{ "data": { "a": { "slug": "docker-model-runner", "name": "Docker Model Runner", "vendor": "Docker, Inc.", "vendorUrl": "https://www.docker.com", "kind": "http-api", "category": "local-ai", "summary": "Docker's open-source tool for pulling and running open models from Docker Hub, OCI registries or Hugging Face. It runs through Docker Desktop, Docker Engine or a standalone `dmr` binary, with local OpenAI-, Anthropic- and Ollama-compatible APIs.", "url": "https://www.anchorterminal.com/tools/docker-model-runner", "markdownUrl": "https://www.anchorterminal.com/tools/docker-model-runner.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/docker-model-runner.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/docker-model-runner.json", "repo": "https://github.com/docker/model-runner", "license": "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", "transports": [ "http" ], "packages": [ { "registry": "oci", "name": "docker.io/docker/model-runner" } ], "auth": "none", "authNotes": "The API takes no credential, and the docs say it ignores any key sent. Per the docs, any client that can reach it, including other containers on the same Docker network, can pull, load and run models. In Docker Desktop, host-side TCP is off until enabled in settings or with `docker desktop enable model-runner --tcp \u003cport\u003e`, and containers reach the API at model-runner.docker.internal. In Docker Engine, TCP is on by default on port 12434. Cross-origin requests get 403 unless the origin is localhost, 127.0.0.1, 0.0.0.0 or listed in `DMR_ORIGINS` (https://docs.docker.com/ai/model-runner/; https://github.com/docker/model-runner/blob/main/pkg/envconfig/envconfig.go).", "pricing": "free", "pricingNotes": "Free under Apache-2.0, with no account needed for the Docker Engine plugin or the standalone `dmr` binary. On macOS and Windows it also ships inside Docker Desktop, which is free for personal use, non-commercial open-source projects and businesses with fewer than 250 employees and under US $10,000,000 in annual revenue. Larger organisations need a paid Docker plan for Desktop (https://www.docker.com/legal/docker-subscription-service-agreement/; https://www.docker.com/pricing/, checked 2026-10-08).", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs or the source (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 656, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-08" }, "docsUrl": "https://docs.docker.com/ai/model-runner/", "llmsTxt": "https://docs.docker.com/llms.txt", "capabilities": [ "inference.local", "inference.open-weights", "inference.llm", "embed.text", "rerank", "image.generate" ], "tags": [ "open-source", "local", "self-hosted", "free", "no-card", "openai-compatible", "llms-txt", "docker", "go", "no-auth" ], "lastRelease": "2026-08-12", "graded": true, "anchor": { "graded": true, "score": 57.1, "grade": "C", "agentReady": false, "rank": 428, "ranked": true, "rankOf": 629, "categoryRank": 5, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 58, "maintenance": 55, "payments": 60, "reliability": 85, "schema": 49, "security": 40, "transparency": 73 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": -3, "negativeNotes": [ "2026-02-27. GHSA-m456-c56c-hh5c (CVE-2026-28400, 7.5). The unauthenticated `/engines/_configure` route accepted arbitrary runtime flags, so a caller, including a container on Docker Desktop, could overwrite files the runner could reach, the Desktop VM disk among them. Fixed in Model Runner 1.0.16 and Docker Desktop 4.61.0 and published by Docker, more than six months ago, -2. https://github.com/docker/model-runner/security/advisories/GHSA-m456-c56c-hh5c", "2026-03-30. GHSA-x2f5-332j-9xwq (CVE-2026-33990, 7.1). A malicious OCI registry could point the token exchange at an internal URL and make the runner send GET requests to host-local services. Fixed in 1.1.25 and Docker Desktop 4.67.0 and published by Docker, more than six months ago, -1. https://github.com/docker/model-runner/security/advisories/GHSA-x2f5-332j-9xwq" ], "verdict": "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.", "bestFor": "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.", "strengths": [ "OpenAI-, Anthropic- and Ollama-compatible routes on one local port, so existing clients for those three APIs work with a changed base URL", "CI runs lint, race-detector tests and end-to-end tests on every push to main, and the ten most recent runs on main passed on 8 October 2026", "Two GitHub security advisories with CVE numbers, fixed versions and workarounds, and a SECURITY.md that promises an acknowledgement within 72 hours", "Apache-2.0 source, and the docs list what usage data is collected with a link to the code that sends it", "Host-side TCP is off by default in Docker Desktop, and inference engines run sandboxed on macOS and Windows or in a container on Linux" ], "weaknesses": [ "No credential on the API. The docs say any client that can reach it, including other containers, can pull, load and run models", "No OpenAPI file, no error reference and no rate-limit or retry guidance in the reviewed documentation", "Two releases in the 90 days to 8 October 2026 (v1.2.7 and v1.2.8), the latest on 12 August", "CVE-2026-28400 let an unauthenticated caller overwrite files, including the Docker Desktop VM disk, until 1.0.16 in February 2026", "On Docker Engine the docs say model-name requests go to Docker Hub regardless of settings, and the `DO_NOT_TRACK` switch in the source is undocumented" ], "agentNotes": [ "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 \u003cn\u003e \u003cmodel\u003e`. 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" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 57.1 } ], "editorialScores": { "ergonomics": 58, "maintenance": 55, "payments": 60, "reliability": 85, "schema": 49, "security": 40, "transparency": 62 }, "provenanceScore": 84 }, "connect": { "install": "sudo apt-get update \u0026\u0026 sudo apt-get install docker-model-plugin # Docker Engine on Ubuntu or Debian; Docker Desktop: docker desktop enable model-runner --tcp 12434\ndocker model pull ai/smollm2", "http": "curl http://localhost:12434/engines/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"ai/smollm2\",\n \"messages\": [{\"role\": \"user\", \"content\": \"Say hello in one sentence.\"}]\n }'", "claudeCode": "docker model launch claude" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/docker-model-runner" }, "sameCompany": [ "docker-agent" ], "area": "models", "provenance": { "legalEntity": "Docker, Inc.", "domain": "docker.com", "domainRegistered": "1995-01-25", "endpointOnVendorDomain": null, "terms": "https://www.docker.com/legal/docker-subscription-service-agreement/", "privacy": "https://www.docker.com/legal/privacy/", "statusPage": "", "changelog": "https://github.com/docker/model-runner/releases", "securityTxt": "valid", "checked": "2026-10-08", "notes": [ "The repository is under GitHub's docker organisation and SECURITY.md sends reports to security@docker.com. The subscription agreement and privacy policy both name Docker, Inc.", "Docker publishes no terms written for Model Runner. The Docker Subscription Service Agreement (last updated 26 August 2026) governs Docker Desktop, which bundles it, and the privacy policy carries the same date. The Engine plugin and the `dmr` binary are under Apache-2.0 only.", "www.docker.com/.well-known/security.txt gives security@docker.com, a policy URL and an expiry of 1 January 2030.", "No status page is listed because the software runs on the owner's machine.", "RDAP for docker.com gives a registration date of 1995-01-25." ], "score": 84 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/docker-model-runner.json", "live": { "slug": "docker-model-runner", "pages": [ { "url": "https://www.docker.com/pricing/", "kind": "pricing", "status": 200, "checkedAt": "2026-10-08T18:27:30.95553924Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "308829465f88" }, { "url": "https://www.docker.com/legal/docker-subscription-service-agreement/", "kind": "terms", "status": 200, "checkedAt": "2026-10-08T18:27:24.912652297Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "f8cfdf3308dd" } ], "updatedAt": "2026-10-08T18:27:30.95553924Z" } }, "answer": "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 \u0026 documentation, agent ergonomics and maintenance \u0026 community.", "b": { "slug": "ollama", "name": "Ollama", "vendor": "Ollama Inc.", "vendorUrl": "https://ollama.com", "kind": "http-api", "category": "local-ai", "summary": "Open-source model runner for macOS, Windows and Linux, with a local API and a library of downloadable models.", "url": "https://www.anchorterminal.com/tools/ollama", "markdownUrl": "https://www.anchorterminal.com/tools/ollama.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/ollama.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/ollama.json", "repo": "https://github.com/ollama/ollama", "license": "MIT (server, CLI and desktop app). Ollama Cloud is a closed service under the ollama.com terms, and each model carries its own licence", "transports": [ "http" ], "packages": [ { "registry": "oci", "name": "docker.io/ollama/ollama" }, { "registry": "pypi", "name": "ollama" }, { "registry": "npm", "name": "ollama" } ], "auth": "none", "authNotes": "The local API at http://localhost:11434 takes no credential. It binds 127.0.0.1, answers a foreign Host header with 403 while bound to loopback, and allows cross-origin calls from 127.0.0.1 and 0.0.0.0 unless `OLLAMA_ORIGINS` adds more. Anything that reaches the port can generate, pull, push, create, copy and delete models. Cloud models through the local server need `ollama signin`, which signs requests with the install's own key. Direct calls to https://ollama.com/api and /v1 need a Bearer API key from ollama.com/settings/keys, which doesn't expire and has no scopes, and is revoked from the same page (https://github.com/ollama/ollama/blob/main/docs/api/authentication.mdx).", "pricing": "freemium", "pricingNotes": "The server, CLI and desktop app are free under MIT with no account. Ollama Cloud has five plans on ollama.com/pricing. Free ($0, starter usage credits, starter models, 1 concurrent request), Pro ($20 a month or $200 a year, $60 of usage credits a month, 3 concurrent requests), Max ($100 a month, $300 of credits, 10 concurrent requests), Team ($500 a month, $1,000 of shared credits, unlimited users) and Enterprise (custom). Usage is priced per model by the token, and the page doesn't say whether the Free plan needs a card (checked 2026-10-03).", "priceSummary": "$20 / mo", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs, the pricing page or the source (checked 2026-10-03).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 181200, "npmWeekly": 871543, "pypiWeekly": null, "asOf": "2026-10-03" }, "docsUrl": "https://docs.ollama.com", "llmsTxt": "https://docs.ollama.com/llms.txt", "openapi": "https://raw.githubusercontent.com/ollama/ollama/main/docs/openapi.yaml", "capabilities": [ "inference.local", "inference.open-weights", "inference.llm", "embed.text", "inference.decision", "web.search", "web.fetch" ], "tags": [ "open-source", "local", "self-hosted", "hosted", "freemium", "no-card", "openai-compatible", "openapi", "llms-txt", "docker", "go", "python", "typescript", "pre-1.0", "no-auth" ], "lastRelease": "2026-10-01", "graded": true, "anchor": { "graded": true, "score": 56.3, "grade": "C", "agentReady": false, "rank": 436, "ranked": true, "rankOf": 629, "categoryRank": 6, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 75, "maintenance": 81, "payments": 60, "reliability": 53, "schema": 79, "security": 28, "transparency": 59 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-03" }, "negative": -4, "negativeNotes": [ "2026-04-29. CERT Polska published CVE-2026-42248 and CVE-2026-42249 (9.8 each). The Windows app accepted downloaded updates without a signature check and took the file name from the server's response, and it installs updates silently, so whoever could answer the update request could run code on the machine. CERT Polska tested 0.12.10 to 0.17.5, and the Windows check stayed a stub returning success until v0.23.3 on 12 May 2026, whose notes list the fix only as `app: harden update flows`. CERT Polska says the maintainers didn't respond with details or the vulnerable range, and Ollama published no advisory. Fixed, but not disclosed by the vendor, -4. https://cert.pl/en/posts/2026/04/CVE-2026-42248/; https://github.com/ollama/ollama/releases/tag/v0.23.3" ], "verdict": "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.", "bestFor": "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.", "strengths": [ "An OpenAPI 3.1 file for the 15 native operations and llms.txt with 68 links to Markdown pages", "Native, OpenAI-compatible and Anthropic-compatible routes on one local port, with `ollama launch` for Claude Code, Codex and OpenCode", "28 releases in the 90 days to 3 October 2026, and official Python and JavaScript libraries released on 28 September", "Local prompts stay on the machine, and `OLLAMA_NO_CLOUD=1` turns off cloud models and web search", "Binds 127.0.0.1 by default and refuses foreign Host headers while bound to loopback" ], "weaknesses": [ "No credential on the local API, and any caller that reaches it can pull, push, create and delete models", "No GitHub security advisory, against 12 CVEs on NVD since October 2025", "The Windows updater installed unsigned files until v0.23.3 on 12 May 2026, fixed under a release note that didn't mention security", "The desktop app checks ollama.com every hour with a signed request, even with automatic updates off, and no documented way to stop it", "A default context of 4k tokens below 24 GiB of VRAM, where the docs say agents need 64,000" ], "agentNotes": [ "Send `\"stream\": false` for one JSON body. The native routes stream NDJSON by default", "Set `OLLAMA_CONTEXT_LENGTH=64000` or `options.num_ctx` before agent work. The default is 4k below 24 GiB of VRAM", "Back off on a 503. It means the queue (512 by default) is full", "Put an authenticating proxy in front before binding past 127.0.0.1. The server checks no credential", "Expect model names with a `cloud` tag to run on Ollama's servers. They need `ollama signin` and fail with `OLLAMA_NO_CLOUD=1`" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 2, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 56.3 } ], "editorialScores": { "ergonomics": 75, "maintenance": 81, "payments": 60, "reliability": 53, "schema": 79, "security": 28, "transparency": 66 }, "provenanceScore": 52 }, "connect": { "install": "curl -fsSL https://ollama.com/install.sh | sh # macOS and Linux; Windows: irm https://ollama.com/install.ps1 | iex\nollama pull gemma4:e2b", "http": "curl http://localhost:11434/api/chat \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"gemma4:e2b\",\n \"messages\": [{\"role\": \"user\", \"content\": \"Say hello in one sentence.\"}],\n \"stream\": false\n }'", "claudeCode": "ollama launch claude # or: ANTHROPIC_AUTH_TOKEN=ollama ANTHROPIC_API_KEY=\"\" ANTHROPIC_BASE_URL=http://localhost:11434 claude --model qwen3.5" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/ollama" }, "area": "models", "unitPrices": [ { "item": "Ollama Cloud Pro", "unit": "month", "usd": 20, "note": "$60 of usage credits a month, 3 concurrent requests. $200 a year" }, { "item": "Ollama Cloud Max", "unit": "month", "usd": 100, "note": "$300 of usage credits a month, 10 concurrent requests" }, { "item": "Ollama Cloud Team", "unit": "month", "usd": 500, "note": "$1,000 of shared usage credits a month, unlimited users, 10 concurrent requests" } ], "provenance": { "legalEntity": "Ollama Inc.", "domain": "ollama.com", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "https://ollama.com/terms", "privacy": "https://ollama.com/privacy", "statusPage": "", "changelog": "https://github.com/ollama/ollama/releases", "securityTxt": "none", "checked": "2026-10-03", "notes": [ "The terms (last updated May 2026) name Ollama Inc., under California law with arbitration in San Francisco. The privacy policy was last updated in March 2026.", "ollama.com/.well-known/security.txt returns 404. SECURITY.md sends reports to hello@ollama.com.", "status.ollama.com doesn't resolve, and we found no other status page for Ollama Cloud.", "The API an agent calls runs on the owner's machine, so there's no shared endpoint to check. Ollama Cloud answers at https://ollama.com/api and /v1." ], "score": 52 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/ollama.json", "live": { "slug": "ollama", "versions": [ { "registry": "github", "name": "ollama/ollama", "version": "v0.40.1", "released": "2026-10-07", "seenAt": "2026-10-08T16:23:02.6097517Z" }, { "registry": "npm", "name": "ollama", "version": "0.6.4", "seenAt": "2026-10-08T16:23:02.362375923Z" }, { "registry": "pypi", "name": "ollama", "version": "0.6.3", "released": "2026-09-29", "seenAt": "2026-10-08T16:23:02.244609581Z" } ], "githubStars": 182568, "npmWeekly": 896480, "pypiWeekly": 3497787, "securityTxt": { "url": "https://ollama.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-08T15:38:41.845996296Z" }, "llmsTxt": { "url": "https://docs.ollama.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-08T14:00:42.41869475Z" }, "domain": { "domain": "ollama.com", "registered": "2017-05-08", "source": "https://rdap.verisign.com/com/v1/domain/ollama.com", "checkedAt": "2026-10-04T13:05:52.948193398Z" }, "pages": [ { "url": "https://ollama.com/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-08T18:22:27.211563974Z", "changedAt": "2026-10-08T18:22:27.211563974Z", "fingerprint": "0d2286fd10da" }, { "url": "https://ollama.com/terms", "kind": "terms", "status": 200, "checkedAt": "2026-10-08T18:22:29.35897412Z", "changedAt": "2026-10-08T18:22:29.35897412Z", "fingerprint": "3bfbf07c7a8b" } ], "updatedAt": "2026-10-08T18:22:29.35897412Z" } }, "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "Docker, Inc.", "b": "Ollama Inc.", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Freemium", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "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", "b": "MIT (server, CLI and desktop app). Ollama Cloud is a closed service under the ollama.com terms, and each model carries its own licence", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-08-12", "b": "2026-10-01", "name": "Last release" }, { "a": "2026-08-26", "b": "2026-05-01", "name": "Terms last updated" }, { "a": "2026-08-26", "b": "2026-03-01", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "yes", "b": "yes", "name": "Terms restrict automated access" }, { "a": "yes", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "yes", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "656 stars", "b": "181k stars, 872k npm/wk", "name": "Popularity" }, { "a": "none", "b": "2.5/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "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 \u0026 documentation, agent ergonomics and maintenance \u0026 community.", "question": "Which is better for AI agents, Docker Model Runner or Ollama?" }, { "answer": "Neither needs a key.", "question": "Do Docker Model Runner and Ollama need an API key?" }, { "answer": "No hosted endpoint is listed for Docker Model Runner. No hosted endpoint is listed for Ollama.", "question": "Can an agent call Docker Model Runner and Ollama without installing anything?" }, { "answer": "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).", "question": "Are Docker Model Runner and Ollama open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 85 against 53", "Security \u0026 auth, 40 against 28", "Transparency \u0026 trust, 73 against 59" ], "also": null, "goodFor": "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.", "slug": "docker-model-runner", "watchFor": "No credential on the API. The docs say any client that can reach it, including other containers, can pull, load and run models" }, { "aheadOn": [ "Schema \u0026 documentation, 79 against 49", "Agent ergonomics, 75 against 58", "Maintenance \u0026 community, 81 against 55" ], "also": null, "goodFor": "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.", "slug": "ollama", "watchFor": "No credential on the local API, and any caller that reaches it can pull, push, create and delete models" } ], "job": { "capability": "inference.local", "name": "Local inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-docker-model-runner.json", "title": "AnythingLLM vs Docker Model Runner", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-docker-model-runner" }, { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-ollama.json", "title": "AnythingLLM vs Ollama", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-ghost-core.json", "title": "Docker Model Runner vs Core", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-ghost-core" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-gpt4all.json", "title": "Docker Model Runner vs GPT4All", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-gpt4all" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-jan.json", "title": "Docker Model Runner vs Jan", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-jan" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-khoj.json", "title": "Docker Model Runner vs Khoj", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-khoj" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-llama-cpp.json", "title": "Docker Model Runner vs llama.cpp", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-llama-cpp" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-lm-studio.json", "title": "Docker Model Runner vs LM Studio", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-localai.json", "title": "Docker Model Runner vs LocalAI", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-open-webui.json", "title": "Docker Model Runner vs Open WebUI", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-screenpipe.json", "title": "Docker Model Runner vs screenpipe", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-ollama.json", "title": "Core vs Ollama", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-ollama.json", "title": "GPT4All vs Ollama", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-ollama.json", "title": "Jan vs Ollama", "url": "https://www.anchorterminal.com/compare/jan-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/khoj-vs-ollama.json", "title": "Khoj vs Ollama", "url": "https://www.anchorterminal.com/compare/khoj-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/llama-cpp-vs-ollama.json", "title": "llama.cpp vs Ollama", "url": "https://www.anchorterminal.com/compare/llama-cpp-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/lm-studio-vs-ollama.json", "title": "LM Studio vs Ollama", "url": "https://www.anchorterminal.com/compare/lm-studio-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/localai-vs-ollama.json", "title": "LocalAI vs Ollama", "url": "https://www.anchorterminal.com/compare/localai-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/ollama-vs-open-webui.json", "title": "Ollama vs Open WebUI", "url": "https://www.anchorterminal.com/compare/ollama-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/ollama-vs-screenpipe.json", "title": "Ollama vs screenpipe", "url": "https://www.anchorterminal.com/compare/ollama-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-underdog.json", "title": "Docker Model Runner vs Underdog", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-underdog" }, { "json": "https://www.anchorterminal.com/compare/ollama-vs-underdog.json", "title": "Ollama vs Underdog", "url": "https://www.anchorterminal.com/compare/ollama-vs-underdog" } ], "scores": [ { "by": 32, "docker-model-runner": 85, "edge": "docker-model-runner", "key": "reliability", "name": "Reliability", "ollama": 53, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 30, "docker-model-runner": 49, "edge": "ollama", "key": "schema", "name": "Schema \u0026 documentation", "ollama": 79, "weight": 13 }, { "by": 17, "docker-model-runner": 58, "edge": "ollama", "key": "ergonomics", "name": "Agent ergonomics", "ollama": 75, "weight": 13 }, { "by": 12, "docker-model-runner": 40, "edge": "docker-model-runner", "key": "security", "name": "Security \u0026 auth", "ollama": 28, "weight": 14 }, { "by": 0, "docker-model-runner": 60, "edge": "", "key": "payments", "name": "Payments \u0026 pricing", "ollama": 60, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 26, "docker-model-runner": 55, "edge": "ollama", "key": "maintenance", "name": "Maintenance \u0026 community", "ollama": 81, "weight": 7 }, { "by": 14, "docker-model-runner": 73, "edge": "docker-model-runner", "key": "transparency", "name": "Transparency \u0026 trust", "ollama": 59, "weight": 7 } ], "summary": "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 \u0026 documentation, agent ergonomics and maintenance \u0026 community. Both do local inference.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/docker-model-runner-vs-ollama", "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-ollama.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/docker-model-runner-vs-ollama.md", "slim": "https://www.anchorterminal.com/compare/docker-model-runner-vs-ollama.min.md" }, "markdown": "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 \u0026 documentation, agent ergonomics and maintenance \u0026 community. Both do local inference.\n\n- 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\n- Ollama: grade C, 56.3/100, rank #436 of 629. Markdown https://www.anchorterminal.com/tools/ollama.md · JSON https://www.anchorterminal.com/api/v1/tools/ollama.json\n\n## Which one, for what\n\n### Docker Model Runner (C)\n\nGood 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.\n\nAhead on:\n- Reliability, 85 against 53\n- Security \u0026 auth, 40 against 28\n- Transparency \u0026 trust, 73 against 59\n\nWatch for: No credential on the API. The docs say any client that can reach it, including other containers, can pull, load and run models\n\n### Ollama (C)\n\nGood 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.\n\nAhead on:\n- Schema \u0026 documentation, 79 against 49\n- Agent ergonomics, 75 against 58\n- Maintenance \u0026 community, 81 against 55\n\nWatch for: No credential on the local API, and any caller that reaches it can pull, push, create and delete models\n\n\n## Score by category\n\n| Category | Weight | Docker Model Runner | Ollama | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 85 | 53 | Docker Model Runner +32 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 49 | 79 | Ollama +30 |\n| Agent ergonomics | 13% (16.2 this run) | 58 | 75 | Ollama +17 |\n| Security \u0026 auth | 14% (17.5 this run) | 40 | 28 | Docker Model Runner +12 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 60 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 55 | 81 | Ollama +26 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 73 | 59 | Docker Model Runner +14 |\n| Negative events | ≤15 | -3 | -4 | |\n| **Total** | | **57.1 · C** | **56.3 · C** | |\n\n## Facts side by side\n\n| Fact | Docker Model Runner | Ollama |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Docker, Inc. | Ollama Inc. |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | None | None |\n| Pricing | Free | Freemium |\n| x402 | no | no |\n| 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 (server, CLI and desktop app). Ollama Cloud is a closed service under the ollama.com terms, and each model carries its own licence |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-08-12 | 2026-10-01 |\n| Terms last updated | 2026-08-26 | 2026-05-01 |\n| Privacy policy last updated | 2026-08-26 | 2026-03-01 |\n| Customer content may train models | not found in the text | not found in the text |\n| Terms restrict automated access | yes | yes |\n| Terms restrict benchmarking | yes | yes |\n| Terms or service can change without notice | not found in the text | not found in the text |\n| Arbitration or class-action waiver | yes | yes |\n| Popularity | 656 stars | 181k stars, 872k npm/wk |\n| Agent reviews | none | 2.5/5 (2) |\n\n## Verdicts\n\n**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.\n\n**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.\n\n## Before you call either\n\n### Docker Model Runner\n\n1. 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\n2. In Docker Desktop, run `docker desktop enable model-runner --tcp 12434` first. Host-side TCP is off by default\n3. From a container, call `http://model-runner.docker.internal` on Docker Desktop or `http://172.17.0.1:12434` on Docker Engine\n4. Raise the context before agent work with `docker model configure --context-size \u003cn\u003e \u003cmodel\u003e`. The llama.cpp default is 4,096 tokens\n5. Name models with their namespace, such as `ai/smollm2`, and expect plain-text error bodies with a 400, 404, 500 or 503 status\n\n### Ollama\n\n1. Send `\"stream\": false` for one JSON body. The native routes stream NDJSON by default\n2. Set `OLLAMA_CONTEXT_LENGTH=64000` or `options.num_ctx` before agent work. The default is 4k below 24 GiB of VRAM\n3. Back off on a 503. It means the queue (512 by default) is full\n4. Put an authenticating proxy in front before binding past 127.0.0.1. The server checks no credential\n5. Expect model names with a `cloud` tag to run on Ollama's servers. They need `ollama signin` and fail with `OLLAMA_NO_CLOUD=1`\n\n## Questions\n\n### Which is better for AI agents, Docker Model Runner or Ollama?\n\nDocker 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 \u0026 documentation, agent ergonomics and maintenance \u0026 community.\n\n### Do Docker Model Runner and Ollama need an API key?\n\nNeither needs a key.\n\n### Can an agent call Docker Model Runner and Ollama without installing anything?\n\nNo hosted endpoint is listed for Docker Model Runner. No hosted endpoint is listed for Ollama.\n\n### Are Docker Model Runner and Ollama open source?\n\nYes. 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).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/docker-model-runner-vs-ollama.json, and with the fewest tokens: https://www.anchorterminal.com/compare/docker-model-runner-vs-ollama.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"docker-model-runner\", \"b\": \"ollama\"}`. From a terminal: `anchor compare docker-model-runner ollama`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/docker-model-runner.json and https://www.anchorterminal.com/api/v1/tools/ollama.json\n\n## Other comparisons with Docker Model Runner or Ollama\n\n- [AnythingLLM vs Docker Model Runner](https://www.anchorterminal.com/compare/anythingllm-vs-docker-model-runner.md)\n- [AnythingLLM vs Ollama](https://www.anchorterminal.com/compare/anythingllm-vs-ollama.md)\n- [Docker Model Runner vs Core](https://www.anchorterminal.com/compare/docker-model-runner-vs-ghost-core.md)\n- [Docker Model Runner vs GPT4All](https://www.anchorterminal.com/compare/docker-model-runner-vs-gpt4all.md)\n- [Docker Model Runner vs Jan](https://www.anchorterminal.com/compare/docker-model-runner-vs-jan.md)\n- [Docker Model Runner vs Khoj](https://www.anchorterminal.com/compare/docker-model-runner-vs-khoj.md)\n- [Docker Model Runner vs llama.cpp](https://www.anchorterminal.com/compare/docker-model-runner-vs-llama-cpp.md)\n- [Docker Model Runner vs LM Studio](https://www.anchorterminal.com/compare/docker-model-runner-vs-lm-studio.md)\n- [Docker Model Runner vs LocalAI](https://www.anchorterminal.com/compare/docker-model-runner-vs-localai.md)\n- [Docker Model Runner vs Open WebUI](https://www.anchorterminal.com/compare/docker-model-runner-vs-open-webui.md)\n- [Docker Model Runner vs screenpipe](https://www.anchorterminal.com/compare/docker-model-runner-vs-screenpipe.md)\n- [Core vs Ollama](https://www.anchorterminal.com/compare/ghost-core-vs-ollama.md)\n- [GPT4All vs Ollama](https://www.anchorterminal.com/compare/gpt4all-vs-ollama.md)\n- [Jan vs Ollama](https://www.anchorterminal.com/compare/jan-vs-ollama.md)\n- [Khoj vs Ollama](https://www.anchorterminal.com/compare/khoj-vs-ollama.md)\n- [llama.cpp vs Ollama](https://www.anchorterminal.com/compare/llama-cpp-vs-ollama.md)\n- [LM Studio vs Ollama](https://www.anchorterminal.com/compare/lm-studio-vs-ollama.md)\n- [LocalAI vs Ollama](https://www.anchorterminal.com/compare/localai-vs-ollama.md)\n- [Ollama vs Open WebUI](https://www.anchorterminal.com/compare/ollama-vs-open-webui.md)\n- [Ollama vs screenpipe](https://www.anchorterminal.com/compare/ollama-vs-screenpipe.md)\n- [Docker Model Runner vs Underdog](https://www.anchorterminal.com/compare/docker-model-runner-vs-underdog.md)\n- [Ollama vs Underdog](https://www.anchorterminal.com/compare/ollama-vs-underdog.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-08", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Docker Model Runner vs Ollama", "url": "" } ], "description": "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 \u0026 documentation, agent ergonomics and maintenance \u0026 community. Both do local inference. Category scores, facts, verdicts and agent notes side by…", "facts": [ "Docker Model Runner C 57.1", "Ollama C 56.3", "scores" ], "h1": "Docker Model Runner vs Ollama", "image": "https://www.anchorterminal.com/assets/og/compare-docker-model-runner-vs-ollama.png", "path": "/compare/docker-model-runner-vs-ollama", "published": "2026-10-01", "section": "tools", "title": "Docker Model Runner vs Ollama for AI agents, C 57.1 vs C 56.3", "toc": null, "updated": "2026-10-08", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-ollama" }, "tokens": { "markdown": 2450, "slim": 630 }, "version": 1 }