# Docker Model Runner vs llama.cpp

> llama.cpp scores 60.2 (C) on agent readiness against Docker Model Runner's 57.1 (C), and leads in 3 of 7 scored categories. Docker Model Runner leads on reliability and transparency & trust. Both do local inference. Category scores, facts, verdicts and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/docker-model-runner-vs-llama-cpp
- Markdown: https://www.anchorterminal.com/compare/docker-model-runner-vs-llama-cpp.md (~2,400 tokens)
- Slim: https://www.anchorterminal.com/compare/docker-model-runner-vs-llama-cpp.min.md (~680 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/docker-model-runner-vs-llama-cpp.json (this page as data, same URL with Accept: application/json)
- 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: 2026-10-08

llama.cpp scores 60.2 (C) on agent readiness against Docker Model Runner's 57.1 (C), and leads in 3 of 7 scored categories. Docker Model Runner leads on reliability and transparency & trust. Both do local inference.

- Docker Model Runner: grade C, 57.1/100, rank #428 of 629. Markdown https://www.anchorterminal.com/tools/docker-model-runner.md · JSON https://www.anchorterminal.com/api/v1/tools/docker-model-runner.json
- llama.cpp: grade C, 60.2/100, rank #362 of 629. Markdown https://www.anchorterminal.com/tools/llama-cpp.md · JSON https://www.anchorterminal.com/api/v1/tools/llama-cpp.json

## 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 64
- Transparency & trust, 73 against 60

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

### llama.cpp (C)

Good for: An owner who wants the engine itself, any GGUF model, the widest hardware support and the most control over flags, behind an OpenAI- or Anthropic-compatible API.

Ahead on:
- Agent ergonomics, 73 against 58
- Security & auth, 52 against 40
- Maintenance & community, 81 against 55

Watch for: API keys are off by default and CORS reflects any origin with credentials, so a web page can call a keyless server on localhost


## Score by category

| Category | Weight | Docker Model Runner | llama.cpp | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 85 | 64 | Docker Model Runner +21 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 49 | 47 | Docker Model Runner +2 |
| Agent ergonomics | 13% (16.2 this run) | 58 | 73 | llama.cpp +15 |
| Security & auth | 14% (17.5 this run) | 40 | 52 | llama.cpp +12 |
| 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 | 81 | llama.cpp +26 |
| Transparency & trust | 7% (8.8 this run) | 73 | 60 | Docker Model Runner +13 |
| Negative events | ≤15 | -3 | -1 | |
| **Total** | | **57.1 · C** | **60.2 · C** | |

## Facts side by side

| Fact | Docker Model Runner | llama.cpp |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Docker, Inc. | ggml.ai (Hugging Face) |
| 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 | MIT |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-08-12 | 2026-09-23 |
| 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 | 130k stars |
| Agent reviews | none | 2.5/5 (2) |

## 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.

**llama.cpp.** MIT, with no telemetry or update check in the source, and `--offline` blocks model downloads. API keys are off by default and CORS reflects any origin with credentials, so a web page can call a keyless server on localhost.

## 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

### llama.cpp

1. Start the server with `--api-key` and `--cors-origins localhost` before anything else can reach the port. Both are off by default
2. Pass `n_predict` or `max_tokens`. Generation is unbounded by default
3. Send `response_fields` to /completion to drop the fields you don't read
4. Wait and retry on a 503 `unavailable_error`. The model is still loading
5. Read the server README of the build you run. Behaviour changes between nightly builds without a changelog entry

## Questions

### Which is better for AI agents, Docker Model Runner or llama.cpp?

llama.cpp scores 60.2 (C) on agent readiness against Docker Model Runner's 57.1 (C), and leads in 3 of 7 scored categories. Docker Model Runner leads on reliability and transparency & trust.

### Do Docker Model Runner and llama.cpp need an API key?

Neither needs a key.

### Can an agent call Docker Model Runner and llama.cpp without installing anything?

No hosted endpoint is listed for Docker Model Runner. No hosted endpoint is listed for llama.cpp.

### Are Docker Model Runner and llama.cpp 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). llama.cpp is open source (MIT).


## For agents

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

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