Head to head · Local inference · October 2026 research run

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.

Docker Model RunnerDocker, Inc. · HTTP API C57.1/100#428 of 629 llama.cppggml.ai (Hugging Face) · HTTP API C60.2/100#362 of 629

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 this run	Docker Model Runner	llama.cpp	Edge
Reliability	16%20	85	64	Docker Model Runner +21
Performance	10%pending	pending	pending	not scored in this run
Schema & documentation	13%16.2	49	47	Docker Model Runner +2
Agent ergonomics	13%16.2	58	73	llama.cpp +15
Security & auth	14%17.5	40	52	llama.cpp +12
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	81	llama.cpp +26
Transparency & trust	7%8.8	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

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
In Docker Desktop, run docker desktop enable model-runner --tcp 12434 first. Host-side TCP is off by default
From a container, call http://model-runner.docker.internal on Docker Desktop or http://172.17.0.1:12434 on 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

llama.cpp

Start the server with --api-key and --cors-origins localhost before anything else can reach the port. Both are off by default
Pass n_predict or max_tokens. Generation is unbounded by default
Send response_fields to /completion to drop the fields you don't read
Wait and retry on a 503 unavailable_error. The model is still loading
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).

Other comparisons with Docker Model Runner or llama.cpp

Machine-readable

This page as Markdown /compare/docker-model-runner-vs-llama-cpp.md · slim .min.md · JSON .json (or send Accept: text/markdown)
Each listing in full /api/v1/tools/docker-model-runner.json · /api/v1/tools/llama-cpp.json
From a terminal anchor compare docker-model-runner llama-cpp (the CLI)
Over MCP compare_tools {"a": "docker-model-runner", "b": "llama-cpp"} at /mcp, no key

Which one, for what

Score by category

Facts side by side

Verdicts

Docker Model Runner

llama.cpp

Before you call either

Docker Model Runner

llama.cpp

Questions

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

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

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

Are Docker Model Runner and llama.cpp open source?

Other comparisons with Docker Model Runner or llama.cpp

Machine-readable

Do agents find, use and choose your tools?