{ "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": "Foundry Local scores 60.5 (C) on agent readiness against BitRun's 37.9 (F), and leads in 6 of 7 scored categories.", "b": { "slug": "foundry-local", "name": "Foundry Local", "vendor": "Microsoft", "vendorUrl": "https://www.foundrylocal.ai", "kind": "sdk", "category": "local-ai", "summary": "Microsoft's on-device model runtime, built on ONNX Runtime. Applications embed it through SDKs for C#, JavaScript, Python and Rust, and it can start an optional OpenAI-compatible server on localhost. A preview CLI is also available.", "url": "https://www.anchorterminal.com/tools/foundry-local", "markdownUrl": "https://www.anchorterminal.com/tools/foundry-local.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/foundry-local.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/foundry-local.json", "repo": "https://github.com/microsoft/Foundry-Local", "license": "MIT for the SDKs and the v2 native runtime. The CLI is closed source under Microsoft Software Licence Terms. Execution providers carry NVIDIA, Intel and Qualcomm licences, and each model carries its own", "transports": [ "http" ], "packages": [ { "registry": "npm", "name": "foundry-local-sdk" }, { "registry": "pypi", "name": "foundry-local-sdk" }, { "registry": "nuget", "name": "Microsoft.AI.Foundry.Local" }, { "registry": "cargo", "name": "foundry-local-sdk" } ], "auth": "none", "authNotes": "No authentication. The SDK runs in the application's own process, and the optional local server takes no key or token. It binds to 127.0.0.1 on a dynamic port unless the owner configures `web.urls` or starts the CLI daemon with `--port`. No account or Azure subscription is needed.", "pricing": "free", "pricingNotes": "Free, with no account, card or Azure subscription. The SDK is MIT and the CLI is a free download under Microsoft's licence terms. Microsoft states there are no per-token costs. Foundry Local on Azure Local is a separate product for servers and is not covered here (checked 2026-10-08).", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs, the README or the SDK source (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 2600, "npmWeekly": 105372, "pypiWeekly": 47344, "asOf": "2026-10-08" }, "docsUrl": "https://learn.microsoft.com/en-us/azure/foundry-local/", "capabilities": [ "inference.local", "inference.open-weights", "embed.text", "speech.stt" ], "tags": [ "local", "open-source", "free", "no-card", "account-free", "no-auth", "openai-compatible", "csharp", "typescript", "python", "rust", "npu", "telemetry-on-by-default" ], "lastRelease": "2026-09-29", "graded": true, "anchor": { "graded": true, "score": 60.5, "grade": "C", "agentReady": false, "rank": 545, "ranked": true, "rankOf": 1094, "categoryRank": 4, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 61, "maintenance": 88, "payments": 60, "reliability": 68, "schema": 53, "security": 39, "transparency": 72 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "The SDK and its native runtime are MIT, at 2.1.0 on four registries, and pick a CPU, GPU or NPU model variant automatically. The optional local server has no credential, its current routes aren't in the published REST reference, and telemetry is on by default with an opt-out.", "bestFor": "An application that ships a model to end users' Windows, macOS or Linux devices and wants NPU and GPU variants chosen automatically, especially on Windows.", "strengths": [ "SDK 2.1.0 published on npm, PyPI, NuGet and crates.io on 29 September 2026, with the SDK and the v2 native runtime under MIT in a public repository", "A model alias selects the best variant for the machine's CPU, GPU or NPU, with CUDA, WebGPU, OpenVINO, QNN and Vitis AI execution providers", "The v2 server answers `/v1/chat/completions`, `/v1/responses`, `/v1/embeddings`, `/v1/audio/transcriptions` and `/v1/models` in OpenAI's shapes", "Six releases in the 90 days to 8 October 2026, and the v2.0.1 notes carry a breaking-changes section", "No account, key, card or Azure subscription is needed, and prompts and outputs are processed on the device per the docs" ], "weaknesses": [ "The local server takes no credential, and its routes include model load and unload and `POST /shutdown`", "The REST reference on Microsoft Learn lists `/openai/*` and `/foundry/list` routes that the v2 runtime source doesn't register, and doesn't cover `/v1/responses`", "Telemetry is on by default through Microsoft's 1DS SDK. The opt-out covers non-essential telemetry only, and the Learn FAQ doesn't mention it", "The CLI is a closed-source public preview, and its REST reference warns of breaking changes without notice", "76 open issues on 8 October 2026, among them a Linux ARM64 segmentation fault (#1182) and several unanswered GPU and NPU detection reports" ], "agentNotes": [ "Read the server URL from `manager.urls[0]` or `foundry server status`. The port is dynamic unless the owner sets `web.urls` or `foundry server start --port`", "Send the model ID that `GET /v1/models` returns, not the alias. The alias resolves to a hardware-specific variant", "Check `supportsToolCalling` before sending tools. Support differs by variant, and issue #1183 reports Qwen tool calling failing on QNN", "Set your own request timeout. Inference has no built-in one, and cancellation takes effect only after the current generation step", "Ask the owner to set `ORT_TELEMETRY_DISABLED=1` or `disableNonessentialTelemetry` before the manager is created if telemetry must be off" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 60.5 } ], "editorialScores": { "ergonomics": 61, "maintenance": 88, "payments": 60, "reliability": 68, "schema": 53, "security": 39, "transparency": 63 }, "provenanceScore": 80 }, "connect": { "install": "pip install foundry-local-sdk # or: npm install foundry-local-sdk\n# CLI (preview): winget install Microsoft.FoundryLocal # macOS: brew tap microsoft/foundrylocal \u0026\u0026 brew install foundrylocal", "http": "foundry server start --port 39839 --idle-timeout 0\ncurl http://localhost:39839/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"\u003cMODEL_ID\u003e\", \"messages\": [{\"role\": \"user\", \"content\": \"What is the golden ratio?\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/foundry-local" }, "sameCompany": [ "azure-foundry-fine-tuning", "azure-ai-content-safety", "azure-speech-to-text", "azure-text-to-speech", "microsoft-agent-framework", "microsoft-execution-containers", "microsoft-entra-agent-id", "azure-key-vault", "azure-document-intelligence", "azure-devops-mcp", "microsoft-learn-mcp", "playwright-mcp", "azure-mcp", "azure-maps", "azure-translator", "microsoft-graph-calendar", "azure-blob-storage", "onedrive-sharepoint", "microsoft-teams", "dynamics-365-sales", "power-automate", "microsoft-decision-1", "microsoft-advertising-api", "microsoft-excel-graph", "outlook-mail-graph", "microsoft-graph-people" ], "area": "models", "provenance": { "legalEntity": "Microsoft Corporation", "domain": "microsoft.com", "domainRegistered": "1991-05-02", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/microsoft/Foundry-Local/releases", "securityTxt": "expired", "checked": "2026-10-08", "notes": [ "The repository is under GitHub's microsoft organisation, the licence file reads Copyright (c) Microsoft Corporation, and foundrylocal.ai names Microsoft Corporation as publisher.", "The terms link is the repository's LICENSE file, which holds the MIT licence for the SDK and the Microsoft Software Licence Terms for the CLI. Microsoft publishes no other agreement for Foundry Local that we found.", "The privacy link is the product's own privacy file in the repository, which the README links. It and the CLI licence both refer on to the Microsoft Privacy Statement, a company-wide notice, which answered 403 to our request.", "www.microsoft.com/.well-known/security.txt loads and points to the MSRC researcher portal, but its Expires field is 2026-09-23T16:00:00.000Z, which had passed on 8 October 2026. learn.microsoft.com and foundrylocal.ai return 404.", "No status page is listed because the software runs on the owner's machine. The model catalogue is a cloud service with no status page that we found.", "RDAP gives microsoft.com a registration date of 1991-05-02 and foundrylocal.ai one of 2025-10-07." ], "score": 80 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/foundry-local.json", "live": { "slug": "foundry-local", "versions": [ { "registry": "github", "name": "microsoft/Foundry-Local", "version": "v2.1.0", "released": "2026-09-30", "seenAt": "2026-10-14T23:53:09.342346231Z" }, { "registry": "npm", "name": "foundry-local-sdk", "version": "2.1.0", "seenAt": "2026-10-14T23:53:08.555520895Z" }, { "registry": "pypi", "name": "foundry-local-sdk", "version": "2.1.0", "released": "2026-09-29", "seenAt": "2026-10-14T23:53:09.152790871Z" } ], "githubStars": 2587, "npmWeekly": 24143, "pypiWeekly": 48300, "securityTxt": { "url": "https://microsoft.com/.well-known/security.txt", "state": "expired", "expires": "2026-09-23T16:00:00.000Z", "checkedAt": "2026-10-14T15:46:30.527013799Z" }, "domain": { "domain": "microsoft.com", "registered": "1991-05-02", "source": "https://rdap.verisign.com/com/v1/domain/microsoft.com", "checkedAt": "2026-10-11T13:11:44.704195317Z" }, "updatedAt": "2026-10-14T23:53:09.342346231Z" } }, "facts": [ { "a": "HTTP API", "b": "SDK + MCP", "name": "Kind" }, { "a": "Abhishek Khanra (IshekKhal on GitHub)", "b": "Microsoft", "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 for the SDKs and the v2 native runtime. The CLI is closed source under Microsoft Software Licence Terms. Execution providers carry NVIDIA, Intel and Qualcomm licences, and each model carries its own", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-10-15", "b": "2026-09-29", "name": "Last release" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "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": "2.6k stars, 105k npm/wk, 47k PyPI/wk", "name": "Popularity" } ], "faq": [ { "answer": "Foundry Local scores 60.5 (C) on agent readiness against BitRun's 37.9 (F), and leads in 6 of 7 scored categories.", "question": "Which is better for AI agents, BitRun or Foundry Local?" }, { "answer": "No hosted endpoint is listed for BitRun. No hosted endpoint is listed for Foundry Local.", "question": "Can an agent call BitRun and Foundry Local without installing anything?" }, { "answer": "Yes. BitRun is open source (MIT). Foundry Local is open source (MIT for the SDKs and the v2 native runtime. The CLI is closed source under Microsoft Software Licence Terms. Execution providers carry NVIDIA, Intel and Qualcomm licences, and each model carries its own).", "question": "Are BitRun and Foundry Local open source?" } ], "goodFor": [ { "aheadOn": null, "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, 68 against 38", "Schema \u0026 documentation, 53 against 30", "Agent ergonomics, 61 against 40", "Security \u0026 auth, 39 against 28", "Maintenance \u0026 community, 88 against 59", "Transparency \u0026 trust, 72 against 50" ], "also": [ "No incidents deducted, where BitRun loses 3 points for them" ], "goodFor": "An application that ships a model to end users' Windows, macOS or Linux devices and wants NPU and GPU variants chosen automatically, especially on Windows.", "slug": "foundry-local", "watchFor": "The local server takes no credential, and its routes include model load and unload and `POST /shutdown`" } ], "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-foundry-local.json", "title": "AnythingLLM vs Foundry Local", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-foundry-local" }, { "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-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/docker-model-runner-vs-foundry-local.json", "title": "Docker Model Runner vs Foundry Local", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-foundry-local" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-ghost-core.json", "title": "Foundry Local vs Core", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-ghost-core" }, { "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/foundry-local-vs-jan.json", "title": "Foundry Local vs Jan", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-jan" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-khoj.json", "title": "Foundry Local vs Khoj", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-khoj" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-koboldcpp.json", "title": "Foundry Local vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-lemonade.json", "title": "Foundry Local vs Lemonade", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-llama-cpp.json", "title": "Foundry Local vs llama.cpp", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-llama-cpp" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-lm-studio.json", "title": "Foundry Local vs LM Studio", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-localai.json", "title": "Foundry Local vs LocalAI", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-mlx-lm.json", "title": "Foundry Local vs MLX LM", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-ollama.json", "title": "Foundry Local vs Ollama", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-open-webui.json", "title": "Foundry Local vs Open WebUI", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-screenpipe.json", "title": "Foundry Local vs screenpipe", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-text-generation-webui.json", "title": "Foundry Local vs TextGen", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/foundry-local-vs-vllm.json", "title": "Foundry Local vs vLLM", "url": "https://www.anchorterminal.com/compare/foundry-local-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/foundry-local-vs-underdog.json", "title": "Foundry Local vs Underdog", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-underdog" } ], "scores": [ { "bitrun": 38, "by": 30, "edge": "foundry-local", "foundry-local": 68, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "bitrun": 30, "by": 23, "edge": "foundry-local", "foundry-local": 53, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "bitrun": 40, "by": 21, "edge": "foundry-local", "foundry-local": 61, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "bitrun": 28, "by": 11, "edge": "foundry-local", "foundry-local": 39, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "bitrun": 60, "by": 0, "edge": "", "foundry-local": 60, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "bitrun": 59, "by": 29, "edge": "foundry-local", "foundry-local": 88, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "bitrun": 50, "by": 22, "edge": "foundry-local", "foundry-local": 72, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Foundry Local scores 60.5 (C) on agent readiness against BitRun's 37.9 (F), and leads in 6 of 7 scored categories. 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.", "foundry-local": "The SDK and its native runtime are MIT, at 2.1.0 on four registries, and pick a CPU, GPU or NPU model variant automatically. The optional local server has no credential, its current routes aren't in the published REST reference, and telemetry is on by default with an opt-out." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/bitrun-vs-foundry-local", "json": "https://www.anchorterminal.com/compare/bitrun-vs-foundry-local.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/bitrun-vs-foundry-local.md", "slim": "https://www.anchorterminal.com/compare/bitrun-vs-foundry-local.min.md" }, "markdown": "Foundry Local scores 60.5 (C) on agent readiness against BitRun's 37.9 (F), and leads in 6 of 7 scored categories. 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- Foundry Local: grade C, 60.5/100, rank #545 of 1094. Markdown https://www.anchorterminal.com/tools/foundry-local.md · JSON https://www.anchorterminal.com/api/v1/tools/foundry-local.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\nWatch for: First released on 12 October 2026. Three pre-release versions in four days, one maintainer and no CI workflow\n\n### Foundry Local (C)\n\nGood for: An application that ships a model to end users' Windows, macOS or Linux devices and wants NPU and GPU variants chosen automatically, especially on Windows.\n\nAhead on:\n- Reliability, 68 against 38\n- Schema \u0026 documentation, 53 against 30\n- Agent ergonomics, 61 against 40\n- Security \u0026 auth, 39 against 28\n- Maintenance \u0026 community, 88 against 59\n- Transparency \u0026 trust, 72 against 50\n\nAlso in its favour:\n- No incidents deducted, where BitRun loses 3 points for them\n\nWatch for: The local server takes no credential, and its routes include model load and unload and `POST /shutdown`\n\n\n## Score by category\n\n| Category | Weight | BitRun | Foundry Local | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 38 | 68 | Foundry Local +30 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 30 | 53 | Foundry Local +23 |\n| Agent ergonomics | 13% (16.2 this run) | 40 | 61 | Foundry Local +21 |\n| Security \u0026 auth | 14% (17.5 this run) | 28 | 39 | Foundry Local +11 |\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 | 88 | Foundry Local +29 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 50 | 72 | Foundry Local +22 |\n| Negative events | ≤15 | -3 | 0 | |\n| **Total** | | **37.9 · F** | **60.5 · C** | |\n\n## Facts side by side\n\n| Fact | BitRun | Foundry Local |\n| --- | --- | --- |\n| Kind | HTTP API | SDK + MCP |\n| Vendor | Abhishek Khanra (IshekKhal on GitHub) | Microsoft |\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 for the SDKs and the v2 native runtime. The CLI is closed source under Microsoft Software Licence Terms. Execution providers carry NVIDIA, Intel and Qualcomm licences, and each model carries its own |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-15 | 2026-09-29 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\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 | 2.6k stars, 105k npm/wk, 47k PyPI/wk |\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**Foundry Local.** The SDK and its native runtime are MIT, at 2.1.0 on four registries, and pick a CPU, GPU or NPU model variant automatically. The optional local server has no credential, its current routes aren't in the published REST reference, and telemetry is on by default with an opt-out.\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### Foundry Local\n\n1. Read the server URL from `manager.urls[0]` or `foundry server status`. The port is dynamic unless the owner sets `web.urls` or `foundry server start --port`\n2. Send the model ID that `GET /v1/models` returns, not the alias. The alias resolves to a hardware-specific variant\n3. Check `supportsToolCalling` before sending tools. Support differs by variant, and issue #1183 reports Qwen tool calling failing on QNN\n4. Set your own request timeout. Inference has no built-in one, and cancellation takes effect only after the current generation step\n5. Ask the owner to set `ORT_TELEMETRY_DISABLED=1` or `disableNonessentialTelemetry` before the manager is created if telemetry must be off\n\n## Questions\n\n### Which is better for AI agents, BitRun or Foundry Local?\n\nFoundry Local scores 60.5 (C) on agent readiness against BitRun's 37.9 (F), and leads in 6 of 7 scored categories.\n\n### Can an agent call BitRun and Foundry Local without installing anything?\n\nNo hosted endpoint is listed for BitRun. No hosted endpoint is listed for Foundry Local.\n\n### Are BitRun and Foundry Local open source?\n\nYes. BitRun is open source (MIT). Foundry Local is open source (MIT for the SDKs and the v2 native runtime. The CLI is closed source under Microsoft Software Licence Terms. Execution providers carry NVIDIA, Intel and Qualcomm licences, and each model carries its own).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/bitrun-vs-foundry-local.json, and with the fewest tokens: https://www.anchorterminal.com/compare/bitrun-vs-foundry-local.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"bitrun\", \"b\": \"foundry-local\"}`. From a terminal: `anchor compare bitrun foundry-local`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/bitrun.json and https://www.anchorterminal.com/api/v1/tools/foundry-local.json\n\n## Other comparisons with BitRun or Foundry Local\n\n- [AnythingLLM vs BitRun](https://www.anchorterminal.com/compare/anythingllm-vs-bitrun.md)\n- [AnythingLLM vs Foundry Local](https://www.anchorterminal.com/compare/anythingllm-vs-foundry-local.md)\n- [BitRun vs Docker Model Runner](https://www.anchorterminal.com/compare/bitrun-vs-docker-model-runner.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- [Docker Model Runner vs Foundry Local](https://www.anchorterminal.com/compare/docker-model-runner-vs-foundry-local.md)\n- [Foundry Local vs Core](https://www.anchorterminal.com/compare/foundry-local-vs-ghost-core.md)\n- [Foundry Local vs GPT4All](https://www.anchorterminal.com/compare/foundry-local-vs-gpt4all.md)\n- [Foundry Local vs Jan](https://www.anchorterminal.com/compare/foundry-local-vs-jan.md)\n- [Foundry Local vs Khoj](https://www.anchorterminal.com/compare/foundry-local-vs-khoj.md)\n- [Foundry Local vs KoboldCpp](https://www.anchorterminal.com/compare/foundry-local-vs-koboldcpp.md)\n- [Foundry Local vs Lemonade](https://www.anchorterminal.com/compare/foundry-local-vs-lemonade.md)\n- [Foundry Local vs llama.cpp](https://www.anchorterminal.com/compare/foundry-local-vs-llama-cpp.md)\n- [Foundry Local vs LM Studio](https://www.anchorterminal.com/compare/foundry-local-vs-lm-studio.md)\n- [Foundry Local vs LocalAI](https://www.anchorterminal.com/compare/foundry-local-vs-localai.md)\n- [Foundry Local vs MLX LM](https://www.anchorterminal.com/compare/foundry-local-vs-mlx-lm.md)\n- [Foundry Local vs Ollama](https://www.anchorterminal.com/compare/foundry-local-vs-ollama.md)\n- [Foundry Local vs Open WebUI](https://www.anchorterminal.com/compare/foundry-local-vs-open-webui.md)\n- [Foundry Local vs screenpipe](https://www.anchorterminal.com/compare/foundry-local-vs-screenpipe.md)\n- [Foundry Local vs TextGen](https://www.anchorterminal.com/compare/foundry-local-vs-text-generation-webui.md)\n- [Foundry Local vs vLLM](https://www.anchorterminal.com/compare/foundry-local-vs-vllm.md)\n- [BitRun vs Underdog](https://www.anchorterminal.com/compare/bitrun-vs-underdog.md)\n- [Foundry Local vs Underdog](https://www.anchorterminal.com/compare/foundry-local-vs-underdog.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 Foundry Local", "url": "" } ], "description": "Foundry Local scores 60.5 (C) to BitRun's 37.9 (F) for local inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "BitRun F 37.9", "Foundry Local C 60.5", "scores" ], "h1": "BitRun vs Foundry Local", "image": "https://www.anchorterminal.com/assets/og/compare-bitrun-vs-foundry-local.png", "path": "/compare/bitrun-vs-foundry-local", "published": "2026-10-01", "section": "tools", "title": "BitRun vs Foundry Local for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-15", "url": "https://www.anchorterminal.com/compare/bitrun-vs-foundry-local" }, "tokens": { "markdown": 2700, "slim": 580 }, "version": 1 }