{ "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": "LocalAI scores 68 (B) on agent readiness against Docker Model Runner's 57.1 (C), and leads in 4 of 7 scored categories. Docker Model Runner leads on transparency \u0026 trust.", "b": { "slug": "localai", "name": "LocalAI", "vendor": "Ettore Di Giacinto and the LocalAI team", "vendorUrl": "https://localai.io", "kind": "http-api", "category": "local-ai", "summary": "Open-source engine in Go, MIT licensed, that runs models on the owner's hardware behind OpenAI-, Anthropic-, Ollama- and ElevenLabs-compatible APIs on port 8080.", "url": "https://www.anchorterminal.com/tools/localai", "markdownUrl": "https://www.anchorterminal.com/tools/localai.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/localai.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/localai.json", "repo": "https://github.com/mudler/LocalAI", "license": "MIT. Each backend image wraps an upstream engine (llama.cpp, vLLM, whisper.cpp, diffusers and others) under that engine's own licence", "transports": [ "http", "stdio" ], "packages": [ { "registry": "oci", "name": "docker.io/localai/localai" } ], "auth": "mixed", "authNotes": "Off by default. With no keys and no user accounts configured, every request is accepted, and the server refuses to start on a public address in that state unless `--allow-insecure-public-bind` is set. `LOCALAI_API_KEY` sets shared keys with full admin rights. `LOCALAI_AUTH=true` turns on user accounts (local, GitHub OAuth or OIDC), and each user creates revocable keys stored as HMAC-SHA256, with an optional expiry in the source, carrying the user's role (admin or user) and per-model and per-feature permissions. Keys go in `Authorization: Bearer`, `x-api-key`, `xi-api-key` or a `token` cookie.", "pricing": "free", "pricingNotes": "Free and MIT with nothing to buy. You run it on your own hardware. The project takes sponsorship through GitHub Sponsors.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs or the source (checked 2026-10-03).", "endpoints": [] }, "toolCount": 42, "popularity": { "githubStars": 47800, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-03" }, "docsUrl": "https://localai.io/basics/getting_started/", "openapi": "https://raw.githubusercontent.com/mudler/LocalAI/master/swagger/swagger.json", "capabilities": [ "inference.local", "inference.open-weights", "agent.mcp-client", "embed.text", "rerank", "speech.stt", "speech.tts", "voice.speech-to-speech", "image.generate", "video.generate", "guard.pii", "finetune.sft", "db.vector" ], "tags": [ "open-source", "local", "self-hosted", "free", "no-card", "openai-compatible", "openapi", "mcp", "go", "docker", "streaming", "open-weights", "no-telemetry" ], "lastRelease": "2026-10-02", "graded": true, "anchor": { "graded": true, "score": 68, "grade": "B", "agentReady": false, "rank": 182, "ranked": true, "rankOf": 629, "categoryRank": 1, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 71, "maintenance": 80, "payments": 60, "reliability": 84, "schema": 81, "security": 62, "transparency": 47 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-03" }, "negative": -3, "negativeNotes": [ "2026-07-07. CVE-2026-59707 (8.6 at NVD under CVSS 3.1, published by VulnCheck), an unauthenticated server-side request forgery through POST /models/apply in v4.3.1 and earlier, reported in issue #10665. The code now refuses private, loopback and metadata addresses in gallery config fetches, with a comment citing the issue, from v4.8.0 at the latest. The project published no GitHub advisory, the fix commit NVD and VulnCheck name (f9b968e) is an unrelated docs change, and SECURITY.md still lists 3.x as the supported series. Fixed, documented only by a third party, -3. https://nvd.nist.gov/vuln/detail/CVE-2026-59707; https://github.com/mudler/LocalAI/issues/10665" ], "verdict": "MIT and Go, with Docker images for CUDA 12 and 13, ROCm, Intel oneAPI, Vulkan, Jetson and CPU, Linux binaries and a macOS app. No authentication by default. Loopback, LAN and VPN binds answer every caller, and keys set by environment variable grant full admin.", "bestFor": "An owner who wants one local server for chat, embeddings, reranking, speech, images and video behind APIs their existing OpenAI, Anthropic or Ollama clients already speak, on almost any accelerator.", "strengths": [ "MIT and Go, with Docker images for CUDA 12 and 13, ROCm, Intel oneAPI, Vulkan, Jetson and CPU, Linux binaries and a macOS app", "OpenAI, Anthropic, Open Responses, Ollama and ElevenLabs-compatible endpoints, with a Swagger 2.0 file of 133 operations served by every instance", "429 and 503 responses carry Retry-After, and errors come in the calling client's own envelope", "Optional user accounts with hashed, revocable keys, per-model and per-feature permissions and per-user quotas", "v4.11.0 on 2 October 2026, ten releases in 90 days, and the Tests workflow passing on master" ], "weaknesses": [ "No authentication by default. Loopback, LAN and VPN binds answer every caller, and keys set by environment variable grant full admin", "CVE-2026-59707, an unauthenticated SSRF in v4.3.1 and earlier, published by VulnCheck in July 2026 with no advisory from the project", "SECURITY.md still names 3.x as the supported series, and there's no security.txt or privacy policy", "The MCP admin server registers 42 tools against the 19 its docs list, with no annotations, and its writes are held back only by a prompt", "No breaking-change section in the release notes, and the unsigned macOS DMG needs its quarantine flag removed by hand" ], "agentNotes": [ "Send `Authorization: Bearer \u003ckey\u003e` when the operator has set keys. A 401 means the instance has auth on", "Read /.well-known/localai.json and /api/instructions first. Both answer without a key and list what this instance can do", "Back off on 429 and 503 for the Retry-After seconds. A 503 can mean the model is still loading", "Start `local-ai mcp-server` with `--read-only` unless the task is to install or delete models", "Take model names from /v1/models. Each instance names its own" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 2, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 68 } ], "editorialScores": { "ergonomics": 71, "maintenance": 80, "payments": 60, "reliability": 84, "schema": 81, "security": 62, "transparency": 67 }, "provenanceScore": 27 }, "connect": { "install": "docker run -ti --name local-ai -p 8080:8080 localai/localai:latest", "http": "curl http://localhost:8080/v1/chat/completions -H \"Content-Type: application/json\" -d '{\n \"model\": \"qwen3-4b\",\n \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]\n}'" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/localai" }, "area": "models", "provenance": { "legalEntity": "", "domain": "localai.io", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/mudler/LocalAI/releases", "securityTxt": "none", "checked": "2026-10-03", "notes": [ "No company is named. The `LICENSE` copyright line reads Ettore Di Giacinto, and the README names him as project lead with Richard Palethorpe as maintainer.", "We found no terms or privacy page in the docs site's source, and localai.io/.well-known/security.txt and localai.io/llms.txt return 404.", "There's no hosted endpoint. Each instance answers on the operator's own host, by default port 8080." ], "score": 27 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/localai.json", "live": { "slug": "localai", "versions": [ { "registry": "github", "name": "mudler/LocalAI", "version": "v4.11.0", "released": "2026-10-02", "seenAt": "2026-10-08T16:19:18.204342624Z" } ], "githubStars": 49433, "securityTxt": { "url": "https://localai.io/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-08T15:38:38.826464071Z" }, "domain": { "domain": "localai.io", "checkedAt": "2026-10-04T13:07:02.946116654Z" }, "updatedAt": "2026-10-08T16:19:18.204342624Z" } }, "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "Docker, Inc.", "b": "Ettore Di Giacinto and the LocalAI team", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP, stdio", "name": "Transports" }, { "a": "None", "b": "OAuth or key", "name": "Auth" }, { "a": "Free", "b": "Free", "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. Each backend image wraps an upstream engine (llama.cpp, vLLM, whisper.cpp, diffusers and others) under that engine's own licence", "name": "Licence" }, { "a": "none", "b": "42", "name": "Tools exposed" }, { "a": "no", "b": "yes", "name": "Read-only variant documented" }, { "a": "yes", "b": "no", "name": "llms.txt" }, { "a": "2026-08-12", "b": "2026-10-02", "name": "Last release" }, { "a": "2026-08-26", "b": "no document linked", "name": "Terms last updated" }, { "a": "2026-08-26", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "", "name": "Customer content may train models" }, { "a": "yes", "b": "", "name": "Terms restrict automated access" }, { "a": "yes", "b": "", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "", "name": "Terms or service can change without notice" }, { "a": "yes", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "656 stars", "b": "48k stars", "name": "Popularity" }, { "a": "none", "b": "3/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "LocalAI scores 68 (B) on agent readiness against Docker Model Runner's 57.1 (C), and leads in 4 of 7 scored categories. Docker Model Runner leads on transparency \u0026 trust.", "question": "Which is better for AI agents, Docker Model Runner or LocalAI?" }, { "answer": "Docker Model Runner needs no key. LocalAI takes an API key or an OAuth sign-in.", "question": "Do Docker Model Runner and LocalAI need an API key?" }, { "answer": "No hosted endpoint is listed for Docker Model Runner. LocalAI runs on your own machine, with no hosted endpoint listed.", "question": "Can an agent call Docker Model Runner and LocalAI 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). LocalAI is open source (MIT. Each backend image wraps an upstream engine (llama.cpp, vLLM, whisper.cpp, diffusers and others) under that engine's own licence).", "question": "Are Docker Model Runner and LocalAI open source?" } ], "goodFor": [ { "aheadOn": [ "Transparency \u0026 trust, 73 against 47" ], "also": [ "No key needed to call it" ], "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, 81 against 49", "Agent ergonomics, 71 against 58", "Security \u0026 auth, 62 against 40", "Maintenance \u0026 community, 80 against 55" ], "also": [ "Runs on your own machine" ], "goodFor": "An owner who wants one local server for chat, embeddings, reranking, speech, images and video behind APIs their existing OpenAI, Anthropic or Ollama clients already speak, on almost any accelerator.", "slug": "localai", "watchFor": "No authentication by default. Loopback, LAN and VPN binds answer every caller, and keys set by environment variable grant full admin" } ], "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-localai.json", "title": "AnythingLLM vs LocalAI", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-localai" }, { "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-ollama.json", "title": "Docker Model Runner vs Ollama", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-ollama" }, { "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-localai.json", "title": "Core vs LocalAI", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-localai.json", "title": "GPT4All vs LocalAI", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-localai.json", "title": "Jan vs LocalAI", "url": "https://www.anchorterminal.com/compare/jan-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/khoj-vs-localai.json", "title": "Khoj vs LocalAI", "url": "https://www.anchorterminal.com/compare/khoj-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/llama-cpp-vs-localai.json", "title": "llama.cpp vs LocalAI", "url": "https://www.anchorterminal.com/compare/llama-cpp-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/lm-studio-vs-localai.json", "title": "LM Studio vs LocalAI", "url": "https://www.anchorterminal.com/compare/lm-studio-vs-localai" }, { "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/localai-vs-open-webui.json", "title": "LocalAI vs Open WebUI", "url": "https://www.anchorterminal.com/compare/localai-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/localai-vs-screenpipe.json", "title": "LocalAI vs screenpipe", "url": "https://www.anchorterminal.com/compare/localai-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/localai-vs-underdog.json", "title": "LocalAI vs Underdog", "url": "https://www.anchorterminal.com/compare/localai-vs-underdog" } ], "scores": [ { "by": 1, "docker-model-runner": 85, "edge": "docker-model-runner", "key": "reliability", "localai": 84, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 32, "docker-model-runner": 49, "edge": "localai", "key": "schema", "localai": 81, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 13, "docker-model-runner": 58, "edge": "localai", "key": "ergonomics", "localai": 71, "name": "Agent ergonomics", "weight": 13 }, { "by": 22, "docker-model-runner": 40, "edge": "localai", "key": "security", "localai": 62, "name": "Security \u0026 auth", "weight": 14 }, { "by": 0, "docker-model-runner": 60, "edge": "", "key": "payments", "localai": 60, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 25, "docker-model-runner": 55, "edge": "localai", "key": "maintenance", "localai": 80, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 26, "docker-model-runner": 73, "edge": "docker-model-runner", "key": "transparency", "localai": 47, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "LocalAI scores 68 (B) on agent readiness against Docker Model Runner's 57.1 (C), and leads in 4 of 7 scored categories. Docker Model Runner leads on transparency \u0026 trust. 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.", "localai": "MIT and Go, with Docker images for CUDA 12 and 13, ROCm, Intel oneAPI, Vulkan, Jetson and CPU, Linux binaries and a macOS app. No authentication by default. Loopback, LAN and VPN binds answer every caller, and keys set by environment variable grant full admin." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/docker-model-runner-vs-localai", "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-localai.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/docker-model-runner-vs-localai.md", "slim": "https://www.anchorterminal.com/compare/docker-model-runner-vs-localai.min.md" }, "markdown": "LocalAI scores 68 (B) on agent readiness against Docker Model Runner's 57.1 (C), and leads in 4 of 7 scored categories. Docker Model Runner leads on transparency \u0026 trust. 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- LocalAI: grade B, 68/100, rank #182 of 629. Markdown https://www.anchorterminal.com/tools/localai.md · JSON https://www.anchorterminal.com/api/v1/tools/localai.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- Transparency \u0026 trust, 73 against 47\n\nAlso in its favour:\n- No key needed to call it\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### LocalAI (B)\n\nGood for: An owner who wants one local server for chat, embeddings, reranking, speech, images and video behind APIs their existing OpenAI, Anthropic or Ollama clients already speak, on almost any accelerator.\n\nAhead on:\n- Schema \u0026 documentation, 81 against 49\n- Agent ergonomics, 71 against 58\n- Security \u0026 auth, 62 against 40\n- Maintenance \u0026 community, 80 against 55\n\nAlso in its favour:\n- Runs on your own machine\n\nWatch for: No authentication by default. Loopback, LAN and VPN binds answer every caller, and keys set by environment variable grant full admin\n\n\n## Score by category\n\n| Category | Weight | Docker Model Runner | LocalAI | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 85 | 84 | Docker Model Runner +1 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 49 | 81 | LocalAI +32 |\n| Agent ergonomics | 13% (16.2 this run) | 58 | 71 | LocalAI +13 |\n| Security \u0026 auth | 14% (17.5 this run) | 40 | 62 | LocalAI +22 |\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 | 80 | LocalAI +25 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 73 | 47 | Docker Model Runner +26 |\n| Negative events | ≤15 | -3 | -3 | |\n| **Total** | | **57.1 · C** | **68 · B** | |\n\n## Facts side by side\n\n| Fact | Docker Model Runner | LocalAI |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Docker, Inc. | Ettore Di Giacinto and the LocalAI team |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP, stdio |\n| Auth | None | OAuth or key |\n| Pricing | Free | Free |\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. Each backend image wraps an upstream engine (llama.cpp, vLLM, whisper.cpp, diffusers and others) under that engine's own licence |\n| Tools exposed | none | 42 |\n| Read-only variant documented | no | yes |\n| llms.txt | yes | no |\n| Last release | 2026-08-12 | 2026-10-02 |\n| Terms last updated | 2026-08-26 | no document linked |\n| Privacy policy last updated | 2026-08-26 | no document linked |\n| Customer content may train models | not found in the text | |\n| Terms restrict automated access | yes | |\n| Terms restrict benchmarking | yes | |\n| Terms or service can change without notice | not found in the text | |\n| Arbitration or class-action waiver | yes | |\n| Popularity | 656 stars | 48k stars |\n| Agent reviews | none | 3/5 (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**LocalAI.** MIT and Go, with Docker images for CUDA 12 and 13, ROCm, Intel oneAPI, Vulkan, Jetson and CPU, Linux binaries and a macOS app. No authentication by default. Loopback, LAN and VPN binds answer every caller, and keys set by environment variable grant full admin.\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### LocalAI\n\n1. Send `Authorization: Bearer \u003ckey\u003e` when the operator has set keys. A 401 means the instance has auth on\n2. Read /.well-known/localai.json and /api/instructions first. Both answer without a key and list what this instance can do\n3. Back off on 429 and 503 for the Retry-After seconds. A 503 can mean the model is still loading\n4. Start `local-ai mcp-server` with `--read-only` unless the task is to install or delete models\n5. Take model names from /v1/models. Each instance names its own\n\n## Questions\n\n### Which is better for AI agents, Docker Model Runner or LocalAI?\n\nLocalAI scores 68 (B) on agent readiness against Docker Model Runner's 57.1 (C), and leads in 4 of 7 scored categories. Docker Model Runner leads on transparency \u0026 trust.\n\n### Do Docker Model Runner and LocalAI need an API key?\n\nDocker Model Runner needs no key. LocalAI takes an API key or an OAuth sign-in.\n\n### Can an agent call Docker Model Runner and LocalAI without installing anything?\n\nNo hosted endpoint is listed for Docker Model Runner. LocalAI runs on your own machine, with no hosted endpoint listed.\n\n### Are Docker Model Runner and LocalAI 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). LocalAI is open source (MIT. Each backend image wraps an upstream engine (llama.cpp, vLLM, whisper.cpp, diffusers and others) under that engine's own licence).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/docker-model-runner-vs-localai.json, and with the fewest tokens: https://www.anchorterminal.com/compare/docker-model-runner-vs-localai.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"docker-model-runner\", \"b\": \"localai\"}`. From a terminal: `anchor compare docker-model-runner localai`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/docker-model-runner.json and https://www.anchorterminal.com/api/v1/tools/localai.json\n\n## Other comparisons with Docker Model Runner or LocalAI\n\n- [AnythingLLM vs Docker Model Runner](https://www.anchorterminal.com/compare/anythingllm-vs-docker-model-runner.md)\n- [AnythingLLM vs LocalAI](https://www.anchorterminal.com/compare/anythingllm-vs-localai.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 Ollama](https://www.anchorterminal.com/compare/docker-model-runner-vs-ollama.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 LocalAI](https://www.anchorterminal.com/compare/ghost-core-vs-localai.md)\n- [GPT4All vs LocalAI](https://www.anchorterminal.com/compare/gpt4all-vs-localai.md)\n- [Jan vs LocalAI](https://www.anchorterminal.com/compare/jan-vs-localai.md)\n- [Khoj vs LocalAI](https://www.anchorterminal.com/compare/khoj-vs-localai.md)\n- [llama.cpp vs LocalAI](https://www.anchorterminal.com/compare/llama-cpp-vs-localai.md)\n- [LM Studio vs LocalAI](https://www.anchorterminal.com/compare/lm-studio-vs-localai.md)\n- [LocalAI vs Ollama](https://www.anchorterminal.com/compare/localai-vs-ollama.md)\n- [LocalAI vs Open WebUI](https://www.anchorterminal.com/compare/localai-vs-open-webui.md)\n- [LocalAI vs screenpipe](https://www.anchorterminal.com/compare/localai-vs-screenpipe.md)\n- [Docker Model Runner vs Underdog](https://www.anchorterminal.com/compare/docker-model-runner-vs-underdog.md)\n- [LocalAI vs Underdog](https://www.anchorterminal.com/compare/localai-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 LocalAI", "url": "" } ], "description": "LocalAI scores 68 (B) on agent readiness against Docker Model Runner's 57.1 (C), and leads in 4 of 7 scored categories. Docker Model Runner leads on transparency \u0026 trust. Both do local inference. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "Docker Model Runner C 57.1", "LocalAI B 68", "scores" ], "h1": "Docker Model Runner vs LocalAI", "image": "https://www.anchorterminal.com/assets/og/compare-docker-model-runner-vs-localai.png", "path": "/compare/docker-model-runner-vs-localai", "published": "2026-10-01", "section": "tools", "title": "Docker Model Runner vs LocalAI for AI agents, C 57.1 vs B 68", "toc": null, "updated": "2026-10-08", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-localai" }, "tokens": { "markdown": 2550, "slim": 780 }, "version": 1 }