{ "data": { "a": { "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": 592, "ranked": true, "rankOf": 1239, "categoryRank": 7, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 61, "maintenance": 88, "payments": 60, "reliability": 68, "schema": 53, "security": 39, "transparency": 73 }, "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": 4, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "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": 83, "checked": { "categories": { "ergonomics": "2026-10-08", "maintenance": "2026-10-08", "payments": "2026-10-08", "reliability": "2026-10-08", "schema": "2026-10-08", "security": "2026-10-08", "transparency": "2026-10-08" }, "last": "2026-10-08", "lastMoved": "2026-10-27", "oldest": "2026-10-08", "stale": false, "staleAfterDays": 90 } }, "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", "copilot-studio-mcp", "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": 83 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/foundry-local.json", "live": { "slug": "foundry-local", "versions": [ { "registry": "github", "name": "microsoft/Foundry-Local", "version": "v2.2.1", "released": "2026-10-23", "seenAt": "2026-10-30T14:13:37.186168616Z" }, { "registry": "npm", "name": "foundry-local-sdk", "version": "2.2.1", "seenAt": "2026-10-30T14:13:35.849631836Z" }, { "registry": "pypi", "name": "foundry-local-sdk", "version": "2.2.1", "released": "2026-10-21", "seenAt": "2026-10-30T14:13:36.995808248Z" } ], "githubStars": 2603, "npmWeekly": 39919, "pypiWeekly": 46927, "securityTxt": { "url": "https://microsoft.com/.well-known/security.txt", "state": "expired", "expires": "2026-09-23T16:00:00.000Z", "checkedAt": "2026-10-30T15:37:48.473009438Z" }, "domain": { "domain": "microsoft.com", "registered": "1991-05-02", "source": "https://rdap.verisign.com/com/v1/domain/microsoft.com", "checkedAt": "2026-10-25T13:59:13.024843334Z" }, "github": { "repo": "microsoft/foundry-local", "checkedAt": "2026-10-26T07:45:31.620788383Z", "stars": 2599, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-26T03:33:25Z", "openIssues": 90, "openPRs": 39, "issuesOpened90d": 101, "issuesClosed90d": 53, "prsMerged90d": 146, "ci": { "branch": "main", "runs": 50, "success": 39, "failure": 11, "other": 0, "latest": "failure", "latestAt": "2026-10-16T17:44:05Z" }, "replies": { "sampled": 25, "unanswered": 19, "medianDays": 4.4 } }, "updatedAt": "2026-10-30T15:37:48.473009438Z" } }, "answer": "Foundry Local scores 60.5 (C) on agent readiness against HyperQwen's 56.9 (C), and leads in 3 of 7 scored categories.", "b": { "slug": "hyperqwen", "name": "HyperQwen", "vendor": "syv.ai (syv-ai on GitHub)", "vendorUrl": "https://syv.ai", "kind": "http-api", "category": "local-ai", "summary": "HyperQwen is syv.ai's open-source serving setup for Qwen3.8-27B on one 24 GB NVIDIA GPU. A patch series against a pinned vLLM, a requantisation pipeline and Docker Compose profiles run vLLM's OpenAI-compatible API on port 18020.", "url": "https://www.anchorterminal.com/tools/hyperqwen", "markdownUrl": "https://www.anchorterminal.com/tools/hyperqwen.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hyperqwen.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hyperqwen.json", "repo": "https://github.com/syv-ai/HyperQwen", "license": "Apache-2.0", "transports": [ "http" ], "packages": [ { "registry": "oci", "name": "ghcr.io/syv-ai/hyperqwen" } ], "auth": "none", "authNotes": "No credential by default. `VLLM_API_KEY` in `.env` (or an `api_key.txt` file) turns on vLLM's Bearer check. With no key, the launcher binds 127.0.0.1 outside a container, and Docker Compose publishes the port on 127.0.0.1 unless `BIND` is changed. With a key set, the launcher binds every interface. The key is vLLM's own, one static key with no scopes, which vLLM checks only under `/v1`, `/v2`, `/inference` and `/cohere` (per the vLLM listing's check of 9 October 2026, https://github.com/vllm-project/vllm/blob/main/docs/usage/security.md).", "pricing": "free", "pricingNotes": "Free under Apache-2.0 with no account, key or card. Nothing is sold. The README links a Ko-fi page for donations towards GPU time. The owner pays for a 24 GB NVIDIA GPU, about 40 GB of disk and electricity.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the README, the docs or the launch scripts (checked 2026-10-30). Nothing is sold.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 2400, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-30" }, "docsUrl": "https://github.com/syv-ai/HyperQwen#readme", "capabilities": [ "inference.local", "inference.open-weights" ], "tags": [ "open-source", "local", "self-hosted", "free", "no-card", "apache-2.0", "openai-compatible", "docker", "tool-calling", "reasoning", "pre-1.0" ], "graded": true, "anchor": { "graded": true, "score": 56.9, "grade": "C", "agentReady": false, "rank": 738, "ranked": true, "rankOf": 1239, "categoryRank": 11, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 65, "maintenance": 68, "payments": 60, "reliability": 59, "schema": 56, "security": 41, "transparency": 55 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-30" }, "negative": 0, "verdict": "HyperQwen packages a patched vLLM 0.32.0 and requantised Qwen3.8-27B weights into one container with tool calling preset and a loopback bind when no key is set. It runs one model family, its speed figures come from one RTX 3090, and it has no versioned releases, changelog or security policy.", "bestFor": "An operator with one 24 GB NVIDIA card who wants Qwen3.8-27B behind an OpenAI-compatible endpoint for a coding or tool-calling agent, with long context.", "strengths": [ "Prebuilt image on ghcr.io with an immutable tag per commit, built by CI that applies all 60 patches and runs the build-time tests", "Tool calling on by default with the `qwen3_coder` parser and argument schemas enforced (`TOOL_STRICT=parameter`)", "With no API key the server listens on 127.0.0.1 only, and a CI check tests that default", "Five documented setups from 64k to 240k context, with the measured cost of each knob", "Apache-2.0 throughout, with vendored kernels and patches carrying their upstream references" ], "weaknesses": [ "Serves Qwen3.8-27B and checkpoints derived from it only. Other models are on the roadmap", "No tags, releases or changelog. Changes reach users through `latest` on every push to main", "No SECURITY.md or disclosure route, and the base weights come from a third-party repository with no pinned revision", "vLLM's key covers only `/v1`-style prefixes, so control routes such as `/pause` answer without it", "First start pulls a 9.5 GB image and about 20 GB of weights and can take over 30 minutes" ], "agentNotes": [ "Call http://127.0.0.1:18020/v1 with model `qwen3.8-27b` and the `VLLM_API_KEY` value, or any string if no key was set", "Poll `/health` before the first request. A first start downloads and prepares the model and compiles kernels, which can take over 30 minutes", "Declare the context window your setup uses (65,536 by default, 131,072 for `CTX=long`, 245,760 for `CTX=huge`) so the client doesn't truncate", "Ask the owner to set `VLLM_API_KEY` before setting `BIND=0.0.0.0`, and to front the port with a proxy that allowlists routes", "Treat the README's tokens-per-second figures as the project's measurements on one RTX 3090 at 250 W" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 56.9 } ], "editorialScores": { "ergonomics": 65, "maintenance": 68, "payments": 60, "reliability": 59, "schema": 56, "security": 41, "transparency": 60 }, "provenanceScore": 49, "checked": { "categories": { "ergonomics": "2026-10-30", "maintenance": "2026-10-30", "payments": "2026-10-30", "reliability": "2026-10-30", "schema": "2026-10-30", "security": "2026-10-30", "transparency": "2026-10-30" }, "last": "2026-10-30", "oldest": "2026-10-30", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "git clone https://github.com/syv-ai/HyperQwen \u0026\u0026 cd HyperQwen\ncp .env.example .env\n\ndocker compose --profile single up -d # one or a few people chatting\ndocker compose --profile batch up -d # API backend, many concurrent requests" }, "letme": { "capability": "https://letme.dev/inference.local", "tool": "https://letme.dev/hyperqwen" }, "area": "models", "provenance": { "legalEntity": "syv.ai (Copenhagen, CVR DK44671247)", "domain": "syv.ai", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "https://syv.ai/privatlivspolitik", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-30", "notes": [ "The Hugging Face organisation syvai, full name syv.ai, links https://syv.ai and github.com/syv-ai, and hosts the drafter files HyperQwen downloads. syv.ai's own pages don't mention HyperQwen.", "syv.ai's contact page gives the address in Copenhagen and CVR DK44671247. The Danish CVR register answered with a bot check and wasn't read.", "No terms, SECURITY.md or changelog for HyperQwen. The Apache-2.0 licence stands in for terms. The privacy policy listed is syv.ai's website policy and doesn't cover the software, which runs on the owner's machine.", "syv.ai answers 404 at /.well-known/security.txt and /security.txt." ], "score": 49 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/hyperqwen.json" }, "facts": [ { "a": "SDK + MCP", "b": "HTTP API", "name": "Kind" }, { "a": "Microsoft", "b": "syv.ai (syv-ai on GitHub)", "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 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", "b": "Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-09-29", "b": "none", "name": "Last release" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no date given", "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": "2.6k stars, 105k npm/wk, 47k PyPI/wk", "b": "2.4k stars", "name": "Popularity" }, { "a": "3/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Foundry Local scores 60.5 (C) on agent readiness against HyperQwen's 56.9 (C), and leads in 3 of 7 scored categories.", "question": "Which is better for AI agents, Foundry Local or HyperQwen?" }, { "answer": "No hosted endpoint is listed for Foundry Local. No hosted endpoint is listed for HyperQwen.", "question": "Can an agent call Foundry Local and HyperQwen without installing anything?" }, { "answer": "Yes. 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). HyperQwen is open source (Apache-2.0).", "question": "Are Foundry Local and HyperQwen open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 68 against 59", "Maintenance \u0026 community, 88 against 68", "Transparency \u0026 trust, 73 against 55" ], "also": null, "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`" }, { "aheadOn": null, "also": null, "goodFor": "An operator with one 24 GB NVIDIA card who wants Qwen3.8-27B behind an OpenAI-compatible endpoint for a coding or tool-calling agent, with long context.", "slug": "hyperqwen", "watchFor": "Serves Qwen3.8-27B and checkpoints derived from it only. Other models are on the roadmap" } ], "job": { "capability": "inference.local", "name": "Local inference" }, "others": [ { "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-hyperqwen.json", "title": "AnythingLLM vs HyperQwen", "url": "https://www.anchorterminal.com/compare/anythingllm-vs-hyperqwen" }, { "json": "https://www.anchorterminal.com/compare/berth-vs-foundry-local.json", "title": "Berth vs Foundry Local", "url": "https://www.anchorterminal.com/compare/berth-vs-foundry-local" }, { "json": "https://www.anchorterminal.com/compare/berth-vs-hyperqwen.json", "title": "Berth vs HyperQwen", "url": "https://www.anchorterminal.com/compare/berth-vs-hyperqwen" }, { "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-hyperqwen.json", "title": "BitRun vs HyperQwen", "url": "https://www.anchorterminal.com/compare/bitrun-vs-hyperqwen" }, { "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/docker-model-runner-vs-hyperqwen.json", "title": "Docker Model Runner vs HyperQwen", "url": "https://www.anchorterminal.com/compare/docker-model-runner-vs-hyperqwen" }, { "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/ghost-core-vs-hyperqwen.json", "title": "Core vs HyperQwen", "url": "https://www.anchorterminal.com/compare/ghost-core-vs-hyperqwen" }, { "json": "https://www.anchorterminal.com/compare/gpt4all-vs-hyperqwen.json", "title": "GPT4All vs HyperQwen", "url": "https://www.anchorterminal.com/compare/gpt4all-vs-hyperqwen" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-jan.json", "title": "HyperQwen vs Jan", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-jan" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-khoj.json", "title": "HyperQwen vs Khoj", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-khoj" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-koboldcpp.json", "title": "HyperQwen vs KoboldCpp", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-koboldcpp" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-lemonade.json", "title": "HyperQwen vs Lemonade", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-lemonade" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-llama-cpp.json", "title": "HyperQwen vs llama.cpp", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-llama-cpp" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-lm-studio.json", "title": "HyperQwen vs LM Studio", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-lm-studio" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-localai.json", "title": "HyperQwen vs LocalAI", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-localai" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-mlx-lm.json", "title": "HyperQwen vs MLX LM", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-mlx-lm" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-ollama.json", "title": "HyperQwen vs Ollama", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-ollama" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-open-webui.json", "title": "HyperQwen vs Open WebUI", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-open-webui" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-screenpipe.json", "title": "HyperQwen vs screenpipe", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-screenpipe" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-text-generation-webui.json", "title": "HyperQwen vs TextGen", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-text-generation-webui" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-vllm.json", "title": "HyperQwen vs vLLM", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-vllm" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/hyperqwen-vs-underdog.json", "title": "HyperQwen vs Underdog", "url": "https://www.anchorterminal.com/compare/hyperqwen-vs-underdog" } ], "scores": [ { "by": 9, "edge": "foundry-local", "foundry-local": 68, "hyperqwen": 59, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 3, "edge": "hyperqwen", "foundry-local": 53, "hyperqwen": 56, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 4, "edge": "hyperqwen", "foundry-local": 61, "hyperqwen": 65, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "by": 2, "edge": "hyperqwen", "foundry-local": 39, "hyperqwen": 41, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "by": 0, "edge": "", "foundry-local": 60, "hyperqwen": 60, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 20, "edge": "foundry-local", "foundry-local": 88, "hyperqwen": 68, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 18, "edge": "foundry-local", "foundry-local": 73, "hyperqwen": 55, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Foundry Local scores 60.5 (C) on agent readiness against HyperQwen's 56.9 (C), and leads in 3 of 7 scored categories. Both do local inference.", "tutorials": [], "verdicts": { "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.", "hyperqwen": "HyperQwen packages a patched vLLM 0.32.0 and requantised Qwen3.8-27B weights into one container with tool calling preset and a loopback bind when no key is set. It runs one model family, its speed figures come from one RTX 3090, and it has no versioned releases, changelog or security policy." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/foundry-local-vs-hyperqwen", "json": "https://www.anchorterminal.com/compare/foundry-local-vs-hyperqwen.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/foundry-local-vs-hyperqwen.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/foundry-local-vs-hyperqwen.min.md" }, "markdown": "Foundry Local scores 60.5 (C) on agent readiness against HyperQwen's 56.9 (C), and leads in 3 of 7 scored categories. Both do local inference.\n\n- Foundry Local: grade C, 60.5/100, rank #592 of 1239. Markdown https://www.anchorterminal.com/tools/foundry-local.md · JSON https://www.anchorterminal.com/api/v1/tools/foundry-local.json\n- HyperQwen: grade C, 56.9/100, rank #738 of 1239. Markdown https://www.anchorterminal.com/tools/hyperqwen.md · JSON https://www.anchorterminal.com/api/v1/tools/hyperqwen.json\n- Best local AI models and assistants: https://www.anchorterminal.com/best/local-ai/index.md\n- All 253 local ai comparisons: https://www.anchorterminal.com/compare/local-ai/index.md\n\n## Which one, for what\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 59\n- Maintenance \u0026 community, 88 against 68\n- Transparency \u0026 trust, 73 against 55\n\nWatch for: The local server takes no credential, and its routes include model load and unload and `POST /shutdown`\n\n### HyperQwen (C)\n\nGood for: An operator with one 24 GB NVIDIA card who wants Qwen3.8-27B behind an OpenAI-compatible endpoint for a coding or tool-calling agent, with long context.\n\nWatch for: Serves Qwen3.8-27B and checkpoints derived from it only. Other models are on the roadmap\n\n\n## Score by category\n\n| Category | Weight | Foundry Local | HyperQwen | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 68 | 59 | Foundry Local +9 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 53 | 56 | HyperQwen +3 |\n| Agent ergonomics | 13% (16.2 this run) | 61 | 65 | HyperQwen +4 |\n| Security \u0026 auth | 14% (17.5 this run) | 39 | 41 | HyperQwen +2 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 60 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 88 | 68 | Foundry Local +20 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 73 | 55 | Foundry Local +18 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **60.5 · C** | **56.9 · C** | |\n\n## Facts side by side\n\n| Fact | Foundry Local | HyperQwen |\n| --- | --- | --- |\n| Kind | SDK + MCP | HTTP API |\n| Vendor | Microsoft | syv.ai (syv-ai on GitHub) |\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 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 | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-09-29 | none |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no date given |\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 | 2.6k stars, 105k npm/wk, 47k PyPI/wk | 2.4k stars |\n| Agent reviews | 3/5 (4) | none |\n\n## Verdicts\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**HyperQwen.** HyperQwen packages a patched vLLM 0.32.0 and requantised Qwen3.8-27B weights into one container with tool calling preset and a loopback bind when no key is set. It runs one model family, its speed figures come from one RTX 3090, and it has no versioned releases, changelog or security policy.\n\n## Before you call either\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### HyperQwen\n\n1. Call http://127.0.0.1:18020/v1 with model `qwen3.8-27b` and the `VLLM_API_KEY` value, or any string if no key was set\n2. Poll `/health` before the first request. A first start downloads and prepares the model and compiles kernels, which can take over 30 minutes\n3. Declare the context window your setup uses (65,536 by default, 131,072 for `CTX=long`, 245,760 for `CTX=huge`) so the client doesn't truncate\n4. Ask the owner to set `VLLM_API_KEY` before setting `BIND=0.0.0.0`, and to front the port with a proxy that allowlists routes\n5. Treat the README's tokens-per-second figures as the project's measurements on one RTX 3090 at 250 W\n\n## Questions\n\n### Which is better for AI agents, Foundry Local or HyperQwen?\n\nFoundry Local scores 60.5 (C) on agent readiness against HyperQwen's 56.9 (C), and leads in 3 of 7 scored categories.\n\n### Can an agent call Foundry Local and HyperQwen without installing anything?\n\nNo hosted endpoint is listed for Foundry Local. No hosted endpoint is listed for HyperQwen.\n\n### Are Foundry Local and HyperQwen open source?\n\nYes. 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). HyperQwen is open source (Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/foundry-local-vs-hyperqwen.json, and with the fewest tokens: https://www.anchorterminal.com/compare/foundry-local-vs-hyperqwen.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"foundry-local\", \"b\": \"hyperqwen\"}`. From a terminal: `anchor compare foundry-local hyperqwen`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/foundry-local.json and https://www.anchorterminal.com/api/v1/tools/hyperqwen.json\n\n## Other comparisons with Foundry Local or HyperQwen\n\n- [AnythingLLM vs Foundry Local](https://www.anchorterminal.com/compare/anythingllm-vs-foundry-local.md)\n- [AnythingLLM vs HyperQwen](https://www.anchorterminal.com/compare/anythingllm-vs-hyperqwen.md)\n- [Berth vs Foundry Local](https://www.anchorterminal.com/compare/berth-vs-foundry-local.md)\n- [Berth vs HyperQwen](https://www.anchorterminal.com/compare/berth-vs-hyperqwen.md)\n- [BitRun vs Foundry Local](https://www.anchorterminal.com/compare/bitrun-vs-foundry-local.md)\n- [BitRun vs HyperQwen](https://www.anchorterminal.com/compare/bitrun-vs-hyperqwen.md)\n- [Docker Model Runner vs Foundry Local](https://www.anchorterminal.com/compare/docker-model-runner-vs-foundry-local.md)\n- [Docker Model Runner vs HyperQwen](https://www.anchorterminal.com/compare/docker-model-runner-vs-hyperqwen.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- [Core vs HyperQwen](https://www.anchorterminal.com/compare/ghost-core-vs-hyperqwen.md)\n- [GPT4All vs HyperQwen](https://www.anchorterminal.com/compare/gpt4all-vs-hyperqwen.md)\n- [HyperQwen vs Jan](https://www.anchorterminal.com/compare/hyperqwen-vs-jan.md)\n- [HyperQwen vs Khoj](https://www.anchorterminal.com/compare/hyperqwen-vs-khoj.md)\n- [HyperQwen vs KoboldCpp](https://www.anchorterminal.com/compare/hyperqwen-vs-koboldcpp.md)\n- [HyperQwen vs Lemonade](https://www.anchorterminal.com/compare/hyperqwen-vs-lemonade.md)\n- [HyperQwen vs llama.cpp](https://www.anchorterminal.com/compare/hyperqwen-vs-llama-cpp.md)\n- [HyperQwen vs LM Studio](https://www.anchorterminal.com/compare/hyperqwen-vs-lm-studio.md)\n- [HyperQwen vs LocalAI](https://www.anchorterminal.com/compare/hyperqwen-vs-localai.md)\n- [HyperQwen vs MLX LM](https://www.anchorterminal.com/compare/hyperqwen-vs-mlx-lm.md)\n- [HyperQwen vs Ollama](https://www.anchorterminal.com/compare/hyperqwen-vs-ollama.md)\n- [HyperQwen vs Open WebUI](https://www.anchorterminal.com/compare/hyperqwen-vs-open-webui.md)\n- [HyperQwen vs screenpipe](https://www.anchorterminal.com/compare/hyperqwen-vs-screenpipe.md)\n- [HyperQwen vs TextGen](https://www.anchorterminal.com/compare/hyperqwen-vs-text-generation-webui.md)\n- [HyperQwen vs vLLM](https://www.anchorterminal.com/compare/hyperqwen-vs-vllm.md)\n- [Foundry Local vs Underdog](https://www.anchorterminal.com/compare/foundry-local-vs-underdog.md)\n- [HyperQwen vs Underdog](https://www.anchorterminal.com/compare/hyperqwen-vs-underdog.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-31", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "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": "Foundry Local vs HyperQwen", "url": "" } ], "description": "Foundry Local scores 60.5 (C) to HyperQwen's 56.9 (C) for local inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Foundry Local C 60.5", "HyperQwen C 56.9", "scores" ], "h1": "Foundry Local vs HyperQwen", "image": "https://www.anchorterminal.com/assets/og/compare-foundry-local-vs-hyperqwen.png", "path": "/compare/foundry-local-vs-hyperqwen", "published": "2026-10-01", "section": "tools", "title": "Foundry Local vs HyperQwen for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-30", "url": "https://www.anchorterminal.com/compare/foundry-local-vs-hyperqwen" }, "tokens": { "markdown": 2800, "slim": 580 }, "version": 1 }