{ "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": 623, "ranked": true, "rankOf": 954, "categoryRank": 9, "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", "versions": [ { "registry": "github", "name": "docker/model-runner", "version": "v1.2.8", "released": "2026-08-12", "seenAt": "2026-10-09T16:50:12.020831953Z" } ], "githubStars": 657, "securityTxt": { "url": "https://docker.com/.well-known/security.txt", "state": "valid", "expires": "2030-01-01T05:00:00.000Z", "checkedAt": "2026-10-10T15:40:43.495346525Z" }, "llmsTxt": { "url": "https://docs.docker.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-10T14:04:05.872909983Z" }, "pages": [ { "url": "https://www.docker.com/pricing/", "kind": "pricing", "status": 200, "checkedAt": "2026-10-09T18:49:43.781722821Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "308829465f88" }, { "url": "https://www.docker.com/legal/docker-subscription-service-agreement/", "kind": "terms", "status": 200, "checkedAt": "2026-10-09T18:49:37.67000485Z", "changedAt": "2026-10-09T18:49:37.67000485Z", "fingerprint": "1d7fb094eaac" } ], "updatedAt": "2026-10-10T15:40:43.495346525Z" } }, "answer": "Lemonade scores 63.8 (B) 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 \u0026 trust.", "b": { "slug": "lemonade", "name": "Lemonade", "vendor": "AMD and the Lemonade community", "vendorUrl": "https://lemonade-server.ai", "kind": "http-api", "category": "local-ai", "summary": "Open-source local AI server from AMD and community contributors. It runs text, speech and image models on the owner's CPU, GPU or NPU behind OpenAI-, Anthropic- and Ollama-compatible APIs and an MCP endpoint on port 13305.", "url": "https://www.anchorterminal.com/tools/lemonade", "markdownUrl": "https://www.anchorterminal.com/tools/lemonade.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/lemonade.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/lemonade.json", "repo": "https://github.com/lemonade-sdk/lemonade", "license": "Apache 2.0. Each backend (llama.cpp, whisper.cpp, stable-diffusion.cpp, FastFlowLM and others) is downloaded separately under its own licence", "transports": [ "http" ], "packages": [ { "registry": "oci", "name": "ghcr.io/lemonade-sdk/lemonade-server" } ], "auth": "api-key", "authNotes": "Off by default. With no key set, every endpoint answers without authentication, on a default bind of localhost. `LEMONADE_API_KEY` sets one bearer key for the regular API (`/api/*`, `/v0/*`, `/v1/*`, `/mcp` and `/metrics`). `LEMONADE_ADMIN_API_KEY` sets a second key for the internal control endpoints (`/internal/*`), and without it the regular key reaches those too. Both are environment variables, so there are no per-user keys. The docs tell WebSocket clients to pass `?api_key=KEY` in the URL.", "pricing": "free", "pricingNotes": "Free and Apache 2.0 with nothing to buy and no account. You run it on your own hardware. Cloud Offload, which is optional and experimental, bills through the owner's own keys at whichever cloud provider they add.", "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": 6, "popularity": { "githubStars": 5800, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-08" }, "docsUrl": "https://lemonade-server.ai/docs/", "capabilities": [ "inference.local", "inference.open-weights", "embed.text", "rerank", "speech.stt", "speech.tts", "image.generate" ], "tags": [ "open-source", "local", "self-hosted", "free", "no-card", "openai-compatible", "mcp", "streaming", "open-weights", "amd", "npu", "docker" ], "lastRelease": "2026-10-07", "graded": true, "anchor": { "graded": true, "score": 63.8, "grade": "B", "agentReady": false, "rank": 373, "ranked": true, "rankOf": 954, "categoryRank": 2, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 70, "maintenance": 76, "payments": 60, "reliability": 75, "schema": 70, "security": 36, "transparency": 64 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "Apache 2.0, with weekly releases, installers for Windows, macOS and five Linux routes, and a six-tool MCP endpoint whose descriptions steer a caller away from accidental multi-gigabyte downloads. Authentication is off by default, the repository has no security policy, and the docs tell WebSocket clients to pass the key in the URL.", "bestFor": "An owner with AMD hardware (Ryzen AI NPUs, Radeon or Strix Halo) who wants one local server for chat, speech and images that existing OpenAI, Anthropic or Ollama clients can call, and for MCP clients that want local models as tools.", "strengths": [ "Apache 2.0, with OpenAI, Anthropic Messages, Ollama and llama.cpp-compatible routes on one port (13305)", "`POST /mcp` exposes six tools over Streamable HTTP, and omitting `model` reuses a loaded or downloaded model before any download", "Every running server returns its own Markdown API reference at `GET /v1/docs` and through the `lemonade_docs` tool, so it matches the installed version", "Stable release v2026.41.1 on 7 October 2026 on a weekly cadence, each with a Breaking Changes section in its notes", "Telemetry is off by default and exports OTLP traces only to an endpoint the operator sets, with switches to redact prompts and outputs" ], "weaknesses": [ "No authentication by default. With no key set, every route answers, including `/internal/*` shutdown and configuration", "GitHub reports no `SECURITY.md`, and we found no security.txt, advisory or disclosure address", "The docs tell WebSocket clients to send the key as `?api_key=KEY` in the URL", "No OpenAPI file in the repository, and no `readOnlyHint` or `destructiveHint` on the MCP tools", "The main build and test workflow's badge read failing on main on 8 October 2026, with 411 issues open" ], "agentNotes": [ "Call `lemonade_list_models` (or `GET /v1/models`) before naming a model. A wrong name with `allow_download: true` can start a multi-gigabyte download", "Send `Authorization: Bearer \u003ckey\u003e` when the operator has set `LEMONADE_API_KEY`. `/internal/*` needs the admin key when one is set", "Use `POST /v1/chat/completions` for streamed tokens, embeddings and speech. The MCP endpoint ignores `stream` and has no embeddings or text-to-speech tool", "Pass `output_dir` to `lemonade_generate_image` and `lemonade_omni` to get file paths in place of inline base64. Writes stay inside the MCP media sandbox", "Read `GET /v1/docs` on the running server for the reference that matches its version. Weekly releases change behaviour" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 63.8 } ], "editorialScores": { "ergonomics": 70, "maintenance": 76, "payments": 60, "reliability": 75, "schema": 70, "security": 36, "transparency": 70 }, "provenanceScore": 57 }, "connect": { "install": "winget install --id AMD.LemonadeServer -e", "http": "curl http://localhost:13305/api/v1/chat/completions -H \"Content-Type: application/json\" -d '{\"model\": \"your-model-name\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello\"}]}'", "claudeCode": "lemonade launch claude" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/lemonade" }, "area": "models", "provenance": { "legalEntity": "Advanced Micro Devices, Inc.", "domain": "lemonade-server.ai", "domainRegistered": "2025-05-12", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/lemonade-sdk/lemonade/releases", "securityTxt": "none", "checked": "2026-10-08", "notes": [ "The website footer reads \"© 2026 AMD. Licensed under Apache 2.0\", and `contrib/debian/copyright` in the repository names Advanced Micro Devices, Inc. The code lives in the lemonade-sdk organisation on GitHub, and the README calls it a community project with optimisations by AMD engineers.", "We found no terms of service and no privacy policy for the software or the website. The home page and its footer link to neither, so both fields are empty.", "lemonade-server.ai/.well-known/security.txt, /security.txt and /llms.txt return 404.", "RDAP gives a registration date of 2025-05-12 for lemonade-server.ai, with Porkbun LLC as registrar and the registrant behind a privacy service.", "There's no hosted endpoint. Each instance answers on the owner's own machine, by default localhost port 13305." ], "score": 57 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/lemonade.json", "live": { "slug": "lemonade", "versions": [ { "registry": "github", "name": "lemonade-sdk/lemonade", "version": "v2026.41.1", "released": "2026-10-07", "seenAt": "2026-10-09T17:01:56.36736009Z" } ], "githubStars": 5851, "securityTxt": { "url": "https://lemonade-server.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-10T15:40:47.029173466Z" }, "updatedAt": "2026-10-10T15:40:47.029173466Z" } }, "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "Docker, Inc.", "b": "AMD and the Lemonade community", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "API 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": "Apache 2.0. Each backend (llama.cpp, whisper.cpp, stable-diffusion.cpp, FastFlowLM and others) is downloaded separately under its own licence", "name": "Licence" }, { "a": "none", "b": "6", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "no", "name": "llms.txt" }, { "a": "2026-08-12", "b": "2026-10-07", "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": "5.8k stars", "name": "Popularity" } ], "faq": [ { "answer": "Lemonade scores 63.8 (B) 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 \u0026 trust.", "question": "Which is better for AI agents, Docker Model Runner or Lemonade?" }, { "answer": "Docker Model Runner needs no key. Lemonade needs an API key.", "question": "Do Docker Model Runner and Lemonade need an API key?" }, { "answer": "No hosted endpoint is listed for Docker Model Runner. No hosted endpoint is listed for Lemonade.", "question": "Can an agent call Docker Model Runner and Lemonade 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). Lemonade is open source (Apache 2.0. Each backend (llama.cpp, whisper.cpp, stable-diffusion.cpp, FastFlowLM and others) is downloaded separately under its own licence).", "question": "Are Docker Model Runner and Lemonade open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 85 against 75", "Transparency \u0026 trust, 73 against 64" ], "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, 70 against 49", "Agent ergonomics, 70 against 58", "Maintenance \u0026 community, 76 against 55" ], "also": [ "No incidents deducted, where Docker Model Runner loses 3 points for them" ], "goodFor": "An owner with AMD hardware (Ryzen AI NPUs, Radeon or Strix Halo) who wants one local server for chat, speech and images that existing OpenAI, Anthropic or Ollama clients can call, and for MCP clients that want local models as tools.", "slug": "lemonade", "watchFor": "No authentication by default. With no key set, every route answers, including `/internal/*` shutdown and configuration" } ], "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-lemonade.json", "title": "AnythingLLM vs Lemonade", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-foundry-local.json", "title": "Docker Model Runner vs Foundry Local", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-foundry-local" }, { "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-koboldcpp.json", "title": "Docker Model Runner vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-koboldcpp" }, { "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-mlx-lm.json", "title": "Docker Model Runner vs MLX LM", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-mlx-lm" }, { "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/docker-model-runner-vs-text-generation-webui.json", "title": "Docker Model Runner vs TextGen", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-vllm.json", "title": "Docker Model Runner vs vLLM", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-vllm" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-lemonade.json", "title": "Foundry Local vs Lemonade", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-lemonade.json", "title": "Core vs Lemonade", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-lemonade.json", "title": "GPT4All vs Lemonade", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/jan-vs-lemonade.json", "title": "Jan vs Lemonade", "url": "https://www.anchorterminal.com/compare/jan-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/khoj-vs-lemonade.json", "title": "Khoj vs Lemonade", "url": "https://www.anchorterminal.com/compare/khoj-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/koboldcpp-vs-lemonade.json", "title": "KoboldCpp vs Lemonade", "url": "https://www.anchorterminal.com/compare/koboldcpp-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-llama-cpp.json", "title": "Lemonade vs llama.cpp", "url": "https://www.anchorterminal.com/compare/lemonade-vs-llama-cpp" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-lm-studio.json", "title": "Lemonade vs LM Studio", "url": "https://www.anchorterminal.com/compare/lemonade-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-localai.json", "title": "Lemonade vs LocalAI", "url": "https://www.anchorterminal.com/compare/lemonade-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-mlx-lm.json", "title": "Lemonade vs MLX LM", "url": "https://www.anchorterminal.com/compare/lemonade-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-ollama.json", "title": "Lemonade vs Ollama", "url": "https://www.anchorterminal.com/compare/lemonade-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-open-webui.json", "title": "Lemonade vs Open WebUI", "url": "https://www.anchorterminal.com/compare/lemonade-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-screenpipe.json", "title": "Lemonade vs screenpipe", "url": "https://www.anchorterminal.com/compare/lemonade-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-text-generation-webui.json", "title": "Lemonade vs TextGen", "url": "https://www.anchorterminal.com/compare/lemonade-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/lemonade-vs-vllm.json", "title": "Lemonade vs vLLM", "url": "https://www.anchorterminal.com/compare/lemonade-vs-vllm" }, { "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/lemonade-vs-underdog.json", "title": "Lemonade vs Underdog", "url": "https://www.anchorterminal.com/compare/lemonade-vs-underdog" } ], "scores": [ { "by": 10, "docker-model-runner": 85, "edge": "docker-model-runner", "key": "reliability", "lemonade": 75, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 21, "docker-model-runner": 49, "edge": "lemonade", "key": "schema", "lemonade": 70, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 12, "docker-model-runner": 58, "edge": "lemonade", "key": "ergonomics", "lemonade": 70, "name": "Agent ergonomics", "weight": 13 }, { "by": 4, "docker-model-runner": 40, "edge": "docker-model-runner", "key": "security", "lemonade": 36, "name": "Security \u0026 auth", "weight": 14 }, { "by": 0, "docker-model-runner": 60, "edge": "", "key": "payments", "lemonade": 60, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 21, "docker-model-runner": 55, "edge": "lemonade", "key": "maintenance", "lemonade": 76, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 9, "docker-model-runner": 73, "edge": "docker-model-runner", "key": "transparency", "lemonade": 64, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Lemonade scores 63.8 (B) 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 \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.", "lemonade": "Apache 2.0, with weekly releases, installers for Windows, macOS and five Linux routes, and a six-tool MCP endpoint whose descriptions steer a caller away from accidental multi-gigabyte downloads. Authentication is off by default, the repository has no security policy, and the docs tell WebSocket clients to pass the key in the URL." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/docker-model-runner-vs-lemonade", "json": "https://www.anchorterminal.com/compare/docker-model-runner-vs-lemonade.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/docker-model-runner-vs-lemonade.md", "slim": "https://www.anchorterminal.com/compare/docker-model-runner-vs-lemonade.min.md" }, "markdown": "Lemonade scores 63.8 (B) 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 \u0026 trust. Both do local inference.\n\n- Docker Model Runner: grade C, 57.1/100, rank #623 of 954. Markdown https://www.anchorterminal.com/tools/docker-model-runner.md · JSON https://www.anchorterminal.com/api/v1/tools/docker-model-runner.json\n- Lemonade: grade B, 63.8/100, rank #373 of 954. Markdown https://www.anchorterminal.com/tools/lemonade.md · JSON https://www.anchorterminal.com/api/v1/tools/lemonade.json\n- Best local AI models and assistants: https://www.anchorterminal.com/best/local-ai/index.md\n- All 184 local ai comparisons: https://www.anchorterminal.com/compare/local-ai/index.md\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 75\n- Transparency \u0026 trust, 73 against 64\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### Lemonade (B)\n\nGood for: An owner with AMD hardware (Ryzen AI NPUs, Radeon or Strix Halo) who wants one local server for chat, speech and images that existing OpenAI, Anthropic or Ollama clients can call, and for MCP clients that want local models as tools.\n\nAhead on:\n- Schema \u0026 documentation, 70 against 49\n- Agent ergonomics, 70 against 58\n- Maintenance \u0026 community, 76 against 55\n\nAlso in its favour:\n- No incidents deducted, where Docker Model Runner loses 3 points for them\n\nWatch for: No authentication by default. With no key set, every route answers, including `/internal/*` shutdown and configuration\n\n\n## Score by category\n\n| Category | Weight | Docker Model Runner | Lemonade | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 85 | 75 | Docker Model Runner +10 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 49 | 70 | Lemonade +21 |\n| Agent ergonomics | 13% (16.2 this run) | 58 | 70 | Lemonade +12 |\n| Security \u0026 auth | 14% (17.5 this run) | 40 | 36 | Docker Model Runner +4 |\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 | 76 | Lemonade +21 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 73 | 64 | Docker Model Runner +9 |\n| Negative events | ≤15 | -3 | 0 | |\n| **Total** | | **57.1 · C** | **63.8 · B** | |\n\n## Facts side by side\n\n| Fact | Docker Model Runner | Lemonade |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Docker, Inc. | AMD and the Lemonade community |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | None | API 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 | Apache 2.0. Each backend (llama.cpp, whisper.cpp, stable-diffusion.cpp, FastFlowLM and others) is downloaded separately under its own licence |\n| Tools exposed | none | 6 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| Last release | 2026-08-12 | 2026-10-07 |\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 | 5.8k stars |\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**Lemonade.** Apache 2.0, with weekly releases, installers for Windows, macOS and five Linux routes, and a six-tool MCP endpoint whose descriptions steer a caller away from accidental multi-gigabyte downloads. Authentication is off by default, the repository has no security policy, and the docs tell WebSocket clients to pass the key in the URL.\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### Lemonade\n\n1. Call `lemonade_list_models` (or `GET /v1/models`) before naming a model. A wrong name with `allow_download: true` can start a multi-gigabyte download\n2. Send `Authorization: Bearer \u003ckey\u003e` when the operator has set `LEMONADE_API_KEY`. `/internal/*` needs the admin key when one is set\n3. Use `POST /v1/chat/completions` for streamed tokens, embeddings and speech. The MCP endpoint ignores `stream` and has no embeddings or text-to-speech tool\n4. Pass `output_dir` to `lemonade_generate_image` and `lemonade_omni` to get file paths in place of inline base64. Writes stay inside the MCP media sandbox\n5. Read `GET /v1/docs` on the running server for the reference that matches its version. Weekly releases change behaviour\n\n## Questions\n\n### Which is better for AI agents, Docker Model Runner or Lemonade?\n\nLemonade scores 63.8 (B) 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 \u0026 trust.\n\n### Do Docker Model Runner and Lemonade need an API key?\n\nDocker Model Runner needs no key. Lemonade needs an API key.\n\n### Can an agent call Docker Model Runner and Lemonade without installing anything?\n\nNo hosted endpoint is listed for Docker Model Runner. No hosted endpoint is listed for Lemonade.\n\n### Are Docker Model Runner and Lemonade 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). Lemonade is open source (Apache 2.0. Each backend (llama.cpp, whisper.cpp, stable-diffusion.cpp, FastFlowLM and others) is downloaded separately under its own licence).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/docker-model-runner-vs-lemonade.json, and with the fewest tokens: https://www.anchorterminal.com/compare/docker-model-runner-vs-lemonade.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"docker-model-runner\", \"b\": \"lemonade\"}`. From a terminal: `anchor compare docker-model-runner lemonade`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/docker-model-runner.json and https://www.anchorterminal.com/api/v1/tools/lemonade.json\n\n## Other comparisons with Docker Model Runner or Lemonade\n\n- [AnythingLLM vs Docker Model Runner](https://www.anchorterminal.com/compare/anythingllm-vs-docker-model-runner.md)\n- [AnythingLLM vs Lemonade](https://www.anchorterminal.com/compare/anythingllm-vs-lemonade.md)\n- [Docker Model Runner vs Foundry Local](https://www.anchorterminal.com/compare/docker-model-runner-vs-foundry-local.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 KoboldCpp](https://www.anchorterminal.com/compare/docker-model-runner-vs-koboldcpp.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 MLX LM](https://www.anchorterminal.com/compare/docker-model-runner-vs-mlx-lm.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- [Docker Model Runner vs TextGen](https://www.anchorterminal.com/compare/docker-model-runner-vs-text-generation-webui.md)\n- [Docker Model Runner vs vLLM](https://www.anchorterminal.com/compare/docker-model-runner-vs-vllm.md)\n- [Foundry Local vs Lemonade](https://www.anchorterminal.com/compare/foundry-local-vs-lemonade.md)\n- [Core vs Lemonade](https://www.anchorterminal.com/compare/ghost-core-vs-lemonade.md)\n- [GPT4All vs Lemonade](https://www.anchorterminal.com/compare/gpt4all-vs-lemonade.md)\n- [Jan vs Lemonade](https://www.anchorterminal.com/compare/jan-vs-lemonade.md)\n- [Khoj vs Lemonade](https://www.anchorterminal.com/compare/khoj-vs-lemonade.md)\n- [KoboldCpp vs Lemonade](https://www.anchorterminal.com/compare/koboldcpp-vs-lemonade.md)\n- [Lemonade vs llama.cpp](https://www.anchorterminal.com/compare/lemonade-vs-llama-cpp.md)\n- [Lemonade vs LM Studio](https://www.anchorterminal.com/compare/lemonade-vs-lm-studio.md)\n- [Lemonade vs LocalAI](https://www.anchorterminal.com/compare/lemonade-vs-localai.md)\n- [Lemonade vs MLX LM](https://www.anchorterminal.com/compare/lemonade-vs-mlx-lm.md)\n- [Lemonade vs Ollama](https://www.anchorterminal.com/compare/lemonade-vs-ollama.md)\n- [Lemonade vs Open WebUI](https://www.anchorterminal.com/compare/lemonade-vs-open-webui.md)\n- [Lemonade vs screenpipe](https://www.anchorterminal.com/compare/lemonade-vs-screenpipe.md)\n- [Lemonade vs TextGen](https://www.anchorterminal.com/compare/lemonade-vs-text-generation-webui.md)\n- [Lemonade vs vLLM](https://www.anchorterminal.com/compare/lemonade-vs-vllm.md)\n- [Docker Model Runner vs Underdog](https://www.anchorterminal.com/compare/docker-model-runner-vs-underdog.md)\n- [Lemonade vs Underdog](https://www.anchorterminal.com/compare/lemonade-vs-underdog.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-10", "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 Lemonade", "url": "" } ], "description": "Lemonade scores 63.8 (B) to Docker Model Runner's 57.1 (C) for local inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Docker Model Runner C 57.1", "Lemonade B 63.8", "scores" ], "h1": "Docker Model Runner vs Lemonade", "image": "https://www.anchorterminal.com/assets/og/compare-docker-model-runner-vs-lemonade.png", "path": "/compare/docker-model-runner-vs-lemonade", "published": "2026-10-01", "section": "tools", "title": "Docker Model Runner vs Lemonade for AI agents (2026) | Anchor Terminal", "toc": null, "updated": "2026-10-10", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-lemonade" }, "tokens": { "markdown": 3000, "slim": 780 }, "version": 1 }