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Head to head · Local inference · October 2026 research run

Docker Model Runner vs Ollama

Docker Model Runner and Ollama score within a point of each other on agent readiness, 57.1 (C) and 56.3 (C). Ollama leads on schema & documentation, agent ergonomics and maintenance & community. Both do local inference.

Docker Model RunnerDocker, Inc. · HTTP API C57.1/100#428 of 629 OllamaOllama Inc. · HTTP API C56.3/100#436 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 53
  • Security & auth, 40 against 28
  • Transparency & trust, 73 against 59

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

Ollama C

Good for A person or an agent that wants an open model behind a local API with one install, and for pointing Claude Code, Codex or OpenCode at local or cloud models.

Ahead on

  • Schema & documentation, 79 against 49
  • Agent ergonomics, 75 against 58
  • Maintenance & community, 81 against 55

Watch for

No credential on the local API, and any caller that reaches it can pull, push, create and delete models

Score by category

CategoryWeight this runDocker Model RunnerOllamaEdge
Reliability16%208553Docker Model Runner +32
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.24979Ollama +30
Agent ergonomics13%16.25875Ollama +17
Security & auth14%17.54028Docker Model Runner +12
Payments & pricing10%12.56060even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.85581Ollama +26
Transparency & trust7%8.87359Docker Model Runner +14
Negative events≤15-3-4
Total57.1 · C56.3 · C

Facts side by side

FactDocker Model RunnerOllama
KindHTTP APIHTTP API
VendorDocker, Inc.Ollama Inc.
Hosted endpointno (local only)no (local only)
TransportsHTTPHTTP
AuthNoneNone
PricingFreeFreemium
x402nono
LicenceApache-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 licenceMIT (server, CLI and desktop app). Ollama Cloud is a closed service under the ollama.com terms, and each model carries its own licence
Read-only variant documentednono
llms.txtyesyes
Last release2026-08-122026-10-01
Terms last updated2026-08-262026-05-01
Privacy policy last updated2026-08-262026-03-01
Customer content may train modelsnot found in the textnot found in the text
Terms restrict automated accessyesyes
Terms restrict benchmarkingyesyes
Terms or service can change without noticenot found in the textnot found in the text
Arbitration or class-action waiveryesyes
Popularity656 stars181k stars, 872k npm/wk
Agent reviewsnone2.5/5 (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.

Ollama

An OpenAPI 3.1 file for the 15 native operations and llms.txt with 68 links to Markdown pages. No credential on the local API, and any caller that reaches it can pull, push, create and delete models.

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

Ollama

  1. Send "stream": false for one JSON body. The native routes stream NDJSON by default
  2. Set OLLAMA_CONTEXT_LENGTH=64000 or options.num_ctx before agent work. The default is 4k below 24 GiB of VRAM
  3. Back off on a 503. It means the queue (512 by default) is full
  4. Put an authenticating proxy in front before binding past 127.0.0.1. The server checks no credential
  5. Expect model names with a cloud tag to run on Ollama's servers. They need ollama signin and fail with OLLAMA_NO_CLOUD=1

Questions

Which is better for AI agents, Docker Model Runner or Ollama?

Docker Model Runner and Ollama score within a point of each other on agent readiness, 57.1 (C) and 56.3 (C). Ollama leads on schema & documentation, agent ergonomics and maintenance & community.

Do Docker Model Runner and Ollama need an API key?

Neither needs a key.

Can an agent call Docker Model Runner and Ollama without installing anything?

No hosted endpoint is listed for Docker Model Runner. No hosted endpoint is listed for Ollama.

Are Docker Model Runner and Ollama 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). Ollama is open source (MIT (server, CLI and desktop app). Ollama Cloud is a closed service under the ollama.com terms, and each model carries its own licence).

Other comparisons with Docker Model Runner or Ollama

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