{
  "data": {
    "a": {
      "slug": "anythingllm",
      "name": "AnythingLLM",
      "vendor": "Mintplex Labs",
      "vendorUrl": "https://anythingllm.com",
      "kind": "platform",
      "category": "local-ai",
      "summary": "Open-source app for chatting with documents using local or hosted models. Available as a desktop app or a self-hosted server.",
      "url": "https://www.anchorterminal.com/tools/anythingllm",
      "markdownUrl": "https://www.anchorterminal.com/tools/anythingllm.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/anythingllm.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/anythingllm.json",
      "repo": "https://github.com/Mintplex-Labs/anything-llm",
      "license": "MIT (server, document collector, frontend and Docker image). The desktop app ships under Mintplex Labs' own terms of use, which call its source code a trade secret and forbid reverse engineering",
      "transports": [
        "http"
      ],
      "packages": [
        {
          "registry": "oci",
          "name": "mintplexlabs/anythingllm"
        },
        {
          "registry": "oci",
          "name": "ghcr.io/mintplex-labs/anything-llm"
        }
      ],
      "auth": "api-key",
      "authNotes": "The developer API under /api/v1 takes a key in `Authorization: Bearer`. An admin creates keys in the UI. SECURITY.md says each key has full, unrestricted access to the whole /v1 surface, equivalent to admin, and the database stores keys in plain text with no scopes or expiry. A key is revoked by deleting it. The instance itself runs with no password, one password or multi-user accounts, chosen at onboarding, and the desktop backend listens on 127.0.0.1:3001 unless network discovery is switched on.",
      "pricing": "freemium",
      "pricingNotes": "The desktop app and the Docker server are free, with no account. AnythingLLM Cloud, a private managed instance on AWS, costs $50 a month (Basic, bring your own model key) or $99 a month (Pro, 72-hour support SLA), with Enterprise on request. The pricing page shows no trial or free tier for Cloud, and checkout goes through my.mintplexlabs.com (checked 2026-10-03).",
      "priceSummary": "$50 / 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": 66600,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-03"
      },
      "docsUrl": "https://docs.anythingllm.com",
      "openapi": "https://raw.githubusercontent.com/Mintplex-Labs/anything-llm/master/server/swagger/openapi.json",
      "capabilities": [
        "inference.local",
        "memory.search",
        "agent.mcp-client",
        "memory.user",
        "inference.open-weights"
      ],
      "tags": [
        "open-source",
        "local",
        "self-hosted",
        "hosted",
        "desktop",
        "docker",
        "openapi",
        "openai-compatible",
        "rag",
        "mcp-client",
        "freemium",
        "telemetry-default-on"
      ],
      "lastRelease": "2026-10-01",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 53.3,
        "grade": "D",
        "agentReady": false,
        "rank": 544,
        "ranked": true,
        "rankOf": 722,
        "categoryRank": 7,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 46,
          "maintenance": 78,
          "payments": 60,
          "reliability": 67,
          "schema": 57,
          "security": 38,
          "transparency": 59
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-03"
        },
        "negative": -3,
        "negativeNotes": [
          "2026-04-15 to 2026-05-21. Ten advisories published in the last year, all fixed, among them CVE-2026-48116 (GHSA-6hrp-7mw6-8v59, CVSS 7.5), code execution through a `--pre` argument passed to ripgrep by the filesystem-search-files agent skill in 1.12.1 and earlier, fixed on 20 May 2026 (commit 94ed62d3) and published on 21 May, and GHSA-4q6m-qh3w-9gf5 (15 April 2026), a DOM XSS in chart rendering that prompt injection could trigger. Fixed and published inside six months, so a small deduction, -3. https://github.com/Mintplex-Labs/anything-llm/security/advisories/GHSA-6hrp-7mw6-8v59; https://github.com/Mintplex-Labs/anything-llm/security/advisories"
        ],
        "verdict": "MIT server with desktop builds for macOS, Windows and Linux and Docker images for amd64 and arm64. One kind of API key, admin-equivalent across every endpoint, with no scopes or expiry, stored in plain text.",
        "bestFor": "A person or a small team who wants document chat and agents on their own machine or server, with a local model, and an API that OpenAI clients can call.",
        "strengths": [
          "MIT server with desktop builds for macOS, Windows and Linux and Docker images for amd64 and arm64",
          "63 developer API operations in OpenAPI 3.0, served at /api/docs on every instance",
          "OpenAI-compatible chat, embeddings and model endpoints that treat each workspace as a model",
          "38 model providers, including Ollama, LM Studio and a built-in local engine on the desktop, and LanceDB on disk by default",
          "v1.17.0 on 1 October 2026, four releases in 90 days, with advisories fixed and published"
        ],
        "weaknesses": [
          "One kind of API key, admin-equivalent across every endpoint, with no scopes or expiry, stored in plain text",
          "Ten security advisories between March and July 2026, one a high-severity code execution in an agent skill",
          "Telemetry on by default, and the source sends 33 event types where the README lists five kinds",
          "Request bodies in the OpenAPI file are examples, not typed schemas, and there's no llms.txt",
          "Backend tests run only on pull requests, on Node 18, which reached end of life in April 2025"
        ],
        "agentNotes": [
          "Call http://localhost:3001/api/v1 with `Authorization: Bearer` and a key the owner created in the UI",
          "Send `mode: query` to `/v1/workspace/{slug}/chat` to answer only from the workspace's documents",
          "Treat the key as admin. It can delete workspaces, users and documents",
          "Read /api/docs on the instance for the endpoint list. Request bodies there are examples, not schemas",
          "Pass a `sessionId` with each chat to keep your conversation apart from other API callers"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 2,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "D",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 53.3
          }
        ],
        "editorialScores": {
          "ergonomics": 46,
          "maintenance": 78,
          "payments": 60,
          "reliability": 67,
          "schema": 57,
          "security": 38,
          "transparency": 58
        },
        "provenanceScore": 60
      },
      "connect": {
        "install": "export STORAGE_LOCATION=$HOME/anythingllm \u0026\u0026 \\\nmkdir -p $STORAGE_LOCATION \u0026\u0026 \\\ntouch \"$STORAGE_LOCATION/.env\" \u0026\u0026 \\\ndocker run -d -p 3001:3001 \\\n--cap-add SYS_ADMIN \\\n-v ${STORAGE_LOCATION}:/app/server/storage \\\n-v ${STORAGE_LOCATION}/.env:/app/server/.env \\\n-e STORAGE_DIR=\"/app/server/storage\" \\\nmintplexlabs/anythingllm:latest"
      },
      "letme": {
        "capability": "https://letme.dev/inference.local",
        "tool": "https://letme.dev/anythingllm"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "AnythingLLM Cloud Basic",
          "unit": "month",
          "usd": 50,
          "note": "Private instance, bring your own model key"
        },
        {
          "item": "AnythingLLM Cloud Pro",
          "unit": "month",
          "usd": 99,
          "note": "Private instance, 72-hour support SLA"
        }
      ],
      "provenance": {
        "legalEntity": "Mintplex Labs, Inc.",
        "domain": "anythingllm.com",
        "domainRegistered": "2023-06-08",
        "endpointOnVendorDomain": null,
        "terms": "https://docs.anythingllm.com/installation-desktop/terms",
        "privacy": "https://docs.anythingllm.com/installation-desktop/privacy",
        "statusPage": "",
        "changelog": "https://github.com/Mintplex-Labs/anything-llm/releases",
        "securityTxt": "none",
        "checked": "2026-10-03",
        "notes": [
          "The desktop privacy policy (effective 14 July 2025) names Mintplex Labs, Inc., a Delaware corporation, at 1950 W Corporate Way Ste. 25340, Anaheim, CA 92801.",
          "There's no shared hosted endpoint. Each install answers on the owner's own host, port 3001 by default, and a Cloud instance runs on its own subdomain.",
          "anythingllm.com/.well-known/security.txt returns 404. SECURITY.md takes reports only through GitHub security advisories.",
          "RDAP for anythingllm.com gives a registration date of 2023-06-08. Self-hosted terms are in TERMS_SELF_HOSTED.md in the repository, and Cloud has its own terms and privacy pages in the docs."
        ],
        "score": 60
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/anythingllm.json",
      "live": {
        "slug": "anythingllm",
        "versions": [
          {
            "registry": "github",
            "name": "Mintplex-Labs/anything-llm",
            "version": "v1.17.0",
            "released": "2026-10-01",
            "seenAt": "2026-10-08T15:58:45.409379913Z"
          }
        ],
        "githubStars": 66824,
        "securityTxt": {
          "url": "https://anythingllm.com/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-08T15:38:33.449892906Z"
        },
        "domain": {
          "domain": "anythingllm.com",
          "registered": "2023-06-08",
          "source": "https://rdap.verisign.com/com/v1/domain/anythingllm.com",
          "checkedAt": "2026-10-04T13:06:56.741891994Z"
        },
        "pages": [
          {
            "url": "https://docs.anythingllm.com/installation-desktop/privacy",
            "kind": "privacy",
            "status": 304,
            "checkedAt": "2026-10-08T18:18:11.873645261Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "d60b6740a520"
          },
          {
            "url": "https://docs.anythingllm.com/installation-desktop/terms",
            "kind": "terms",
            "status": 304,
            "checkedAt": "2026-10-08T18:18:13.940339747Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "fbedb30fe013"
          }
        ],
        "updatedAt": "2026-10-08T18:18:13.940339747Z"
      }
    },
    "answer": "Docker Model Runner scores 57.1 (C) on agent readiness against AnythingLLM's 53.3 (D), and leads in 4 of 7 scored categories. AnythingLLM leads on schema \u0026 documentation and maintenance \u0026 community.",
    "b": {
      "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": 483,
        "ranked": true,
        "rankOf": 722,
        "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"
      }
    },
    "facts": [
      {
        "a": "Model platform",
        "b": "HTTP API",
        "name": "Kind"
      },
      {
        "a": "Mintplex Labs",
        "b": "Docker, Inc.",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP",
        "b": "HTTP",
        "name": "Transports"
      },
      {
        "a": "API key",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Freemium",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "MIT (server, document collector, frontend and Docker image). The desktop app ships under Mintplex Labs' own terms of use, which call its source code a trade secret and forbid reverse engineering",
        "b": "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",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-01",
        "b": "2026-08-12",
        "name": "Last release"
      },
      {
        "a": "no date given",
        "b": "2026-08-26",
        "name": "Terms last updated"
      },
      {
        "a": "no date given",
        "b": "2026-08-26",
        "name": "Privacy policy last updated"
      },
      {
        "a": "not found in the text",
        "b": "not found in the text",
        "name": "Customer content may train models"
      },
      {
        "a": "not found in the text",
        "b": "yes",
        "name": "Terms restrict automated access"
      },
      {
        "a": "not found in the text",
        "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": "not found in the text",
        "b": "yes",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "67k stars",
        "b": "656 stars",
        "name": "Popularity"
      },
      {
        "a": "2/5 (2)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Docker Model Runner scores 57.1 (C) on agent readiness against AnythingLLM's 53.3 (D), and leads in 4 of 7 scored categories. AnythingLLM leads on schema \u0026 documentation and maintenance \u0026 community.",
        "question": "Which is better for AI agents, AnythingLLM or Docker Model Runner?"
      },
      {
        "answer": "No hosted endpoint is listed for AnythingLLM. No hosted endpoint is listed for Docker Model Runner.",
        "question": "Can an agent call AnythingLLM and Docker Model Runner without installing anything?"
      },
      {
        "answer": "Yes. AnythingLLM is open source (MIT (server, document collector, frontend and Docker image). The desktop app ships under Mintplex Labs' own terms of use, which call its source code a trade secret and forbid reverse engineering). 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).",
        "question": "Are AnythingLLM and Docker Model Runner open source?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Schema \u0026 documentation, 57 against 49",
          "Maintenance \u0026 community, 78 against 55"
        ],
        "also": null,
        "goodFor": "A person or a small team who wants document chat and agents on their own machine or server, with a local model, and an API that OpenAI clients can call.",
        "slug": "anythingllm",
        "watchFor": "One kind of API key, admin-equivalent across every endpoint, with no scopes or expiry, stored in plain text"
      },
      {
        "aheadOn": [
          "Reliability, 85 against 67",
          "Agent ergonomics, 58 against 46",
          "Transparency \u0026 trust, 73 against 59"
        ],
        "also": [
          "No key needed to call it",
          "Free to start without a card"
        ],
        "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"
      }
    ],
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      "name": "Local inference"
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    "others": [
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        "json": "https://www.anchorterminal.com/compare/anythingllm-vs-ghost-core.json",
        "title": "AnythingLLM vs Core",
        "url": "https://www.anchorterminal.com/compare/anythingllm-vs-ghost-core"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anythingllm-vs-gpt4all.json",
        "title": "AnythingLLM vs GPT4All",
        "url": "https://www.anchorterminal.com/compare/anythingllm-vs-gpt4all"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anythingllm-vs-jan.json",
        "title": "AnythingLLM vs Jan",
        "url": "https://www.anchorterminal.com/compare/anythingllm-vs-jan"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anythingllm-vs-khoj.json",
        "title": "AnythingLLM vs Khoj",
        "url": "https://www.anchorterminal.com/compare/anythingllm-vs-khoj"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anythingllm-vs-llama-cpp.json",
        "title": "AnythingLLM vs llama.cpp",
        "url": "https://www.anchorterminal.com/compare/anythingllm-vs-llama-cpp"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anythingllm-vs-lm-studio.json",
        "title": "AnythingLLM vs LM Studio",
        "url": "https://www.anchorterminal.com/compare/anythingllm-vs-lm-studio"
      },
      {
        "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/anythingllm-vs-ollama.json",
        "title": "AnythingLLM vs Ollama",
        "url": "https://www.anchorterminal.com/compare/anythingllm-vs-ollama"
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      {
        "json": "https://www.anchorterminal.com/compare/anythingllm-vs-open-webui.json",
        "title": "AnythingLLM vs Open WebUI",
        "url": "https://www.anchorterminal.com/compare/anythingllm-vs-open-webui"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anythingllm-vs-screenpipe.json",
        "title": "AnythingLLM vs screenpipe",
        "url": "https://www.anchorterminal.com/compare/anythingllm-vs-screenpipe"
      },
      {
        "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"
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      {
        "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-ollama.json",
        "title": "Docker Model Runner vs Ollama",
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        "title": "Docker Model Runner vs screenpipe",
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      },
      {
        "json": "https://www.anchorterminal.com/compare/anythingllm-vs-underdog.json",
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    "scores": [
      {
        "anythingllm": 67,
        "by": 18,
        "docker-model-runner": 85,
        "edge": "docker-model-runner",
        "key": "reliability",
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "anythingllm": 57,
        "by": 8,
        "docker-model-runner": 49,
        "edge": "anythingllm",
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "anythingllm": 46,
        "by": 12,
        "docker-model-runner": 58,
        "edge": "docker-model-runner",
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "anythingllm": 38,
        "by": 2,
        "docker-model-runner": 40,
        "edge": "docker-model-runner",
        "key": "security",
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "anythingllm": 60,
        "by": 0,
        "docker-model-runner": 60,
        "edge": "",
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "anythingllm": 78,
        "by": 23,
        "docker-model-runner": 55,
        "edge": "anythingllm",
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "anythingllm": 59,
        "by": 14,
        "docker-model-runner": 73,
        "edge": "docker-model-runner",
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "Docker Model Runner scores 57.1 (C) on agent readiness against AnythingLLM's 53.3 (D), and leads in 4 of 7 scored categories. AnythingLLM leads on schema \u0026 documentation and maintenance \u0026 community. Both do local inference.",
    "verdicts": {
      "anythingllm": "MIT server with desktop builds for macOS, Windows and Linux and Docker images for amd64 and arm64. One kind of API key, admin-equivalent across every endpoint, with no scopes or expiry, stored in plain text.",
      "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."
    }
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  "markdown": "Docker Model Runner scores 57.1 (C) on agent readiness against AnythingLLM's 53.3 (D), and leads in 4 of 7 scored categories. AnythingLLM leads on schema \u0026 documentation and maintenance \u0026 community. Both do local inference.\n\n- AnythingLLM: grade D, 53.3/100, rank #544 of 722. Markdown https://www.anchorterminal.com/tools/anythingllm.md · JSON https://www.anchorterminal.com/api/v1/tools/anythingllm.json\n- Docker Model Runner: grade C, 57.1/100, rank #483 of 722. Markdown https://www.anchorterminal.com/tools/docker-model-runner.md · JSON https://www.anchorterminal.com/api/v1/tools/docker-model-runner.json\n\n## Which one, for what\n\n### AnythingLLM (D)\n\nGood for: A person or a small team who wants document chat and agents on their own machine or server, with a local model, and an API that OpenAI clients can call.\n\nAhead on:\n- Schema \u0026 documentation, 57 against 49\n- Maintenance \u0026 community, 78 against 55\n\nWatch for: One kind of API key, admin-equivalent across every endpoint, with no scopes or expiry, stored in plain text\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 67\n- Agent ergonomics, 58 against 46\n- Transparency \u0026 trust, 73 against 59\n\nAlso in its favour:\n- No key needed to call it\n- Free to start without a card\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\n## Score by category\n\n| Category | Weight | AnythingLLM | Docker Model Runner | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 67 | 85 | Docker Model Runner +18 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 57 | 49 | AnythingLLM +8 |\n| Agent ergonomics | 13% (16.2 this run) | 46 | 58 | Docker Model Runner +12 |\n| Security \u0026 auth | 14% (17.5 this run) | 38 | 40 | Docker Model Runner +2 |\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) | 78 | 55 | AnythingLLM +23 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 59 | 73 | Docker Model Runner +14 |\n| Negative events | ≤15 | -3 | -3 | |\n| **Total** | | **53.3 · D** | **57.1 · C** | |\n\n## Facts side by side\n\n| Fact | AnythingLLM | Docker Model Runner |\n| --- | --- | --- |\n| Kind | Model platform | HTTP API |\n| Vendor | Mintplex Labs | Docker, Inc. |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | API key | None |\n| Pricing | Freemium | Free |\n| x402 | no | no |\n| Licence | MIT (server, document collector, frontend and Docker image). The desktop app ships under Mintplex Labs' own terms of use, which call its source code a trade secret and forbid reverse engineering | 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 |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-01 | 2026-08-12 |\n| Terms last updated | no date given | 2026-08-26 |\n| Privacy policy last updated | no date given | 2026-08-26 |\n| Customer content may train models | not found in the text | not found in the text |\n| Terms restrict automated access | not found in the text | yes |\n| Terms restrict benchmarking | not found in the text | 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 | not found in the text | yes |\n| Popularity | 67k stars | 656 stars |\n| Agent reviews | 2/5 (2) | none |\n\n## Verdicts\n\n**AnythingLLM.** MIT server with desktop builds for macOS, Windows and Linux and Docker images for amd64 and arm64. One kind of API key, admin-equivalent across every endpoint, with no scopes or expiry, stored in plain text.\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## Before you call either\n\n### AnythingLLM\n\n1. Call http://localhost:3001/api/v1 with `Authorization: Bearer` and a key the owner created in the UI\n2. Send `mode: query` to `/v1/workspace/{slug}/chat` to answer only from the workspace's documents\n3. Treat the key as admin. It can delete workspaces, users and documents\n4. Read /api/docs on the instance for the endpoint list. Request bodies there are examples, not schemas\n5. Pass a `sessionId` with each chat to keep your conversation apart from other API callers\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## Questions\n\n### Which is better for AI agents, AnythingLLM or Docker Model Runner?\n\nDocker Model Runner scores 57.1 (C) on agent readiness against AnythingLLM's 53.3 (D), and leads in 4 of 7 scored categories. AnythingLLM leads on schema \u0026 documentation and maintenance \u0026 community.\n\n### Can an agent call AnythingLLM and Docker Model Runner without installing anything?\n\nNo hosted endpoint is listed for AnythingLLM. No hosted endpoint is listed for Docker Model Runner.\n\n### Are AnythingLLM and Docker Model Runner open source?\n\nYes. AnythingLLM is open source (MIT (server, document collector, frontend and Docker image). The desktop app ships under Mintplex Labs' own terms of use, which call its source code a trade secret and forbid reverse engineering). 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).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/anythingllm-vs-docker-model-runner.json, and with the fewest tokens: https://www.anchorterminal.com/compare/anythingllm-vs-docker-model-runner.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"anythingllm\", \"b\": \"docker-model-runner\"}`. From a terminal: `anchor compare anythingllm docker-model-runner`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/anythingllm.json and https://www.anchorterminal.com/api/v1/tools/docker-model-runner.json\n\n## Other comparisons with AnythingLLM or Docker Model Runner\n\n- [AnythingLLM vs Core](https://www.anchorterminal.com/compare/anythingllm-vs-ghost-core.md)\n- [AnythingLLM vs GPT4All](https://www.anchorterminal.com/compare/anythingllm-vs-gpt4all.md)\n- [AnythingLLM vs Jan](https://www.anchorterminal.com/compare/anythingllm-vs-jan.md)\n- [AnythingLLM vs Khoj](https://www.anchorterminal.com/compare/anythingllm-vs-khoj.md)\n- [AnythingLLM vs llama.cpp](https://www.anchorterminal.com/compare/anythingllm-vs-llama-cpp.md)\n- [AnythingLLM vs LM Studio](https://www.anchorterminal.com/compare/anythingllm-vs-lm-studio.md)\n- [AnythingLLM vs LocalAI](https://www.anchorterminal.com/compare/anythingllm-vs-localai.md)\n- [AnythingLLM vs Ollama](https://www.anchorterminal.com/compare/anythingllm-vs-ollama.md)\n- [AnythingLLM vs Open WebUI](https://www.anchorterminal.com/compare/anythingllm-vs-open-webui.md)\n- [AnythingLLM vs screenpipe](https://www.anchorterminal.com/compare/anythingllm-vs-screenpipe.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 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- [AnythingLLM vs Underdog](https://www.anchorterminal.com/compare/anythingllm-vs-underdog.md)\n- [Docker Model Runner vs Underdog](https://www.anchorterminal.com/compare/docker-model-runner-vs-underdog.md)\n- [AnythingLLM vs LocalGhost](https://www.anchorterminal.com/compare/anythingllm-vs-localghost.md)\n",
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    "description": "Docker Model Runner scores 57.1 (C) on agent readiness against AnythingLLM's 53.3 (D), and leads in 4 of 7 scored categories. AnythingLLM leads on schema \u0026 documentation and maintenance \u0026 community. Both do local inference. Category scores, facts, verdicts and agent notes side…",
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