Docker Model Runner vs TextGen

Docker Model Runner

CI passes on the main branch, and Docker has published two security advisories with CVEs and fixed versions for the project. The API takes no credential, so any client or container that reaches it can pull, delete and run models, and the documentation has no OpenAPI file or error reference.

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.

Docker Model Runner

1. Use base URL http://localhost:12434/engines/v1 for OpenAI clients and http://localhost:12434 for Anthropic and Ollama clients. Any API key value is accepted
2. In Docker Desktop, run docker desktop enable model-runner --tcp 12434 first. Host-side TCP is off by default
3. From a container, call http://model-runner.docker.internal on Docker Desktop or http://172.17.0.1:12434 on Docker Engine
4. Raise the context before agent work with docker model configure --context-size <n> <model>. The llama.cpp default is 4,096 tokens
5. Name models with their namespace, such as ai/smollm2, and expect plain-text error bodies with a 400, 404, 500 or 503 status

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