# Docker Model Runner vs vLLM

> vLLM and Docker Model Runner score within a point of each other for local inference, 57.7 and 57.1 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/docker-model-runner-vs-vllm
- Markdown: https://www.anchorterminal.com/compare/docker-model-runner-vs-vllm.md (~2,750 tokens)
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- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- Updated: 2026-10-09

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.

- Docker Model Runner: grade C, 57.1/100, rank #621 of 950. Markdown https://www.anchorterminal.com/tools/docker-model-runner.md · JSON https://www.anchorterminal.com/api/v1/tools/docker-model-runner.json
- vLLM: grade C, 57.7/100, rank #600 of 950. Markdown https://www.anchorterminal.com/tools/vllm.md · JSON https://www.anchorterminal.com/api/v1/tools/vllm.json
- Best local AI models and assistants: https://www.anchorterminal.com/best/local-ai/index.md
- All 184 local ai comparisons: https://www.anchorterminal.com/compare/local-ai/index.md

## Which one, for what

### Docker Model Runner (C)

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 | Docker Model Runner | vLLM | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 85 | 62 | Docker Model Runner +23 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 49 | 68 | vLLM +19 |
| Agent ergonomics | 13% (16.2 this run) | 58 | 64 | vLLM +6 |
| Security & auth | 14% (17.5 this run) | 40 | 50 | vLLM +10 |
| Payments & pricing | 10% (12.5 this run) | 60 | 60 | even |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 55 | 88 | vLLM +33 |
| Transparency & trust | 7% (8.8 this run) | 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

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

### vLLM

1. Put a reverse proxy that allowlists routes in front of the server. `--api-key` leaves `/invocations` and the control routes open
2. Pass `--host 127.0.0.1` for single-machine use. With no `--host` the server listens on every interface
3. Set `VLLM_NO_USAGE_STATS=1` or `DO_NOT_TRACK=1` before starting if nothing should be sent to stats.vllm.ai
4. Start with `--enable-auto-tool-choice` and the `--tool-call-parser` for the model before sending tools. Tool calling is off without them
5. Send `max_tokens` on 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).


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/docker-model-runner-vs-vllm.json, and with the fewest tokens: https://www.anchorterminal.com/compare/docker-model-runner-vs-vllm.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "docker-model-runner", "b": "vllm"}`. From a terminal: `anchor compare docker-model-runner vllm`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/docker-model-runner.json and https://www.anchorterminal.com/api/v1/tools/vllm.json

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