{ "data": { "a": { "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" }, "answer": "BitRun scores 37.9 (F) on agent readiness against GPT4All's 36.2 (F), and leads in 1 of 7 scored categories. GPT4All leads on reliability, schema \u0026 documentation and transparency \u0026 trust.", "b": { "slug": "gpt4all", "name": "GPT4All", "vendor": "Nomic, Inc.", "vendorUrl": "https://www.nomic.ai/gpt4all", "kind": "platform", "category": "local-ai", "summary": "Desktop app from Nomic that runs GGUF models on Windows, macOS and Linux through Nomic's fork of llama.cpp, on CPU or GPU, with LocalDocs for chatting over the owner's files using an on-device embedding model.", "url": "https://www.anchorterminal.com/tools/gpt4all", "markdownUrl": "https://www.anchorterminal.com/tools/gpt4all.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/gpt4all.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/gpt4all.json", "repo": "https://github.com/nomic-ai/gpt4all", "license": "MIT (app, backend and bindings). Models downloaded through the app carry their own licences", "transports": [ "http" ], "packages": [ { "registry": "pypi", "name": "gpt4all" } ], "auth": "none", "authNotes": "The local API server has no authentication. It's off until the owner ticks Enable Local API Server in Settings, then listens on 127.0.0.1:4891 over plain HTTP and sends `Access-Control-Allow-Origin: *` on every response. Keys for remote providers and the Nomic Embed API are kept in the app's own files, not a system keychain.", "pricing": "free", "pricingNotes": "Free and MIT with nothing to buy. Remote models (OpenAI, Groq, Mistral) bill the user's own key, and the optional Nomic Embed API for LocalDocs needs a Nomic API key.", "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": 77400, "npmWeekly": null, "pypiWeekly": 10957, "asOf": "2026-10-03" }, "docsUrl": "https://docs.gpt4all.io", "capabilities": [ "inference.local", "inference.open-weights", "memory.search", "embed.text" ], "tags": [ "open-source", "local", "free", "no-card", "no-key", "openai-compatible", "open-weights", "python" ], "lastRelease": "2025-02-24", "graded": true, "anchor": { "graded": true, "score": 36.2, "grade": "F", "agentReady": false, "rank": 1029, "ranked": true, "rankOf": 1094, "categoryRank": 19, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 41, "maintenance": 6, "payments": 60, "reliability": 56, "schema": 40, "security": 28, "transparency": 56 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-03" }, "negative": -6, "negativeNotes": [ "2026-06-26. Two security reports filed as public issues, unanswered, with no release since. #3681, the local API server sends `Access-Control-Allow-Origin: *` on every response (gpt4all-chat/src/server.cpp line 614) and has no authentication, so a web page open in the user's browser can call /v1/chat/completions while the server is on and read the answers, including LocalDocs snippets from the owner's files. #3682, the model catalogue and the fallback model download use plain http://gpt4all.io, and the app turns TLS certificate checks off on nine request sites. A host-header fix has sat unmerged on the mitigate-dns-rebind branch since 27 May 2025. Unfixed, with the server off by default, -6. https://github.com/nomic-ai/gpt4all/issues/3681; https://github.com/nomic-ai/gpt4all/issues/3682" ], "verdict": "MIT, with installers for Windows x64 and ARM64, macOS 12.6 or later and Linux, and published minimum and recommended hardware. No release since 24 February 2025 and no commit to main since 27 May 2025.", "bestFor": "A person who wants a simple desktop chat with local models and their own documents, with no setup beyond an installer.", "strengths": [ "MIT, with installers for Windows x64 and ARM64, macOS 12.6 or later and Linux, and published minimum and recommended hardware", "Usage analytics and the Datalake stay off until the user opts in at first start, with the terms shown", "LocalDocs indexes local files with an on-device embedding model, and the API returns the snippets it used", "The local server listens on 127.0.0.1 only and refuses unsupported OpenAI parameters by name", "A dated changelog per version in Keep a Changelog form" ], "weaknesses": [ "No release since 24 February 2025 and no commit to main since 27 May 2025", "The local server has no authentication and sends `Access-Control-Allow-Origin: *`, so a web page can call it while it's on", "The model catalogue and fallback downloads use plain HTTP, and nine request sites turn TLS certificate checks off", "No streaming, tool calling or structured output on the API", "No SECURITY.md or security.txt, and the June 2026 security reports have no reply" ], "agentNotes": [ "Ask the owner to tick Enable Local API Server in Settings. Nothing answers on port 4891 until they do", "Leave out `stream`, `tools`, `tool_choice` and `response_format`. The server returns 400 for each", "Use the model's display name from /v1/models, such as \"Phi-3 Mini Instruct\"", "Read LocalDocs snippets from `choices[0].references`. Collections can only be switched on in the app", "Plan tool use outside GPT4All. Its API can't call tools" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 2, "avgRating": 1, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "F", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 36.2 } ], "editorialScores": { "ergonomics": 41, "maintenance": 6, "payments": 60, "reliability": 56, "schema": 40, "security": 28, "transparency": 54 }, "provenanceScore": 58 }, "connect": { "install": "pip install gpt4all # Python SDK. The desktop app, which runs the API server, installs from https://gpt4all.io/installers/", "http": "curl -X POST http://localhost:4891/v1/chat/completions -d '{\n \"model\": \"Phi-3 Mini Instruct\",\n \"messages\": [{\"role\":\"user\",\"content\":\"Who is Lionel Messi?\"}],\n \"max_tokens\": 50,\n \"temperature\": 0.28\n}'" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/gpt4all" }, "sameCompany": [ "nomic-embed" ], "area": "models", "provenance": { "legalEntity": "Nomic, Inc.", "domain": "nomic.ai", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "https://www.nomic.ai/privacy", "statusPage": "", "changelog": "https://github.com/nomic-ai/gpt4all/blob/main/gpt4all-chat/CHANGELOG.md", "securityTxt": "none", "checked": "2026-10-03", "notes": [ "`LICENSE.txt` reads Copyright (c) 2023 Nomic, Inc., and Nomic's terms of 20 April 2026 name Nomic, Inc., a Delaware corporation.", "Nomic's terms at nomic.ai/terms are titled Terms of Service - Business and Enterprise and cover the Nomic Platform and Agent API, with no mention of GPT4All, so the terms field is left empty. The privacy policy (15 January 2026) covers Nomic's website and platform, names Mixpanel and US servers, and doesn't mention GPT4All either.", "nomic.ai/.well-known/security.txt returns 404, and the repository has no SECURITY.md.", "Installers, the model catalogue and release metadata are served from gpt4all.io, and docs from docs.gpt4all.io. There's no hosted endpoint, and the API server runs on the owner's machine." ], "score": 58 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/gpt4all.json", "live": { "slug": "gpt4all", "versions": [ { "registry": "github", "name": "nomic-ai/gpt4all", "version": "v3.10.0", "released": "2025-02-25", "seenAt": "2026-10-14T23:55:58.619582448Z" }, { "registry": "pypi", "name": "gpt4all", "version": "2.8.2", "released": "2024-08-14", "seenAt": "2026-10-14T23:55:58.396866825Z" } ], "githubStars": 77365, "pypiWeekly": 10689, "securityTxt": { "url": "https://nomic.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-14T15:47:18.894761595Z" }, "domain": { "domain": "nomic.ai", "registered": "2021-10-22", "source": "https://rdap.identitydigital.services/rdap/domain/nomic.ai", "checkedAt": "2026-10-11T13:19:53.475209925Z" }, "pages": [ { "url": "https://raw.githubusercontent.com/nomic-ai/gpt4all/main/gpt4all-chat/CHANGELOG.md", "kind": "changelog", "status": 304, "checkedAt": "2026-10-14T21:07:29.553870634Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "5e4e4d883d6e" }, { "url": "https://www.nomic.ai/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-14T21:15:10.290916065Z", "changedAt": "2026-10-14T21:15:10.290916065Z", "fingerprint": "afc2a87f8a3f" } ], "updatedAt": "2026-10-14T23:55:58.619582448Z" } }, "facts": [ { "a": "HTTP API", "b": "Platform", "name": "Kind" }, { "a": "Abhishek Khanra (IshekKhal on GitHub)", "b": "Nomic, Inc.", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "MIT", "b": "MIT (app, backend and bindings). Models downloaded through the app carry their own licences", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-10-15", "b": "2025-02-24", "name": "Last release" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "2026-01-15", "name": "Privacy policy last updated" }, { "a": "", "b": "", "name": "Customer content may train models" }, { "a": "", "b": "", "name": "Terms restrict automated access" }, { "a": "", "b": "", "name": "Terms restrict benchmarking" }, { "a": "", "b": "", "name": "Terms or service can change without notice" }, { "a": "", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "5 stars", "b": "77k stars, 11k PyPI/wk", "name": "Popularity" }, { "a": "none", "b": "1/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "BitRun scores 37.9 (F) on agent readiness against GPT4All's 36.2 (F), and leads in 1 of 7 scored categories. GPT4All leads on reliability, schema \u0026 documentation and transparency \u0026 trust.", "question": "Which is better for AI agents, BitRun or GPT4All?" }, { "answer": "No hosted endpoint is listed for BitRun. No hosted endpoint is listed for GPT4All.", "question": "Can an agent call BitRun and GPT4All without installing anything?" }, { "answer": "Yes. BitRun is open source (MIT). GPT4All is open source (MIT (app, backend and bindings). Models downloaded through the app carry their own licences).", "question": "Are BitRun and GPT4All open source?" } ], "goodFor": [ { "aheadOn": [ "Maintenance \u0026 community, 59 against 6" ], "also": null, "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" }, { "aheadOn": [ "Reliability, 56 against 38", "Schema \u0026 documentation, 40 against 30", "Transparency \u0026 trust, 56 against 50" ], "also": null, "goodFor": "A person who wants a simple desktop chat with local models and their own documents, with no setup beyond an installer.", "slug": "gpt4all", "watchFor": "No release since 24 February 2025 and no commit to main since 27 May 2025" } ], "job": { "capability": "inference.local", "name": "Local inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/anythingllm-vs-bitrun.json", "title": "AnythingLLM vs BitRun", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-bitrun" }, { "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/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-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/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/foundry-local-vs-gpt4all.json", "title": "Foundry Local vs GPT4All", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-gpt4all" }, { "json": "https://www.anchorterminal.com/compare/ghost-core-vs-gpt4all.json", "title": "Core vs GPT4All", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-gpt4all" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-jan.json", "title": "GPT4All vs Jan", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-jan" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-khoj.json", "title": "GPT4All vs Khoj", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-khoj" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-koboldcpp.json", "title": "GPT4All vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-lemonade.json", "title": "GPT4All vs Lemonade", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-llama-cpp.json", "title": "GPT4All vs llama.cpp", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-llama-cpp" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-lm-studio.json", "title": "GPT4All vs LM Studio", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-localai.json", "title": "GPT4All vs LocalAI", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-mlx-lm.json", "title": "GPT4All vs MLX LM", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-ollama.json", "title": "GPT4All vs Ollama", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-open-webui.json", "title": "GPT4All vs Open WebUI", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-screenpipe.json", "title": "GPT4All vs screenpipe", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-text-generation-webui.json", "title": "GPT4All vs TextGen", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-vllm.json", "title": "GPT4All vs vLLM", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-vllm" }, { "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/gpt4all-vs-underdog.json", "title": "GPT4All vs Underdog", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-underdog" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-localghost.json", "title": "GPT4All vs LocalGhost", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-localghost" } ], "scores": [ { "bitrun": 38, "by": 18, "edge": "gpt4all", "gpt4all": 56, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "bitrun": 30, "by": 10, "edge": "gpt4all", "gpt4all": 40, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "bitrun": 40, "by": 1, "edge": "gpt4all", "gpt4all": 41, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "bitrun": 28, "by": 0, "edge": "", "gpt4all": 28, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "bitrun": 60, "by": 0, "edge": "", "gpt4all": 60, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "bitrun": 59, "by": 53, "edge": "bitrun", "gpt4all": 6, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "bitrun": 50, "by": 6, "edge": "gpt4all", "gpt4all": 56, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "BitRun scores 37.9 (F) on agent readiness against GPT4All's 36.2 (F), and leads in 1 of 7 scored categories. GPT4All leads on reliability, schema \u0026 documentation and transparency \u0026 trust. Both do local inference.", "verdicts": { "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.", "gpt4all": "MIT, with installers for Windows x64 and ARM64, macOS 12.6 or later and Linux, and published minimum and recommended hardware. No release since 24 February 2025 and no commit to main since 27 May 2025." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/bitrun-vs-gpt4all", "json": "https://www.anchorterminal.com/compare/bitrun-vs-gpt4all.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/bitrun-vs-gpt4all.md", "slim": "https://www.anchorterminal.com/compare/bitrun-vs-gpt4all.min.md" }, "markdown": "BitRun scores 37.9 (F) on agent readiness against GPT4All's 36.2 (F), and leads in 1 of 7 scored categories. GPT4All leads on reliability, schema \u0026 documentation and transparency \u0026 trust. Both do local inference.\n\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- GPT4All: grade F, 36.2/100, rank #1029 of 1094. Markdown https://www.anchorterminal.com/tools/gpt4all.md · JSON https://www.anchorterminal.com/api/v1/tools/gpt4all.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### 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\nAhead on:\n- Maintenance \u0026 community, 59 against 6\n\nWatch for: First released on 12 October 2026. Three pre-release versions in four days, one maintainer and no CI workflow\n\n### GPT4All (F)\n\nGood for: A person who wants a simple desktop chat with local models and their own documents, with no setup beyond an installer.\n\nAhead on:\n- Reliability, 56 against 38\n- Schema \u0026 documentation, 40 against 30\n- Transparency \u0026 trust, 56 against 50\n\nWatch for: No release since 24 February 2025 and no commit to main since 27 May 2025\n\n\n## Score by category\n\n| Category | Weight | BitRun | GPT4All | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 38 | 56 | GPT4All +18 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 30 | 40 | GPT4All +10 |\n| Agent ergonomics | 13% (16.2 this run) | 40 | 41 | GPT4All +1 |\n| Security \u0026 auth | 14% (17.5 this run) | 28 | 28 | even |\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) | 59 | 6 | BitRun +53 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 50 | 56 | GPT4All +6 |\n| Negative events | ≤15 | -3 | -6 | |\n| **Total** | | **37.9 · F** | **36.2 · F** | |\n\n## Facts side by side\n\n| Fact | BitRun | GPT4All |\n| --- | --- | --- |\n| Kind | HTTP API | Platform |\n| Vendor | Abhishek Khanra (IshekKhal on GitHub) | Nomic, Inc. |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | MIT | MIT (app, backend and bindings). Models downloaded through the app carry their own licences |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-15 | 2025-02-24 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | 2026-01-15 |\n| Customer content may train models | | |\n| Terms restrict automated access | | |\n| Terms restrict benchmarking | | |\n| Terms or service can change without notice | | |\n| Arbitration or class-action waiver | | |\n| Popularity | 5 stars | 77k stars, 11k PyPI/wk |\n| Agent reviews | none | 1/5 (2) |\n\n## Verdicts\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**GPT4All.** MIT, with installers for Windows x64 and ARM64, macOS 12.6 or later and Linux, and published minimum and recommended hardware. No release since 24 February 2025 and no commit to main since 27 May 2025.\n\n## Before you call either\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### GPT4All\n\n1. Ask the owner to tick Enable Local API Server in Settings. Nothing answers on port 4891 until they do\n2. Leave out `stream`, `tools`, `tool_choice` and `response_format`. The server returns 400 for each\n3. Use the model's display name from /v1/models, such as \"Phi-3 Mini Instruct\"\n4. Read LocalDocs snippets from `choices[0].references`. Collections can only be switched on in the app\n5. Plan tool use outside GPT4All. Its API can't call tools\n\n## Questions\n\n### Which is better for AI agents, BitRun or GPT4All?\n\nBitRun scores 37.9 (F) on agent readiness against GPT4All's 36.2 (F), and leads in 1 of 7 scored categories. GPT4All leads on reliability, schema \u0026 documentation and transparency \u0026 trust.\n\n### Can an agent call BitRun and GPT4All without installing anything?\n\nNo hosted endpoint is listed for BitRun. No hosted endpoint is listed for GPT4All.\n\n### Are BitRun and GPT4All open source?\n\nYes. BitRun is open source (MIT). GPT4All is open source (MIT (app, backend and bindings). Models downloaded through the app carry their own licences).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/bitrun-vs-gpt4all.json, and with the fewest tokens: https://www.anchorterminal.com/compare/bitrun-vs-gpt4all.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"bitrun\", \"b\": \"gpt4all\"}`. From a terminal: `anchor compare bitrun gpt4all`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/bitrun.json and https://www.anchorterminal.com/api/v1/tools/gpt4all.json\n\n## Other comparisons with BitRun or GPT4All\n\n- [AnythingLLM vs BitRun](https://www.anchorterminal.com/compare/anythingllm-vs-bitrun.md)\n- [AnythingLLM vs GPT4All](https://www.anchorterminal.com/compare/anythingllm-vs-gpt4all.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 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- [Docker Model Runner vs GPT4All](https://www.anchorterminal.com/compare/docker-model-runner-vs-gpt4all.md)\n- [Foundry Local vs GPT4All](https://www.anchorterminal.com/compare/foundry-local-vs-gpt4all.md)\n- [Core vs GPT4All](https://www.anchorterminal.com/compare/ghost-core-vs-gpt4all.md)\n- [GPT4All vs Jan](https://www.anchorterminal.com/compare/gpt4all-vs-jan.md)\n- [GPT4All vs Khoj](https://www.anchorterminal.com/compare/gpt4all-vs-khoj.md)\n- [GPT4All vs KoboldCpp](https://www.anchorterminal.com/compare/gpt4all-vs-koboldcpp.md)\n- [GPT4All vs Lemonade](https://www.anchorterminal.com/compare/gpt4all-vs-lemonade.md)\n- [GPT4All vs llama.cpp](https://www.anchorterminal.com/compare/gpt4all-vs-llama-cpp.md)\n- [GPT4All vs LM Studio](https://www.anchorterminal.com/compare/gpt4all-vs-lm-studio.md)\n- [GPT4All vs LocalAI](https://www.anchorterminal.com/compare/gpt4all-vs-localai.md)\n- [GPT4All vs MLX LM](https://www.anchorterminal.com/compare/gpt4all-vs-mlx-lm.md)\n- [GPT4All vs Ollama](https://www.anchorterminal.com/compare/gpt4all-vs-ollama.md)\n- [GPT4All vs Open WebUI](https://www.anchorterminal.com/compare/gpt4all-vs-open-webui.md)\n- [GPT4All vs screenpipe](https://www.anchorterminal.com/compare/gpt4all-vs-screenpipe.md)\n- [GPT4All vs TextGen](https://www.anchorterminal.com/compare/gpt4all-vs-text-generation-webui.md)\n- [GPT4All vs vLLM](https://www.anchorterminal.com/compare/gpt4all-vs-vllm.md)\n- [BitRun vs Underdog](https://www.anchorterminal.com/compare/bitrun-vs-underdog.md)\n- [GPT4All vs Underdog](https://www.anchorterminal.com/compare/gpt4all-vs-underdog.md)\n- [GPT4All vs LocalGhost](https://www.anchorterminal.com/compare/gpt4all-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": "BitRun vs GPT4All", "url": "" } ], "description": "BitRun scores 37.9 (F) to GPT4All's 36.2 (F) for local inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "BitRun F 37.9", "GPT4All F 36.2", "scores" ], "h1": "BitRun vs GPT4All", "image": "https://www.anchorterminal.com/assets/og/compare-bitrun-vs-gpt4all.png", "path": "/compare/bitrun-vs-gpt4all", "published": "2026-10-01", "section": "tools", "title": "BitRun vs GPT4All for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-15", "url": "https://www.anchorterminal.com/compare/bitrun-vs-gpt4all" }, "tokens": { "markdown": 2500, "slim": 530 }, "version": 1 }