LM Studio vs TextGen

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.

TextGen

AGPL-3.0 with no telemetry, and a local API on 127.0.0.1:5000 that checks the Host header, limits CORS to localhost and separates an admin key from the caller's key. No release since v4.9 on 20 May 2026, no code commits since 31 May, no test suite, and ten security advisories in the year, all fixed.

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

TextGen

1. Ask the owner to launch with --api. Nothing listens on port 5000 without it, and a model must be loaded first
2. Call http://127.0.0.1:5000/v1. Any Host header other than localhost or 127.0.0.1 gets 400 Invalid host header unless --listen is set
3. Send the key as Authorization: Bearer on OpenAI routes and as x-api-key on /v1/messages. Model loading needs the admin key
4. Read http://127.0.0.1:5000/docs or modules/api/typing.py for parameters. max_tokens defaults to 512 on chat completions
5. Run tool calls yourself. The API returns finish_reason: "tool_calls" and executes nothing on the server
6. Use the repository name oobabooga/textgen. The old text-generation-webui URL redirects