Head to head · Local inference · October 2026 research run
Docker Model Runner vs vLLM
vLLM and Docker Model Runner score within a point of each other on agent readiness, 57.7 (C) and 57.1 (C). Docker Model Runner leads on reliability and transparency & trust. Both do local inference.
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Which one, for what
Good for A team that already runs Docker and wants local models served to containers and Compose services through OpenAI-, Anthropic- or Ollama-compatible routes, with models stored as OCI artefacts.
Ahead on
- Reliability, 85 against 62
- Transparency & trust, 73 against 67
Watch for
No credential on the API. The docs say any client that can reach it, including other containers, can pull, load and run models
vLLM C
Good for An owner with a GPU server who wants many concurrent requests against one open-weight model behind OpenAI or Anthropic compatible routes.
Ahead on
- Schema & documentation, 68 against 49
- Agent ergonomics, 64 against 58
- Security & auth, 50 against 40
- Maintenance & community, 88 against 55
Watch for
--api-key guards only the /v1, /v2, /inference and /cohere prefixes. /invocations, /pooling, /classify, /score, /rerank, /pause and /update_weights answer without it
Score by category
| Category | Weight this run | Docker Model Runner | vLLM | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 85 | 62 | Docker Model Runner +23 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 49 | 68 | vLLM +19 |
| Agent ergonomics | 13%16.2 | 58 | 64 | vLLM +6 |
| Security & auth | 14%17.5 | 40 | 50 | vLLM +10 |
| Payments & pricing | 10%12.5 | 60 | 60 | even |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 55 | 88 | vLLM +33 |
| Transparency & trust | 7%8.8 | 73 | 67 | Docker Model Runner +6 |
| Negative events | ≤15 | -3 | -6 | |
| Total | 57.1 · C | 57.7 · C |
Facts side by side
| Fact | Docker Model Runner | vLLM |
|---|---|---|
| Kind | HTTP API | HTTP API |
| Vendor | Docker, Inc. | vLLM project (PyTorch Foundation) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP | HTTP |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 (server, CLI plugin and dmr binary). Docker Desktop, which bundles it, is closed software under Docker's subscription agreement, and each model carries its own licence | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-08-12 | 2026-10-02 |
| Terms last updated | 2026-08-26 | no document linked |
| Privacy policy last updated | 2026-08-26 | no document linked |
| Customer content may train models | not found in the text | |
| Terms restrict automated access | yes | |
| Terms restrict benchmarking | yes | |
| Terms or service can change without notice | not found in the text | |
| Arbitration or class-action waiver | yes | |
| Popularity | 656 stars | 93k stars |
Verdicts
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.
vLLM
Apache-2.0 software with a release about every two weeks, each with notes that list breaking changes and security fixes. The optional API key covers only some path prefixes, so /invocations and control routes such as /pause answer without it, and at least 81 security advisories were published in the 12 months to 9 October 2026.
Before you call either
Docker Model Runner
- Use base URL
http://localhost:12434/engines/v1for OpenAI clients andhttp://localhost:12434for Anthropic and Ollama clients. Any API key value is accepted - In Docker Desktop, run
docker desktop enable model-runner --tcp 12434first. Host-side TCP is off by default - From a container, call
http://model-runner.docker.internalon Docker Desktop orhttp://172.17.0.1:12434on Docker Engine - Raise the context before agent work with
docker model configure --context-size <n> <model>. The llama.cpp default is 4,096 tokens - Name models with their namespace, such as
ai/smollm2, and expect plain-text error bodies with a 400, 404, 500 or 503 status
vLLM
- Put a reverse proxy that allowlists routes in front of the server.
--api-keyleaves/invocationsand the control routes open - Pass
--host 127.0.0.1for single-machine use. With no--hostthe server listens on every interface - Set
VLLM_NO_USAGE_STATS=1orDO_NOT_TRACK=1before starting if nothing should be sent to stats.vllm.ai - Start with
--enable-auto-tool-choiceand the--tool-call-parserfor the model before sending tools. Tool calling is off without them - Send
max_tokenson every request, and read the breaking changes section of the release notes before upgrading a minor version
Questions
Which is better for AI agents, Docker Model Runner or vLLM?
vLLM and Docker Model Runner score within a point of each other on agent readiness, 57.7 (C) and 57.1 (C). Docker Model Runner leads on reliability and transparency & trust.
Do Docker Model Runner and vLLM need an API key?
Neither needs a key.
Can an agent call Docker Model Runner and vLLM without installing anything?
No hosted endpoint is listed for Docker Model Runner. No hosted endpoint is listed for vLLM.
Are Docker Model Runner and vLLM open source?
Yes. Docker Model Runner is open source (Apache-2.0 (server, CLI plugin and `dmr` binary). Docker Desktop, which bundles it, is closed software under Docker's subscription agreement, and each model carries its own licence). vLLM is open source (Apache-2.0).
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Machine-readable
- This page as Markdown
/compare/docker-model-runner-vs-vllm.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/docker-model-runner.json·/api/v1/tools/vllm.json - From a terminal
anchor compare docker-model-runner vllm(the CLI) - Over MCP
compare_tools {"a": "docker-model-runner", "b": "vllm"}at/mcp, no key