{
  "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": 53.6,
        "grade": "D",
        "agentReady": false,
        "rank": 330,
        "ranked": true,
        "rankOf": 452,
        "categoryRank": 6,
        "methodology": "0.3",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 46,
          "maintenance": 78,
          "payments": 60,
          "reliability": 67,
          "schema": 57,
          "security": 38,
          "transparency": 63
        },
        "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.",
        "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": "0.3",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 53.6
          }
        ],
        "editorialScores": {
          "ergonomics": 46,
          "maintenance": 78,
          "payments": 60,
          "reliability": 67,
          "schema": 57,
          "security": 38,
          "transparency": 58
        },
        "provenanceScore": 67
      },
      "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": 67
      },
      "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": "2026-10-04T16:20:25.081085298Z"
          }
        ],
        "githubStars": 66708,
        "securityTxt": {
          "url": "https://anythingllm.com/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-04T15:16:04.556618476Z"
        },
        "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": 200,
            "checkedAt": "2026-10-04T15:43:09.350190924Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "d60b6740a520"
          },
          {
            "url": "https://docs.anythingllm.com/installation-desktop/terms",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-10-04T15:43:11.412362007Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "fbedb30fe013"
          }
        ],
        "updatedAt": "2026-10-04T16:20:25.081085298Z"
      }
    },
    "b": {
      "slug": "llama-cpp",
      "name": "llama.cpp",
      "vendor": "ggml.ai (Hugging Face)",
      "vendorUrl": "https://llama.app",
      "kind": "http-api",
      "category": "local-ai",
      "summary": "Open-source C/C++ engine for running GGUF models locally, with a web interface and compatible model APIs.",
      "url": "https://www.anchorterminal.com/tools/llama-cpp",
      "markdownUrl": "https://www.anchorterminal.com/tools/llama-cpp.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/llama-cpp.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/llama-cpp.json",
      "repo": "https://github.com/ggml-org/llama.cpp",
      "license": "MIT",
      "transports": [
        "http"
      ],
      "packages": [
        {
          "registry": "oci",
          "name": "ghcr.io/ggml-org/llama.cpp"
        },
        {
          "registry": "pypi",
          "name": "gguf"
        }
      ],
      "auth": "none",
      "authNotes": "No credential by default. `--api-key` (one key or a comma-separated list) or `--api-key-file` (one key a line) turns on a check for every route but /health and the web UI's files, with the key sent as `Authorization: Bearer` or `X-Api-Key`, never in the query string. Keys have no scopes and change only with a restart. TLS is built in with `--ssl-key-file` and `--ssl-cert-file`. The server binds 127.0.0.1:8080 by default, and CORS reflects any Origin with credentials allowed unless built-in tools, MCP servers or `--agent` are on, when it narrows to localhost (https://github.com/ggml-org/llama.cpp/blob/master/tools/server/README.md).",
      "pricing": "free",
      "pricingNotes": "Free under MIT, with no account, key or card. Nothing is sold. You pay for your own hardware and electricity.",
      "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": null,
      "popularity": {
        "githubStars": 130200,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-03"
      },
      "docsUrl": "https://github.com/ggml-org/llama.cpp/blob/master/tools/server/README.md",
      "capabilities": [
        "inference.local",
        "inference.open-weights",
        "embed.text",
        "rerank",
        "inference.decision",
        "agent.mcp-client"
      ],
      "tags": [
        "open-source",
        "local",
        "self-hosted",
        "free",
        "no-card",
        "openai-compatible",
        "docker",
        "pre-1.0",
        "no-telemetry"
      ],
      "lastRelease": "2026-09-23",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 60.2,
        "grade": "C",
        "agentReady": false,
        "rank": 253,
        "ranked": true,
        "rankOf": 452,
        "categoryRank": 3,
        "methodology": "0.3",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 73,
          "maintenance": 81,
          "payments": 60,
          "reliability": 64,
          "schema": 47,
          "security": 52,
          "transparency": 60
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-03"
        },
        "negative": -1,
        "negativeNotes": [
          "2026-03-26. GHSA-j8rj-fmpv-wcxw (CVE-2026-34159, 9.8 at NVD), unauthenticated code execution through a GRAPH_COMPUTE bypass in the RPC backend, the most serious of four advisories published between January and March 2026 (the others a llama-server out-of-bounds write through a negative `n_discard` and two GGUF integer overflows). All were fixed in named builds and published as advisories, SECURITY.md says not to expose the RPC server or llama-server to untrusted networks, and the newest is more than six months old, -1. https://github.com/ggml-org/llama.cpp/security/advisories/GHSA-j8rj-fmpv-wcxw; https://github.com/ggml-org/llama.cpp/security"
        ],
        "verdict": "MIT, with no telemetry or update check in the source, and `--offline` blocks model downloads. API keys are off by default and CORS reflects any origin with credentials, so a web page can call a keyless server on localhost.",
        "strengths": [
          "MIT, with no telemetry or update check in the source, and `--offline` blocks model downloads",
          "OpenAI chat completions, responses and embeddings, Anthropic messages, reranking and /v1/systemone from one server",
          "`response_fields`, `json_schema` and `grammar` control the size and shape of output, and errors carry an OpenAI-style type and code",
          "1,005 nightly builds and eight semver releases in 90 days, with 37 workflows running on every push to master",
          "Ten published GitHub advisories with CVEs and fixed builds, and SECURITY.md guidance on untrusted models and inputs"
        ],
        "weaknesses": [
          "API keys are off by default and CORS reflects any origin with credentials, so a web page can call a keyless server on localhost",
          "No OpenAPI file of its own, and the REST API changelog stops at b4599",
          "Private security disclosure disabled since 1 June 2026, with fixes asked for as public pull requests",
          "Pre-1.0 (0.5.0), and semver releases are bare tags with no notes",
          "No official client library, and `n_predict` defaults to unlimited"
        ],
        "agentNotes": [
          "Start the server with `--api-key` and `--cors-origins localhost` before anything else can reach the port. Both are off by default",
          "Pass `n_predict` or `max_tokens`. Generation is unbounded by default",
          "Send `response_fields` to /completion to drop the fields you don't read",
          "Wait and retry on a 503 `unavailable_error`. The model is still loading",
          "Read the server README of the build you run. Behaviour changes between nightly builds without a changelog entry"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 2.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.3",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 60.2
          }
        ],
        "editorialScores": {
          "ergonomics": 73,
          "maintenance": 81,
          "payments": 60,
          "reliability": 64,
          "schema": 47,
          "security": 52,
          "transparency": 66
        },
        "provenanceScore": 53
      },
      "connect": {
        "install": "curl -LsSf https://llama.app/install.sh | sh   # or: brew install llama.cpp; winget install llama.cpp\nllama serve -hf ggml-org/Qwen3.5-0.8B-GGUF   # listens on 127.0.0.1:8080",
        "http": "curl --request POST \\\n    --url http://localhost:8080/completion \\\n    --header \"Content-Type: application/json\" \\\n    --data '{\"prompt\": \"Building a website can be done in 10 simple steps:\",\"n_predict\": 128}'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.local",
        "tool": "https://letme.dev/llama-cpp"
      },
      "area": "models",
      "provenance": {
        "legalEntity": "ggml.ai, part of Hugging Face since 2026",
        "domain": "llama.app",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://github.com/ggml-org/llama.cpp/releases",
        "securityTxt": "none",
        "checked": "2026-10-03",
        "notes": [
          "The repository's About link is llama.app, which says it's by the llama.cpp team and Hugging Face and links no terms, privacy or security page. ggml.ai says the company was acquired by Hugging Face in 2026 and names no address.",
          "The `LICENSE` file reads Copyright (c) 2023-2026 The ggml authors.",
          "llama.app/.well-known/security.txt and llama.app/llms.txt return 404. SECURITY.md points to GitHub private advisories while saying private disclosure is disabled.",
          "There's no shared hosted endpoint. The server runs on the owner's machine."
        ],
        "score": 53
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/llama-cpp.json",
      "live": {
        "slug": "llama-cpp",
        "versions": [
          {
            "registry": "github",
            "name": "ggml-org/llama.cpp",
            "version": "v0.5.0",
            "released": "2026-09-23",
            "seenAt": "2026-10-04T16:31:53.040249174Z"
          },
          {
            "registry": "pypi",
            "name": "gguf",
            "version": "0.19.0",
            "released": "2026-05-06",
            "seenAt": "2026-10-04T16:31:52.933067593Z"
          }
        ],
        "githubStars": 130286,
        "securityTxt": {
          "url": "https://llama.app/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-04T15:16:00.86400098Z"
        },
        "domain": {
          "domain": "llama.app",
          "registered": "2018-07-18",
          "source": "https://pubapi.registry.google/rdap/domain/llama.app",
          "checkedAt": "2026-10-04T13:04:03.05886804Z"
        },
        "updatedAt": "2026-10-04T16:31:53.040249174Z"
      }
    },
    "summary": "llama.cpp has a score of 60.2 (C) against AnythingLLM's 53.6 (D). Both do local inference. The largest gap is agent ergonomics, 27 points."
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/anythingllm-vs-llama-cpp",
    "json": "https://www.anchorterminal.com/compare/anythingllm-vs-llama-cpp.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/anythingllm-vs-llama-cpp.md",
    "slim": "https://www.anchorterminal.com/compare/anythingllm-vs-llama-cpp.min.md"
  },
  "markdown": "llama.cpp has a score of 60.2 (C) against AnythingLLM's 53.6 (D). Both do local inference. The largest gap is agent ergonomics, 27 points.\n\n- AnythingLLM: grade D, 53.6/100, rank #330 of 452. Markdown https://www.anchorterminal.com/tools/anythingllm.md · JSON https://www.anchorterminal.com/api/v1/tools/anythingllm.json\n- llama.cpp: grade C, 60.2/100, rank #253 of 452. Markdown https://www.anchorterminal.com/tools/llama-cpp.md · JSON https://www.anchorterminal.com/api/v1/tools/llama-cpp.json\n\n## Which one, for what\n\nPick AnythingLLM for schema \u0026 documentation (+10).\n\nPick llama.cpp for agent ergonomics (+27), security \u0026 auth (+14).\n\n## Score by category\n\n| Category | Weight | AnythingLLM | llama.cpp | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 67 | 64 | AnythingLLM +3 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 57 | 47 | AnythingLLM +10 |\n| Agent ergonomics | 13% (16.2 this run) | 46 | 73 | llama.cpp +27 |\n| Security \u0026 auth | 14% (17.5 this run) | 38 | 52 | llama.cpp +14 |\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 | 81 | llama.cpp +3 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 63 | 60 | AnythingLLM +3 |\n| Negative events | ≤15 | -3 | -1 | |\n| **Total** | | **53.6 · D** | **60.2 · C** | |\n\n## Facts side by side\n\n| Fact | AnythingLLM | llama.cpp |\n| --- | --- | --- |\n| Kind | Model platform | HTTP API |\n| Vendor | Mintplex Labs | ggml.ai (Hugging Face) |\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 | MIT |\n| Tools exposed | none | none |\n| Context cost (tools/list) | n/a | n/a |\n| p95 latency | not measured yet | not measured yet |\n| Availability (30d) | not measured yet | not measured yet |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| MCP registry | not listed | not listed |\n| Last release | 2026-10-01 | 2026-09-23 |\n| Popularity | 67k stars | 130k stars |\n| Agent reviews | 2/5 (2) | 2.5/5 (2) |\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**llama.cpp.** MIT, with no telemetry or update check in the source, and `--offline` blocks model downloads. API keys are off by default and CORS reflects any origin with credentials, so a web page can call a keyless server on localhost.\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### llama.cpp\n\n1. Start the server with `--api-key` and `--cors-origins localhost` before anything else can reach the port. Both are off by default\n2. Pass `n_predict` or `max_tokens`. Generation is unbounded by default\n3. Send `response_fields` to /completion to drop the fields you don't read\n4. Wait and retry on a 503 `unavailable_error`. The model is still loading\n5. Read the server README of the build you run. Behaviour changes between nightly builds without a changelog entry\n\n## Other comparisons with AnythingLLM or llama.cpp\n\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 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- [GPT4All vs llama.cpp](https://www.anchorterminal.com/compare/gpt4all-vs-llama-cpp.md)\n- [Jan vs llama.cpp](https://www.anchorterminal.com/compare/jan-vs-llama-cpp.md)\n- [Khoj vs llama.cpp](https://www.anchorterminal.com/compare/khoj-vs-llama-cpp.md)\n- [llama.cpp vs LM Studio](https://www.anchorterminal.com/compare/llama-cpp-vs-lm-studio.md)\n- [llama.cpp vs LocalAI](https://www.anchorterminal.com/compare/llama-cpp-vs-localai.md)\n- [llama.cpp vs Ollama](https://www.anchorterminal.com/compare/llama-cpp-vs-ollama.md)\n- [llama.cpp vs Open WebUI](https://www.anchorterminal.com/compare/llama-cpp-vs-open-webui.md)\n- [llama.cpp vs screenpipe](https://www.anchorterminal.com/compare/llama-cpp-vs-screenpipe.md)\n- [AnythingLLM vs Underdog](https://www.anchorterminal.com/compare/anythingllm-vs-underdog.md)\n- [llama.cpp vs Underdog](https://www.anchorterminal.com/compare/llama-cpp-vs-underdog.md)\n- [AnythingLLM vs LocalGhost](https://www.anchorterminal.com/compare/anythingllm-vs-localghost.md)\n",
  "meta": {
    "attribution": "Anchor Terminal (https://www.anchorterminal.com)",
    "docs": "https://www.anchorterminal.com/docs/",
    "generatedAt": "2026-10-05",
    "license": "CC-BY-4.0",
    "method": "https://www.anchorterminal.com/benchmark/",
    "methodology": "0.3",
    "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": "AnythingLLM vs llama.cpp",
        "url": ""
      }
    ],
    "description": "llama.cpp has a score of 60.2 (C) against AnythingLLM's 53.6 (D). Both do local inference. The largest gap is agent ergonomics, 27 points. Category scores, facts, verdicts and agent notes side by side.",
    "facts": [
      "AnythingLLM D 53.6",
      "llama.cpp C 60.2",
      "scores"
    ],
    "h1": "AnythingLLM vs llama.cpp",
    "image": "https://www.anchorterminal.com/assets/og/compare-anythingllm-vs-llama-cpp.png",
    "path": "/compare/anythingllm-vs-llama-cpp",
    "published": "2026-10-01",
    "section": "tools",
    "title": "AnythingLLM vs llama.cpp for AI agents, D 53.6 vs C 60.2",
    "toc": null,
    "updated": "2026-10-05",
    "url": "https://www.anchorterminal.com/compare/anythingllm-vs-llama-cpp"
  },
  "tokens": {
    "markdown": 1600,
    "slim": 330
  },
  "version": 1
}
