum and recommended hardware. No release since 24 February 2025 and no commit to main since 27 May 2025.

LM Studio

OpenAI-compatible chat completions, responses, completions and embeddings, Anthropic-compatible /v1/messages and a native /api/v1, all on one port. Authentication is off by default, so any local process can call the server.

GPT4All

1. Ask the owner to tick Enable Local API Server in Settings. Nothing answers on port 4891 until they do
2. Leave out stream, tools, tool_choice and response_format. The server returns 400 for each
3. Use the model's display name from /v1/models, such as "Phi-3 Mini Instruct"
4. Read LocalDocs snippets from choices[0].references. Collections can only be switched on in the app
5. Plan tool use outside GPT4All. Its API can't call tools

LM Studio

1. Send Authorization: Bearer $LM_API_TOKEN when the owner gives you a token. With Require Authentication on, every request needs it
2. Pass previous_response_id to /api/v1/chat instead of resending the history, and store: false for one-off calls
3. List models with GET /api/v1/models before naming one. A named model that's downloaded loads just in time
4. Install the Python SDK pre-release (1.6.0b1) and pass api_token directly. It reads LMSTUDIO_API_TOKEN, not the LM_API_TOKEN the docs name
5. Set allowed_tools on every MCP integration. Without it the model sees every tool on the server