{ "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": 760, "ranked": true, "rankOf": 1094, "categoryRank": 12, "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": "v1.18.0", "released": "2026-10-13", "seenAt": "2026-10-14T23:38:20.96906636Z" } ], "githubStars": 67088, "securityTxt": { "url": "https://anythingllm.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-14T15:46:11.412808134Z" }, "domain": { "domain": "anythingllm.com", "registered": "2023-06-08", "source": "https://rdap.verisign.com/com/v1/domain/anythingllm.com", "checkedAt": "2026-10-11T13:25:37.066734987Z" }, "pages": [ { "url": "https://docs.anythingllm.com/installation-desktop/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-14T20:57:41.353170697Z", "changedAt": "2026-10-14T20:57:41.353170697Z", "fingerprint": "cc1ee72c7020" }, { "url": "https://docs.anythingllm.com/installation-desktop/terms", "kind": "terms", "status": 200, "checkedAt": "2026-10-14T20:57:43.702789479Z", "changedAt": "2026-10-14T20:57:43.702789479Z", "fingerprint": "6cd9a7d6730c" } ], "updatedAt": "2026-10-14T23:38:20.96906636Z" } }, "answer": "AnythingLLM scores 53.3 (D) on agent readiness against BitRun's 37.9 (F), and leads in 6 of 7 scored categories.", "b": { "slug": "bitrun", "name": "BitRun", "vendor": "Abhishek Khanra (IshekKhal on GitHub)", "vendorUrl": "https://github.com/IshekKhal", "kind": "http-api", "category": "local-ai", "summary": "BitRun is an open-source command-line runner for 1-bit and 1.58-bit ternary language models such as BitNet b1.58, Falcon3 1.58-bit and Bonsai on CPUs, with a model downloader and a local OpenAI-compatible server.", "url": "https://www.anchorterminal.com/tools/bitrun", "markdownUrl": "https://www.anchorterminal.com/tools/bitrun.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/bitrun.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/bitrun.json", "repo": "https://github.com/IshekKhal/bitrun", "license": "MIT", "transports": [ "http" ], "packages": [], "auth": "none", "authNotes": "No credential. `bitrun serve` starts a patched llama-server on 127.0.0.1 (default port 11435, changed with `--port`) and passes no `--api-key`, so any process on the machine can call it. The bind address is fixed in the code, with no flag to expose it on the network. The README's SDK example sets `api_key` to any string.", "pricing": "free", "pricingNotes": "Free under MIT with nothing to buy. Models are downloaded from Hugging Face under each model's own licence.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the source, the README or the release notes (checked 2026-10-15). Nothing is sold.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 5, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-15" }, "docsUrl": "https://github.com/IshekKhal/bitrun#readme", "capabilities": [ "inference.local", "inference.open-weights" ], "tags": [ "open-source", "local", "self-hosted", "free", "no-card", "mit", "openai-compatible", "go", "pre-1.0", "macos", "windows", "cli" ], "lastRelease": "2026-10-15", "graded": true, "anchor": { "graded": true, "score": 37.9, "grade": "F", "agentReady": false, "rank": 1018, "ranked": true, "rankOf": 1094, "categoryRank": 18, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 40, "maintenance": 59, "payments": 60, "reliability": 38, "schema": 30, "security": 28, "transparency": 50 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-15" }, "negative": -3, "negativeNotes": [ "Misleading claim, 15 October 2026. The README's \"Verified Hardware Benchmarks\", described as physical hardware runs, list package power of 11.70 W, 22.60 W and 8.50 W for every model on each machine, and joules per token from them. These equal the fixed estimates in power.go (2.5 + 1.15 per thread on macOS without battery data, 5.0 + 2.2 per thread on Windows, 4.5 + 2.0 per thread on Linux without RAPL) at the default thread counts of 8, 8 and 2. The README also says Windows power is measured through PPM and that `pull` resumes downloads, and the source does neither (https://github.com/IshekKhal/bitrun/blob/0fec65a/pkg/telemetry/power.go#L137-L163, https://github.com/IshekKhal/bitrun/blob/0fec65a/pkg/models/downloader.go#L57-L60, https://github.com/IshekKhal/bitrun/blob/0fec65a/README.md). Judgement call, -3." ], "verdict": "BitRun packages patched llama.cpp builds for ternary models into one download for macOS on Apple silicon, Windows and Linux, with a loopback-only OpenAI-compatible server. It is three days old with three pre-release versions, one maintainer and no CI, and its published power figures come from a fixed formula rather than measurement.", "bestFor": "A developer who wants to try ternary models on a laptop CPU behind an OpenAI-style endpoint without building bitnet.cpp.", "strengths": [ "One archive per platform (macOS arm64, Linux amd64, Windows amd64) with llama-server, so no compiler, Python or Docker is needed", "The server binds 127.0.0.1 with no flag to expose it, and works with OpenAI SDKs by changing the base URL", "A catalogue of six ternary and compact models, 79 MB to 2.08 GB, pulled from their Hugging Face repositories by tag", "MIT licence, and no network telemetry found in the Go source. Outbound calls are model downloads on `pull`" ], "weaknesses": [ "First released on 12 October 2026. Three pre-release versions in four days, one maintainer and no CI workflow", "The README's package power and joules-per-token figures match a fixed per-thread formula in the code, not a counter reading", "No API key option, so any local process can call the server, and model downloads and the installer verify no checksum", "The server documentation covers one route, `/v1/chat/completions`, with no error responses, OpenAPI file or llms.txt", "Context windows of the catalogue models run from 768 to 8,192 tokens, and one server process serves one model" ], "agentNotes": [ "Ask the user to install BitRun and run `bitrun pull \u003ctag\u003e` and `bitrun serve \u003ctag\u003e` first. Then call http://127.0.0.1:11435/v1 with any API key string", "Poll `/health` before the first request. The server loads the model in the background and answers only when ready", "Use a model tag from the catalogue (bitnet-70m, bonsai-1.7b, falcon3-1b, bitnet-2b, falcon3-3b, bonsai-8b) and keep prompts within its context window", "Treat the README's energy figures as estimates, and don't report them as measured power", "Expect small research checkpoints. Check outputs before relying on them for code or facts" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "F", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 37.9 } ], "editorialScores": { "ergonomics": 40, "maintenance": 59, "payments": 60, "reliability": 38, "schema": 30, "security": 28, "transparency": 46 }, "provenanceScore": 53 }, "connect": { "install": "curl -fsSL https://raw.githubusercontent.com/IshekKhal/bitrun/main/install.sh | sh\nbitrun pull falcon3-1b\nbitrun serve falcon3-1b --port 11435", "http": "curl -s http://127.0.0.1:11435/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"falcon3-1b\", \"messages\": [{\"role\": \"user\", \"content\": \"How do 1-bit models conserve memory bandwidth?\"}], \"temperature\": 0.2}'" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/bitrun" }, "area": "models", "provenance": { "legalEntity": "Abhishek Khanra (IshekKhal on GitHub)", "domain": "", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/IshekKhal/bitrun/releases", "securityTxt": "none", "checked": "2026-10-15", "notes": [ "The project has no website. The GitHub account IshekKhal (created 17 December 2024) gives the name Abhishek Khanra, and the licence reads Copyright (c) 2026 Abhishek. The Show HN post was made by the HN account ishekofficial.", "No terms, privacy policy, SECURITY.md or security.txt. The repository has no .github folder.", "The software runs on the owner's machine, so there is no vendor endpoint or status page to check." ], "score": 53 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/bitrun.json" }, "facts": [ { "a": "Platform", "b": "HTTP API", "name": "Kind" }, { "a": "Mintplex Labs", "b": "Abhishek Khanra (IshekKhal on GitHub)", "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": "MIT", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-10-01", "b": "2026-10-15", "name": "Last release" }, { "a": "no date given", "b": "no document linked", "name": "Terms last updated" }, { "a": "no date given", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "67k stars", "b": "5 stars", "name": "Popularity" }, { "a": "2/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "AnythingLLM scores 53.3 (D) on agent readiness against BitRun's 37.9 (F), and leads in 6 of 7 scored categories.", "question": "Which is better for AI agents, AnythingLLM or BitRun?" }, { "answer": "No hosted endpoint is listed for AnythingLLM. No hosted endpoint is listed for BitRun.", "question": "Can an agent call AnythingLLM and BitRun 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). BitRun is open source (MIT).", "question": "Are AnythingLLM and BitRun open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 67 against 38", "Schema \u0026 documentation, 57 against 30", "Agent ergonomics, 46 against 40", "Security \u0026 auth, 38 against 28", "Maintenance \u0026 community, 78 against 59", "Transparency \u0026 trust, 59 against 50" ], "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": null, "also": [ "No key needed to call it", "Free to start without a card" ], "goodFor": "A developer who wants to try ternary models on a laptop CPU behind an OpenAI-style endpoint without building bitnet.cpp.", "slug": "bitrun", "watchFor": "First released on 12 October 2026. Three pre-release versions in four days, one maintainer and no CI workflow" } ], "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-foundry-local.json", "title": "AnythingLLM vs Foundry Local", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-foundry-local" }, { "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-koboldcpp.json", "title": "AnythingLLM vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-koboldcpp" }, { "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/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-mlx-lm.json", "title": "AnythingLLM vs MLX LM", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-ollama.json", "title": "AnythingLLM vs Ollama", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/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/anythingllm-vs-text-generation-webui.json", "title": "AnythingLLM vs TextGen", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-vllm.json", "title": "AnythingLLM vs vLLM", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-vllm" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-docker-model-runner.json", "title": "BitRun vs Docker Model Runner", "url": "https://www.anchorterminal.com/compare/bitrun-vs-docker-model-runner" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-foundry-local.json", "title": "BitRun vs Foundry Local", "url": "https://www.anchorterminal.com/compare/bitrun-vs-foundry-local" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-ghost-core.json", "title": "BitRun vs Core", "url": "https://www.anchorterminal.com/compare/bitrun-vs-ghost-core" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-gpt4all.json", "title": "BitRun vs GPT4All", "url": "https://www.anchorterminal.com/compare/bitrun-vs-gpt4all" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-jan.json", "title": "BitRun vs Jan", "url": "https://www.anchorterminal.com/compare/bitrun-vs-jan" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-khoj.json", "title": "BitRun vs Khoj", "url": "https://www.anchorterminal.com/compare/bitrun-vs-khoj" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-koboldcpp.json", "title": "BitRun vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/bitrun-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-lemonade.json", "title": "BitRun vs Lemonade", "url": "https://www.anchorterminal.com/compare/bitrun-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-llama-cpp.json", "title": "BitRun vs llama.cpp", "url": "https://www.anchorterminal.com/compare/bitrun-vs-llama-cpp" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-lm-studio.json", "title": "BitRun vs LM Studio", "url": "https://www.anchorterminal.com/compare/bitrun-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-localai.json", "title": "BitRun vs LocalAI", "url": "https://www.anchorterminal.com/compare/bitrun-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-mlx-lm.json", "title": "BitRun vs MLX LM", "url": "https://www.anchorterminal.com/compare/bitrun-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-ollama.json", "title": "BitRun vs Ollama", "url": "https://www.anchorterminal.com/compare/bitrun-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-open-webui.json", "title": "BitRun vs Open WebUI", "url": "https://www.anchorterminal.com/compare/bitrun-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-screenpipe.json", "title": "BitRun vs screenpipe", "url": "https://www.anchorterminal.com/compare/bitrun-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-text-generation-webui.json", "title": "BitRun vs TextGen", "url": "https://www.anchorterminal.com/compare/bitrun-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-vllm.json", "title": "BitRun vs vLLM", "url": "https://www.anchorterminal.com/compare/bitrun-vs-vllm" }, { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-underdog.json", "title": "AnythingLLM vs Underdog", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-underdog" }, { "json": "https://www.anchorterminal.com/compare/bitrun-vs-underdog.json", "title": "BitRun vs Underdog", "url": "https://www.anchorterminal.com/compare/bitrun-vs-underdog" }, { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-localghost.json", "title": "AnythingLLM vs LocalGhost", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-localghost" } ], "scores": [ { "anythingllm": 67, "bitrun": 38, "by": 29, "edge": "anythingllm", "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "anythingllm": 57, "bitrun": 30, "by": 27, "edge": "anythingllm", "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "anythingllm": 46, "bitrun": 40, "by": 6, "edge": "anythingllm", "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "anythingllm": 38, "bitrun": 28, "by": 10, "edge": "anythingllm", "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "anythingllm": 60, "bitrun": 60, "by": 0, "edge": "", "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "anythingllm": 78, "bitrun": 59, "by": 19, "edge": "anythingllm", "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "anythingllm": 59, "bitrun": 50, "by": 9, "edge": "anythingllm", "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "AnythingLLM scores 53.3 (D) on agent readiness against BitRun's 37.9 (F), and leads in 6 of 7 scored categories. 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.", "bitrun": "BitRun packages patched llama.cpp builds for ternary models into one download for macOS on Apple silicon, Windows and Linux, with a loopback-only OpenAI-compatible server. It is three days old with three pre-release versions, one maintainer and no CI, and its published power figures come from a fixed formula rather than measurement." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/anythingllm-vs-bitrun", "json": "https://www.anchorterminal.com/compare/anythingllm-vs-bitrun.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/anythingllm-vs-bitrun.md", "slim": "https://www.anchorterminal.com/compare/anythingllm-vs-bitrun.min.md" }, "markdown": "AnythingLLM scores 53.3 (D) on agent readiness against BitRun's 37.9 (F), and leads in 6 of 7 scored categories. Both do local inference.\n\n- AnythingLLM: grade D, 53.3/100, rank #760 of 1094. Markdown https://www.anchorterminal.com/tools/anythingllm.md · JSON https://www.anchorterminal.com/api/v1/tools/anythingllm.json\n- BitRun: grade F, 37.9/100, rank #1018 of 1094. Markdown https://www.anchorterminal.com/tools/bitrun.md · JSON https://www.anchorterminal.com/api/v1/tools/bitrun.json\n- Best local AI models and assistants: https://www.anchorterminal.com/best/local-ai/index.md\n- All 204 local ai comparisons: https://www.anchorterminal.com/compare/local-ai/index.md\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- Reliability, 67 against 38\n- Schema \u0026 documentation, 57 against 30\n- Agent ergonomics, 46 against 40\n- Security \u0026 auth, 38 against 28\n- Maintenance \u0026 community, 78 against 59\n- Transparency \u0026 trust, 59 against 50\n\nWatch for: One kind of API key, admin-equivalent across every endpoint, with no scopes or expiry, stored in plain text\n\n### BitRun (F)\n\nGood for: A developer who wants to try ternary models on a laptop CPU behind an OpenAI-style endpoint without building bitnet.cpp.\n\nAlso in its favour:\n- No key needed to call it\n- Free to start without a card\n\nWatch for: First released on 12 October 2026. Three pre-release versions in four days, one maintainer and no CI workflow\n\n\n## Score by category\n\n| Category | Weight | AnythingLLM | BitRun | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 67 | 38 | AnythingLLM +29 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 57 | 30 | AnythingLLM +27 |\n| Agent ergonomics | 13% (16.2 this run) | 46 | 40 | AnythingLLM +6 |\n| Security \u0026 auth | 14% (17.5 this run) | 38 | 28 | AnythingLLM +10 |\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 | 59 | AnythingLLM +19 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 59 | 50 | AnythingLLM +9 |\n| Negative events | ≤15 | -3 | -3 | |\n| **Total** | | **53.3 · D** | **37.9 · F** | |\n\n## Facts side by side\n\n| Fact | AnythingLLM | BitRun |\n| --- | --- | --- |\n| Kind | Platform | HTTP API |\n| Vendor | Mintplex Labs | Abhishek Khanra (IshekKhal on GitHub) |\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| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-01 | 2026-10-15 |\n| Terms last updated | no date given | no document linked |\n| Privacy policy last updated | no date given | no document linked |\n| Customer content may train models | not found in the text | |\n| Terms restrict automated access | not found in the text | |\n| Terms restrict benchmarking | not found in the text | |\n| Terms or service can change without notice | not found in the text | |\n| Arbitration or class-action waiver | not found in the text | |\n| Popularity | 67k stars | 5 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**BitRun.** BitRun packages patched llama.cpp builds for ternary models into one download for macOS on Apple silicon, Windows and Linux, with a loopback-only OpenAI-compatible server. It is three days old with three pre-release versions, one maintainer and no CI, and its published power figures come from a fixed formula rather than measurement.\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### BitRun\n\n1. Ask the user to install BitRun and run `bitrun pull \u003ctag\u003e` and `bitrun serve \u003ctag\u003e` first. Then call http://127.0.0.1:11435/v1 with any API key string\n2. Poll `/health` before the first request. The server loads the model in the background and answers only when ready\n3. Use a model tag from the catalogue (bitnet-70m, bonsai-1.7b, falcon3-1b, bitnet-2b, falcon3-3b, bonsai-8b) and keep prompts within its context window\n4. Treat the README's energy figures as estimates, and don't report them as measured power\n5. Expect small research checkpoints. Check outputs before relying on them for code or facts\n\n## Questions\n\n### Which is better for AI agents, AnythingLLM or BitRun?\n\nAnythingLLM scores 53.3 (D) on agent readiness against BitRun's 37.9 (F), and leads in 6 of 7 scored categories.\n\n### Can an agent call AnythingLLM and BitRun without installing anything?\n\nNo hosted endpoint is listed for AnythingLLM. No hosted endpoint is listed for BitRun.\n\n### Are AnythingLLM and BitRun 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). BitRun is open source (MIT).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/anythingllm-vs-bitrun.json, and with the fewest tokens: https://www.anchorterminal.com/compare/anythingllm-vs-bitrun.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"anythingllm\", \"b\": \"bitrun\"}`. From a terminal: `anchor compare anythingllm bitrun`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/anythingllm.json and https://www.anchorterminal.com/api/v1/tools/bitrun.json\n\n## Other comparisons with AnythingLLM or BitRun\n\n- [AnythingLLM vs Docker Model Runner](https://www.anchorterminal.com/compare/anythingllm-vs-docker-model-runner.md)\n- [AnythingLLM vs Foundry Local](https://www.anchorterminal.com/compare/anythingllm-vs-foundry-local.md)\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 KoboldCpp](https://www.anchorterminal.com/compare/anythingllm-vs-koboldcpp.md)\n- [AnythingLLM vs Lemonade](https://www.anchorterminal.com/compare/anythingllm-vs-lemonade.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 MLX LM](https://www.anchorterminal.com/compare/anythingllm-vs-mlx-lm.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- [AnythingLLM vs TextGen](https://www.anchorterminal.com/compare/anythingllm-vs-text-generation-webui.md)\n- [AnythingLLM vs vLLM](https://www.anchorterminal.com/compare/anythingllm-vs-vllm.md)\n- [BitRun vs Docker Model Runner](https://www.anchorterminal.com/compare/bitrun-vs-docker-model-runner.md)\n- [BitRun vs Foundry Local](https://www.anchorterminal.com/compare/bitrun-vs-foundry-local.md)\n- [BitRun vs Core](https://www.anchorterminal.com/compare/bitrun-vs-ghost-core.md)\n- [BitRun vs GPT4All](https://www.anchorterminal.com/compare/bitrun-vs-gpt4all.md)\n- [BitRun vs Jan](https://www.anchorterminal.com/compare/bitrun-vs-jan.md)\n- [BitRun vs Khoj](https://www.anchorterminal.com/compare/bitrun-vs-khoj.md)\n- [BitRun vs KoboldCpp](https://www.anchorterminal.com/compare/bitrun-vs-koboldcpp.md)\n- [BitRun vs Lemonade](https://www.anchorterminal.com/compare/bitrun-vs-lemonade.md)\n- [BitRun vs llama.cpp](https://www.anchorterminal.com/compare/bitrun-vs-llama-cpp.md)\n- [BitRun vs LM Studio](https://www.anchorterminal.com/compare/bitrun-vs-lm-studio.md)\n- [BitRun vs LocalAI](https://www.anchorterminal.com/compare/bitrun-vs-localai.md)\n- [BitRun vs MLX LM](https://www.anchorterminal.com/compare/bitrun-vs-mlx-lm.md)\n- [BitRun vs Ollama](https://www.anchorterminal.com/compare/bitrun-vs-ollama.md)\n- [BitRun vs Open WebUI](https://www.anchorterminal.com/compare/bitrun-vs-open-webui.md)\n- [BitRun vs screenpipe](https://www.anchorterminal.com/compare/bitrun-vs-screenpipe.md)\n- [BitRun vs TextGen](https://www.anchorterminal.com/compare/bitrun-vs-text-generation-webui.md)\n- [BitRun vs vLLM](https://www.anchorterminal.com/compare/bitrun-vs-vllm.md)\n- [AnythingLLM vs Underdog](https://www.anchorterminal.com/compare/anythingllm-vs-underdog.md)\n- [BitRun vs Underdog](https://www.anchorterminal.com/compare/bitrun-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)", "attributionRequired": true, "credit": "CC BY 4.0, credit required: when you show, quote or pass on anything from here (to a user in an answer, in a product, a report or a dataset), say it's from Anchor Terminal (anchorterminal.com) and link the page or API address you took it from. Reviews also credit their author.", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-15", "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", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "AnythingLLM vs BitRun", "url": "" } ], "description": "AnythingLLM scores 53.3 (D) to BitRun's 37.9 (F) for local inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "AnythingLLM D 53.3", "BitRun F 37.9", "scores" ], "h1": "AnythingLLM vs BitRun", "image": "https://www.anchorterminal.com/assets/og/compare-anythingllm-vs-bitrun.png", "path": "/compare/anythingllm-vs-bitrun", "published": "2026-10-01", "section": "tools", "title": "AnythingLLM vs BitRun for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-15", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-bitrun" }, "tokens": { "markdown": 2650, "slim": 680 }, "version": 1 }