{ "data": { "a": { "slug": "microsoft-decision-1", "name": "Microsoft-Decision-1", "vendor": "Microsoft", "vendorUrl": "https://www.microsoft.com", "kind": "model", "category": "decision-models", "summary": "Microsoft-Decision-1 is a Microsoft model, post-trained from Qwen3.5-9B, that scores fixed answer options with a calibrated probability for each. It is in public preview on Microsoft Foundry and OpenRouter, at $0.042 per million input tokens.", "url": "https://www.anchorterminal.com/tools/microsoft-decision-1", "markdownUrl": "https://www.anchorterminal.com/tools/microsoft-decision-1.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/microsoft-decision-1.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/microsoft-decision-1.json", "license": "Not stated. The announcement and OpenRouter's model page name no licence, and no weights repository was found.", "transports": [ "http" ], "packages": [], "auth": "mixed", "authNotes": "Foundry route: a Microsoft Entra bearer token for https://cognitiveservices.azure.com/.default, against a deployment in a Foundry resource, so an Azure subscription and deployment come first. OpenRouter route: an OpenRouter API key, read from OPENROUTER_API_KEY in OpenRouter's SDK example. Signup and key creation on OpenRouter were not checked.", "pricing": "usage", "pricingNotes": "$0.042 per million input tokens, with output free, on Foundry US and EU Datazone deployments and on OpenRouter (checked 10 October 2026). Microsoft says usage charges apply. No free tier or trial without a card was found.", "priceSummary": "Pay per use", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in Microsoft's announcement, the Tech Community post, the Foundry sample or OpenRouter's model page, checked 10 October 2026.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-10" }, "docsUrl": "https://commandline.microsoft.com/microsoft-decision-1-model-foundry/", "capabilities": [ "inference.decision" ], "tags": [ "hosted", "model", "usage-priced", "status-page", "beta" ], "lastRelease": "2026-10-09", "graded": true, "anchor": { "graded": true, "score": 38.8, "grade": "E", "agentReady": false, "rank": 1008, "ranked": true, "rankOf": 1094, "categoryRank": 17, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 50, "maintenance": 40, "payments": 20, "reliability": 30, "schema": 43, "security": 52, "transparency": 29 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-10" }, "negative": 0, "verdict": "Microsoft publishes $0.042 per million input tokens, with output free, and the model is callable through Microsoft Foundry and OpenRouter. It is in public preview. No licence, model-specific retention statement, rate limit or deprecation policy was found, and the Foundry route needs an Azure deployment and an Entra token. Latency and accuracy figures are Microsoft's claims.", "bestFor": "Routing, classification, prioritisation and rubric checks over text, where a fixed set of options and a low price per token matter more than generated text.", "strengths": [ "Price published without a login: $0.042 per million input tokens, with output free, on the US and EU Datazone deployments and on OpenRouter", "Callable today through two routes, Microsoft Foundry and OpenRouter, both linked from Microsoft's 9 October 2026 announcement", "Each answer is a probability for one fixed option, which Microsoft describes as calibrated, so an application can send uncertain results to review", "OpenRouter lists a 32,768-token context window, text input and decisions as output", "OpenRouter's documentation lists a Decisions method in its Python, TypeScript and Go SDKs, marked alpha" ], "weaknesses": [ "Public preview only. Microsoft's post gives no general availability date and states no licence for the hosted model", "No model-specific rate limit, retention statement or deprecation policy was found. Microsoft's Foundry data page covers Models sold by Azure in general", "The Foundry route needs an Azure subscription, a deployment of the model and a Microsoft Entra token, all set up by a person", "Microsoft describes its Xbox Research result as competitive with GPT-5 or GPT-6 Sol on quality, not better, and the two Microsoft posts name different baselines for it", "Azure status history lists a Foundry Models incident on 29 September 2026 in Sweden Central, with intermittent failures and HTTP 5xx for about six hours" ], "agentNotes": [ "Use OpenRouter's Decisions method, not an OpenAI chat-completions SDK. OpenRouter says chat completions SDKs will not work with this model", "On Foundry, send the request to the deployment's /providers/microsoft/v1/systemone path with a Microsoft Entra token for https://cognitiveservices.azure.com/.default, not an API key", "Take the deployment name from the Foundry quickstart before the first call. Microsoft says to confirm the route and authentication header, and the pages reviewed do not give the name", "Keep each request within OpenRouter's 32,768-token context and send only fixed options, since the model is not intended for open-ended generation", "Measure latency and calibration on your own labelled cases before relying on Microsoft's latency and 'nine times out of 10' statements" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "E", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 38.8 } ], "editorialScores": { "ergonomics": 50, "maintenance": 40, "payments": 20, "reliability": 30, "schema": 43, "security": 52, "transparency": 22 }, "provenanceScore": 36 }, "connect": { "http": "curl -X POST \"$AZURE_ENDPOINT/providers/microsoft/v1/systemone\" \\\n -H \"Authorization: Bearer $ENTRA_TOKEN\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"\u003cdeployment-name\u003e\",\"state\":\"The customer requests a refund for a duplicate charge.\",\"questions\":{\"team\":{\"type\":\"choice\",\"instructions\":\"Which team should handle this request?\",\"criteria\":{\"billing\":\"Charges, invoices, refunds or subscription payments\",\"technical\":\"Software errors or integration failures\"}}}}'" }, "letme": { "capability": "https://letme.dev/inference.decision", "tool": "https://letme.dev/microsoft-decision-1" }, "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", "foundry-local", "microsoft-advertising-api", "microsoft-excel-graph", "outlook-mail-graph", "microsoft-graph-people" ], "area": "models", "unitPrices": [ { "item": "Decision input", "unit": "1m-tokens", "usd": 0.042, "note": "US and EU Datazone on Foundry and OpenRouter. Microsoft's post says usage charges apply." }, { "item": "Decision output", "unit": "1m-tokens", "usd": 0, "note": "Free per Microsoft's post and OpenRouter. The Foundry price table shows N/A." } ], "provenance": { "legalEntity": "", "domain": "microsoft.com", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/data-privacy", "statusPage": "https://azure.status.microsoft/en-us/status/history/", "changelog": "", "securityTxt": "expired", "checked": "2026-10-10", "notes": [ "The Foundry endpoint is account-specific, given as AZURE_ENDPOINT in Microsoft's sample, so endpointOnVendorDomain is not set.", "The legal entity name and Microsoft's product terms were not read, so terms is empty.", "Microsoft's security.txt at www.microsoft.com/.well-known/security.txt gives an Expires date of 2026-09-23, which has passed.", "The Azure status history page shows a Foundry Models component and dated incidents. It is shared by all Foundry models, not specific to this one.", "The Foundry model catalogue page at ai.azure.com is rendered by script and returned no model content when read." ], "score": 36 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/microsoft-decision-1.json", "live": { "slug": "microsoft-decision-1", "vendorStatus": { "page": "https://azure.status.microsoft/en-us/status/history", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-15T10:06:45.52846908Z" }, "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" }, "pages": [ { "url": "https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/data-privacy", "kind": "privacy", "status": 304, "checkedAt": "2026-10-14T21:02:23.45545964Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "35ed8a2e1125" } ], "updatedAt": "2026-10-15T10:06:45.52846908Z" } }, "answer": "ScaleDown scores 48.6 (D) on agent readiness against Microsoft-Decision-1's 38.8 (E), and leads in 5 of 7 scored categories. Microsoft-Decision-1 leads on reliability.", "b": { "slug": "scaledown", "name": "ScaleDown", "vendor": "Carbon ScaleDown, Inc.", "vendorUrl": "https://scaledown.ai", "kind": "model", "category": "decision-models", "summary": "ScaleDown's API serves three single-task Constrained Decoding Models (Classify, Extract and Summarize) and a Compress model, called with an API key at api.scaledown.xyz. Classify answers Jev-shaped decision requests with probabilities.", "url": "https://www.anchorterminal.com/tools/scaledown", "markdownUrl": "https://www.anchorterminal.com/tools/scaledown.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/scaledown.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/scaledown.json", "repo": "https://github.com/scaledown-team/langchain-scaledown", "license": "Proprietary hosted models under ScaleDown's Terms of Service. The langchain-scaledown integration is MIT", "transports": [ "http" ], "remoteUrl": "https://api.scaledown.xyz", "packages": [ { "registry": "pypi", "name": "langchain-scaledown" } ], "auth": "api-key", "authNotes": "An API key in the `x-api-key` header. Extract and Summarize on `/v1/chat/completions` also accept `Authorization: Bearer`, so an unmodified OpenAI SDK works by changing the base URL. Keys are made in the dashboard after sign-up at scaledown.ai/auth. We found no documentation of key scopes, expiry or rotation. An unauthenticated request returns 401 with `{\"detail\":\"x-api-key header is required\"}`.", "pricing": "usage", "pricingNotes": "$0.05 per million input tokens for every model, with output tokens free (https://scaledown.ai, FAQ). Classify's optional one-sentence reasoning bills its extra input tokens at 2x. New accounts get 50 million free tokens with no card, per the homepage. The docs introduction instead says to contact sales for a key. OpenRouter lists Extract and Summarize at $0.04 per million input tokens. Enterprise and self-hosted plans are priced by sales.", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs, the OpenAPI document, the site or the LiteLLM and OpenRouter entries (checked 2026-10-14). Running out of credit returns 402 Payment Required as an ordinary error.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 0, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-14" }, "docsUrl": "https://docs.scaledown.ai/introduction", "llmsTxt": "https://docs.scaledown.ai/llms.txt", "openapi": "https://docs.scaledown.ai/api-reference/openapi.json", "capabilities": [ "inference.decision", "docs.extract" ], "tags": [ "hosted", "model", "closed-source", "openapi", "llms-txt", "openai-compatible", "usage-priced", "free-tier", "no-card", "python" ], "lastRelease": "2026-10-14", "graded": true, "anchor": { "graded": true, "score": 48.6, "grade": "D", "agentReady": false, "rank": 880, "ranked": true, "rankOf": 1094, "categoryRank": 15, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 76, "maintenance": 56, "payments": 40, "reliability": 20, "schema": 69, "security": 48, "transparency": 54 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-14" }, "negative": -2, "negativeNotes": [ "Conflicting compliance claims on ScaleDown's own pages, read 14 October 2026. The DPA (20 July 2026) says ScaleDown maintains a SOC 2 Type II attestation and ISO 27001 certification, the homepage shows SOC 2 Type 1, HIPAA and ISO 27001 badges, and llms.txt says GDPR, HIPAA and SOC 2 compliance is in progress. At least one is wrong. No report or trust centre found to settle it (-2) (https://scaledown.ai/dpa, https://scaledown.ai/llms.txt)" ], "verdict": "Classify answers Jev-shaped `choice`, `noul` and `score` questions with probabilities, and Extract returns values with confidences and character offsets, at $0.05 per million input tokens with output free. There is no status page, no published rate limit and no public changelog, and the site's compliance claims contradict each other.", "bestFor": "Cheap, high-volume labelling, routing and yes or no checks where a probability is more useful than prose, and for pulling described fields with offsets from text, images or PDFs.", "strengths": [ "`POST /v1/scaledown` takes Jev's request shape, so a Jev integration can move by changing the base URL, per the docs", "$0.05 per million input tokens for every model, output free, and 50 million free tokens with no card, per the homepage", "Extract returns each value with a confidence, character offsets and surrounding context, and routes `enum` fields to the Classify model", "llms.txt with Markdown twins, an OpenAPI 3.1 document and OpenAI-compatible chat completions for Extract and Summarize", "The terms, DPA and FAQ agree that customer data isn't used for training, and the DPA lists four US subprocessors" ], "weaknesses": [ "No status page, no published rate limits and no SLA outside enterprise contracts", "No public changelog. The docs dropped the native /extract and /summarization endpoints from the reference on 13 October 2026", "Compliance claims disagree between the DPA (SOC 2 Type II, ISO 27001), the homepage badges (SOC 2 Type 1) and llms.txt (in progress)", "No security.txt, disclosure policy or bug bounty, and no guidance on hostile text in classified input", "The OpenAPI document covers /classify, /v1/scaledown and Compress only, without the documented limits" ], "agentNotes": [ "Send several questions about one item in one `/v1/scaledown` call. Each becomes its own Classify call and the usage is summed", "Pin `classify-1`, `extract-1` or `summarize-1` once you've tuned thresholds on your own labelled cases", "Set `context_chars` to 0 and use `top_n` on Extract unless you need the 500 characters of context each side", "Set `reasoning: false` on /classify when you only need the label. The reasoning call bills its input at 2x", "Back off and retry on 429, 502 and 504. No limits are published and calls have no side effects" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 48.6 } ], "editorialScores": { "ergonomics": 76, "maintenance": 56, "payments": 40, "reliability": 20, "schema": 69, "security": 48, "transparency": 56 }, "provenanceScore": 52 }, "connect": { "install": "pip install langchain-scaledown # LangChain middleware; any OpenAI SDK also works against /v1/chat/completions", "http": "curl https://api.scaledown.xyz/v1/scaledown \\\n -H \"x-api-key: $SCALEDOWN_API_KEY\" -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"classify-1\",\"state\":\"I was charged twice for my subscription this month.\",\"questions\":{\"category\":{\"type\":\"choice\",\"criteria\":{\"billing\":\"About a charge, invoice, refund, or payment problem.\",\"technical\":\"About a bug or something not working.\"}}}}'" }, "letme": { "capability": "https://letme.dev/inference.decision", "tool": "https://letme.dev/scaledown" }, "alsoIn": [ "document-extraction" ], "area": "models", "unitPrices": [ { "item": "Classify, Extract, Summarize and Compress input", "unit": "1m-tokens", "usd": 0.05, "note": "Output tokens free. Classify reasoning input billed at 2x. 50M free tokens for new accounts" } ], "provenance": { "legalEntity": "Carbon ScaleDown, Inc.", "domain": "scaledown.ai", "domainRegistered": "2025-03-28", "endpointOnVendorDomain": true, "terms": "https://scaledown.ai/terms", "privacy": "https://scaledown.ai/privacy", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-14", "notes": [ "The terms (last updated 20 July 2026), privacy notice (3 June 2026) and DPA (20 July 2026) name Carbon ScaleDown, Inc., 22952 Stokes Rd, Ramona, CA 92065, and Delaware law. One sentence of the terms names ScaleDown, Inc.", "scaledown.ai is a single-page app. /terms, /privacy and /dpa answer HTTP 404 with the app shell, and their text is in the JavaScript bundle (https://scaledown.ai/assets/index-CIrIjse9.js), where we read it.", "The API host is api.scaledown.xyz. scaledown.xyz redirects to scaledown.ai, so we treat the endpoint as on the vendor's domain.", "scaledown.ai/.well-known/security.txt and docs.scaledown.ai/.well-known/security.txt return 404. status.scaledown.ai and status.scaledown.xyz don't resolve.", "No public changelog. The docs source at github.com/scaledown-team/docs has dated commits that record API changes.", "RDAP gives scaledown.ai a registration date of 28 March 2025." ], "score": 52 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/scaledown.json", "live": { "slug": "scaledown", "probe": { "target": "https://api.scaledown.xyz", "method": "get", "lastAt": "2026-10-15T14:03:43.707330463Z", "lastOk": true, "lastStatus": 403, "lastMs": 252, "lastNote": "asks for credentials", "authRequired": true, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 263, "p95ms24h": 308, "samples24h": 197, "samples30d": 197, "days": [ { "date": "2026-10-14", "probes": 47, "ok": 47 }, { "date": "2026-10-15", "probes": 150, "ok": 150 } ] }, "versions": [ { "registry": "pypi", "name": "langchain-scaledown", "version": "0.2.0", "released": "2026-10-12", "seenAt": "2026-10-15T00:19:27.075016002Z" } ], "githubStars": 0, "pypiWeekly": 229, "pages": [ { "url": "https://scaledown.ai/privacy", "kind": "privacy", "status": 404, "checkedAt": "2026-10-14T21:06:40.247126332Z", "changedAt": "0001-01-01T00:00:00Z" }, { "url": "https://scaledown.ai/terms", "kind": "terms", "status": 404, "checkedAt": "2026-10-14T21:06:42.626164273Z", "changedAt": "0001-01-01T00:00:00Z" } ], "updatedAt": "2026-10-15T14:03:43.707330463Z" } }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Microsoft", "b": "Carbon ScaleDown, Inc.", "name": "Vendor" }, { "a": "no (local only)", "b": "https://api.scaledown.xyz", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "OAuth or key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "free", "b": "not published", "name": "Price for decision models" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Not stated. The announcement and OpenRouter's model page name no licence, and no weights repository was found.", "b": "Proprietary hosted models under ScaleDown's Terms of Service. The langchain-scaledown integration is MIT", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-09", "b": "2026-10-14", "name": "Last release" }, { "a": "no document linked", "b": "couldn't be read", "name": "Terms last updated" }, { "a": "no date given", "b": "couldn't be read", "name": "Privacy policy last updated" }, { "a": "", "b": "couldn't be read", "name": "Customer content may train models" }, { "a": "", "b": "couldn't be read", "name": "Terms restrict automated access" }, { "a": "", "b": "couldn't be read", "name": "Terms restrict benchmarking" }, { "a": "", "b": "couldn't be read", "name": "Terms or service can change without notice" }, { "a": "", "b": "couldn't be read", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "0 stars", "name": "Popularity" } ], "faq": [ { "answer": "ScaleDown scores 48.6 (D) on agent readiness against Microsoft-Decision-1's 38.8 (E), and leads in 5 of 7 scored categories. Microsoft-Decision-1 leads on reliability.", "question": "Which is better for AI agents, Microsoft-Decision-1 or ScaleDown?" }, { "answer": "Microsoft-Decision-1 takes an API key or an OAuth sign-in. ScaleDown needs an API key.", "question": "Do Microsoft-Decision-1 and ScaleDown need an API key?" }, { "answer": "No hosted endpoint is listed for Microsoft-Decision-1. ScaleDown has a hosted endpoint at https://api.scaledown.xyz.", "question": "Can an agent call Microsoft-Decision-1 and ScaleDown without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 30 against 20" ], "also": null, "goodFor": "Routing, classification, prioritisation and rubric checks over text, where a fixed set of options and a low price per token matter more than generated text.", "slug": "microsoft-decision-1", "watchFor": "Public preview only. Microsoft's post gives no general availability date and states no licence for the hosted model" }, { "aheadOn": [ "Schema \u0026 documentation, 69 against 43", "Agent ergonomics, 76 against 50", "Payments \u0026 pricing, 40 against 20", "Maintenance \u0026 community, 56 against 40", "Transparency \u0026 trust, 54 against 29" ], "also": [ "A hosted endpoint, with nothing to install", "Free to start without a card" ], "goodFor": "Cheap, high-volume labelling, routing and yes or no checks where a probability is more useful than prose, and for pulling described fields with offsets from text, images or PDFs.", "slug": "scaledown", "watchFor": "No status page, no published rate limits and no SLA outside enterprise contracts" } ], "job": { "capability": "inference.decision", "name": "Decision models" }, "others": [ { "json": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-microsoft-decision-1.json", "title": "Celeris-1 Decision vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-microsoft-decision-1" }, { "json": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-scaledown.json", "title": "Celeris-1 Decision vs ScaleDown", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-scaledown" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-microsoft-decision-1.json", "title": "Clef vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-microsoft-decision-1" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-scaledown.json", "title": "Clef vs ScaleDown", "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-scaledown" }, { "json": "https://www.anchorterminal.com/compare/convai-laya-vs-microsoft-decision-1.json", "title": "Laya vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-microsoft-decision-1" }, { "json": "https://www.anchorterminal.com/compare/convai-laya-vs-scaledown.json", "title": "Laya vs ScaleDown", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-scaledown" }, { "json": "https://www.anchorterminal.com/compare/decider-vs-microsoft-decision-1.json", "title": "Decider vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/decider-vs-microsoft-decision-1" }, { "json": "https://www.anchorterminal.com/compare/decider-vs-scaledown.json", "title": "Decider vs ScaleDown", "url": "https://www.anchorterminal.com/compare/decider-vs-scaledown" }, { "json": "https://www.anchorterminal.com/compare/decision-3-vs-microsoft-decision-1.json", "title": "Decision 3.0 vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/decision-3-vs-microsoft-decision-1" }, { "json": "https://www.anchorterminal.com/compare/decision-3-vs-scaledown.json", "title": "Decision 3.0 vs ScaleDown", "url": "https://www.anchorterminal.com/compare/decision-3-vs-scaledown" }, { "json": "https://www.anchorterminal.com/compare/gliclass-vs-microsoft-decision-1.json", "title": "GLiClass vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/gliclass-vs-microsoft-decision-1" }, { "json": "https://www.anchorterminal.com/compare/gliclass-vs-scaledown.json", "title": "GLiClass vs ScaleDown", "url": "https://www.anchorterminal.com/compare/gliclass-vs-scaledown" }, { "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-microsoft-decision-1.json", "title": "Kev vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-microsoft-decision-1" }, { "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-scaledown.json", "title": "Kev vs ScaleDown", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-scaledown" }, { "json": "https://www.anchorterminal.com/compare/liquid-d1-vs-microsoft-decision-1.json", "title": "Liquid d1 vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-microsoft-decision-1" }, { "json": "https://www.anchorterminal.com/compare/liquid-d1-vs-scaledown.json", "title": "Liquid d1 vs ScaleDown", "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-scaledown" }, { "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-nace-drex.json", "title": "Microsoft-Decision-1 vs Drex 1.5", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-nace-drex" }, { "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-openai-decisions-api.json", "title": "Microsoft-Decision-1 vs OpenAI Decisions API", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-openai-decisions-api" }, { "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-pplx-decider.json", "title": "Microsoft-Decision-1 vs pplx-decider", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-pplx-decider" }, { "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-sprag-spev.json", "title": "Microsoft-Decision-1 vs SPEV", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-sprag-spev" }, { "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-strands-decider.json", "title": "Microsoft-Decision-1 vs Strands Decider 2B", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-strands-decider" }, { "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-typesafe-jev.json", "title": "Microsoft-Decision-1 vs Jev", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-typesafe-jev" }, { "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-vela.json", "title": "Microsoft-Decision-1 vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-vela" }, { "json": "https://www.anchorterminal.com/compare/nace-drex-vs-scaledown.json", "title": "Drex 1.5 vs ScaleDown", "url": "https://www.anchorterminal.com/compare/nace-drex-vs-scaledown" }, { "json": "https://www.anchorterminal.com/compare/openai-decisions-api-vs-scaledown.json", "title": "OpenAI Decisions API vs ScaleDown", "url": "https://www.anchorterminal.com/compare/openai-decisions-api-vs-scaledown" }, { "json": "https://www.anchorterminal.com/compare/pplx-decider-vs-scaledown.json", "title": "pplx-decider vs ScaleDown", "url": "https://www.anchorterminal.com/compare/pplx-decider-vs-scaledown" }, { "json": "https://www.anchorterminal.com/compare/scaledown-vs-sprag-spev.json", "title": "ScaleDown vs SPEV", "url": "https://www.anchorterminal.com/compare/scaledown-vs-sprag-spev" }, { "json": "https://www.anchorterminal.com/compare/scaledown-vs-strands-decider.json", "title": "ScaleDown vs Strands Decider 2B", "url": "https://www.anchorterminal.com/compare/scaledown-vs-strands-decider" }, { "json": "https://www.anchorterminal.com/compare/scaledown-vs-typesafe-jev.json", "title": "ScaleDown vs Jev", "url": "https://www.anchorterminal.com/compare/scaledown-vs-typesafe-jev" }, { "json": "https://www.anchorterminal.com/compare/scaledown-vs-vela.json", "title": "ScaleDown vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/scaledown-vs-vela" } ], "scores": [ { "by": 10, "edge": "microsoft-decision-1", "key": "reliability", "microsoft-decision-1": 30, "name": "Reliability", "scaledown": 20, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 26, "edge": "scaledown", "key": "schema", "microsoft-decision-1": 43, "name": "Schema \u0026 documentation", "scaledown": 69, "weight": 13 }, { "by": 26, "edge": "scaledown", "key": "ergonomics", "microsoft-decision-1": 50, "name": "Agent ergonomics", "scaledown": 76, "weight": 13 }, { "by": 4, "edge": "microsoft-decision-1", "key": "security", "microsoft-decision-1": 52, "name": "Security \u0026 auth", "scaledown": 48, "weight": 14 }, { "by": 20, "edge": "scaledown", "key": "payments", "microsoft-decision-1": 20, "name": "Payments \u0026 pricing", "scaledown": 40, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 16, "edge": "scaledown", "key": "maintenance", "microsoft-decision-1": 40, "name": "Maintenance \u0026 community", "scaledown": 56, "weight": 7 }, { "by": 25, "edge": "scaledown", "key": "transparency", "microsoft-decision-1": 29, "name": "Transparency \u0026 trust", "scaledown": 54, "weight": 7 } ], "summary": "ScaleDown scores 48.6 (D) on agent readiness against Microsoft-Decision-1's 38.8 (E), and leads in 5 of 7 scored categories. Microsoft-Decision-1 leads on reliability. Both do decision models.", "verdicts": { "microsoft-decision-1": "Microsoft publishes $0.042 per million input tokens, with output free, and the model is callable through Microsoft Foundry and OpenRouter. It is in public preview. No licence, model-specific retention statement, rate limit or deprecation policy was found, and the Foundry route needs an Azure deployment and an Entra token. Latency and accuracy figures are Microsoft's claims.", "scaledown": "Classify answers Jev-shaped `choice`, `noul` and `score` questions with probabilities, and Extract returns values with confidences and character offsets, at $0.05 per million input tokens with output free. There is no status page, no published rate limit and no public changelog, and the site's compliance claims contradict each other." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-scaledown", "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-scaledown.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-scaledown.md", "slim": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-scaledown.min.md" }, "markdown": "ScaleDown scores 48.6 (D) on agent readiness against Microsoft-Decision-1's 38.8 (E), and leads in 5 of 7 scored categories. Microsoft-Decision-1 leads on reliability. Both do decision models.\n\n- Microsoft-Decision-1: grade E, 38.8/100, rank #1008 of 1094. Markdown https://www.anchorterminal.com/tools/microsoft-decision-1.md · JSON https://www.anchorterminal.com/api/v1/tools/microsoft-decision-1.json\n- ScaleDown: grade D, 48.6/100, rank #880 of 1094. Markdown https://www.anchorterminal.com/tools/scaledown.md · JSON https://www.anchorterminal.com/api/v1/tools/scaledown.json\n- Best decision models for AI agents: https://www.anchorterminal.com/best/decision-models/index.md\n- All 136 decisions comparisons: https://www.anchorterminal.com/compare/decision-models/index.md\n- Best document parsing, OCR and extraction APIs for AI agents: https://www.anchorterminal.com/best/document-extraction/index.md\n- All 125 documents comparisons: https://www.anchorterminal.com/compare/document-extraction/index.md\n\n## Which one, for what\n\n### Microsoft-Decision-1 (E)\n\nGood for: Routing, classification, prioritisation and rubric checks over text, where a fixed set of options and a low price per token matter more than generated text.\n\nAhead on:\n- Reliability, 30 against 20\n\nWatch for: Public preview only. Microsoft's post gives no general availability date and states no licence for the hosted model\n\n### ScaleDown (D)\n\nGood for: Cheap, high-volume labelling, routing and yes or no checks where a probability is more useful than prose, and for pulling described fields with offsets from text, images or PDFs.\n\nAhead on:\n- Schema \u0026 documentation, 69 against 43\n- Agent ergonomics, 76 against 50\n- Payments \u0026 pricing, 40 against 20\n- Maintenance \u0026 community, 56 against 40\n- Transparency \u0026 trust, 54 against 29\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n- Free to start without a card\n\nWatch for: No status page, no published rate limits and no SLA outside enterprise contracts\n\n\n## Score by category\n\n| Category | Weight | Microsoft-Decision-1 | ScaleDown | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 30 | 20 | Microsoft-Decision-1 +10 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 43 | 69 | ScaleDown +26 |\n| Agent ergonomics | 13% (16.2 this run) | 50 | 76 | ScaleDown +26 |\n| Security \u0026 auth | 14% (17.5 this run) | 52 | 48 | Microsoft-Decision-1 +4 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 40 | ScaleDown +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 40 | 56 | ScaleDown +16 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 29 | 54 | ScaleDown +25 |\n| Negative events | ≤15 | 0 | -2 | |\n| **Total** | | **38.8 · E** | **48.6 · D** | |\n\n## Facts side by side\n\n| Fact | Microsoft-Decision-1 | ScaleDown |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Microsoft | Carbon ScaleDown, Inc. |\n| Hosted endpoint | no (local only) | `https://api.scaledown.xyz` |\n| Transports | HTTP | HTTP |\n| Auth | OAuth or key | API key |\n| Pricing | Pay per use | Pay per use |\n| Price for decision models | free | not published |\n| x402 | no | no |\n| Licence | Not stated. The announcement and OpenRouter's model page name no licence, and no weights repository was found. | Proprietary hosted models under ScaleDown's Terms of Service. The langchain-scaledown integration is MIT |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-09 | 2026-10-14 |\n| Terms last updated | no document linked | couldn't be read |\n| Privacy policy last updated | no date given | couldn't be read |\n| Customer content may train models | | couldn't be read |\n| Terms restrict automated access | | couldn't be read |\n| Terms restrict benchmarking | | couldn't be read |\n| Terms or service can change without notice | | couldn't be read |\n| Arbitration or class-action waiver | | couldn't be read |\n| Popularity | none | 0 stars |\n\n## Verdicts\n\n**Microsoft-Decision-1.** Microsoft publishes $0.042 per million input tokens, with output free, and the model is callable through Microsoft Foundry and OpenRouter. It is in public preview. No licence, model-specific retention statement, rate limit or deprecation policy was found, and the Foundry route needs an Azure deployment and an Entra token. Latency and accuracy figures are Microsoft's claims.\n\n**ScaleDown.** Classify answers Jev-shaped `choice`, `noul` and `score` questions with probabilities, and Extract returns values with confidences and character offsets, at $0.05 per million input tokens with output free. There is no status page, no published rate limit and no public changelog, and the site's compliance claims contradict each other.\n\n## Before you call either\n\n### Microsoft-Decision-1\n\n1. Use OpenRouter's Decisions method, not an OpenAI chat-completions SDK. OpenRouter says chat completions SDKs will not work with this model\n2. On Foundry, send the request to the deployment's /providers/microsoft/v1/systemone path with a Microsoft Entra token for https://cognitiveservices.azure.com/.default, not an API key\n3. Take the deployment name from the Foundry quickstart before the first call. Microsoft says to confirm the route and authentication header, and the pages reviewed do not give the name\n4. Keep each request within OpenRouter's 32,768-token context and send only fixed options, since the model is not intended for open-ended generation\n5. Measure latency and calibration on your own labelled cases before relying on Microsoft's latency and 'nine times out of 10' statements\n\n### ScaleDown\n\n1. Send several questions about one item in one `/v1/scaledown` call. Each becomes its own Classify call and the usage is summed\n2. Pin `classify-1`, `extract-1` or `summarize-1` once you've tuned thresholds on your own labelled cases\n3. Set `context_chars` to 0 and use `top_n` on Extract unless you need the 500 characters of context each side\n4. Set `reasoning: false` on /classify when you only need the label. The reasoning call bills its input at 2x\n5. Back off and retry on 429, 502 and 504. No limits are published and calls have no side effects\n\n## Questions\n\n### Which is better for AI agents, Microsoft-Decision-1 or ScaleDown?\n\nScaleDown scores 48.6 (D) on agent readiness against Microsoft-Decision-1's 38.8 (E), and leads in 5 of 7 scored categories. Microsoft-Decision-1 leads on reliability.\n\n### Do Microsoft-Decision-1 and ScaleDown need an API key?\n\nMicrosoft-Decision-1 takes an API key or an OAuth sign-in. ScaleDown needs an API key.\n\n### Can an agent call Microsoft-Decision-1 and ScaleDown without installing anything?\n\nNo hosted endpoint is listed for Microsoft-Decision-1. ScaleDown has a hosted endpoint at https://api.scaledown.xyz.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/microsoft-decision-1-vs-scaledown.json, and with the fewest tokens: https://www.anchorterminal.com/compare/microsoft-decision-1-vs-scaledown.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"microsoft-decision-1\", \"b\": \"scaledown\"}`. From a terminal: `anchor compare microsoft-decision-1 scaledown`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/microsoft-decision-1.json and https://www.anchorterminal.com/api/v1/tools/scaledown.json\n\n## Other comparisons with Microsoft-Decision-1 or ScaleDown\n\n- [Celeris-1 Decision vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/celeris-1-decision-vs-microsoft-decision-1.md)\n- [Celeris-1 Decision vs ScaleDown](https://www.anchorterminal.com/compare/celeris-1-decision-vs-scaledown.md)\n- [Clef vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/cloudflare-clef-vs-microsoft-decision-1.md)\n- [Clef vs ScaleDown](https://www.anchorterminal.com/compare/cloudflare-clef-vs-scaledown.md)\n- [Laya vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/convai-laya-vs-microsoft-decision-1.md)\n- [Laya vs ScaleDown](https://www.anchorterminal.com/compare/convai-laya-vs-scaledown.md)\n- [Decider vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/decider-vs-microsoft-decision-1.md)\n- [Decider vs ScaleDown](https://www.anchorterminal.com/compare/decider-vs-scaledown.md)\n- [Decision 3.0 vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/decision-3-vs-microsoft-decision-1.md)\n- [Decision 3.0 vs ScaleDown](https://www.anchorterminal.com/compare/decision-3-vs-scaledown.md)\n- [GLiClass vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/gliclass-vs-microsoft-decision-1.md)\n- [GLiClass vs ScaleDown](https://www.anchorterminal.com/compare/gliclass-vs-scaledown.md)\n- [Kev vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-microsoft-decision-1.md)\n- [Kev vs ScaleDown](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-scaledown.md)\n- [Liquid d1 vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/liquid-d1-vs-microsoft-decision-1.md)\n- [Liquid d1 vs ScaleDown](https://www.anchorterminal.com/compare/liquid-d1-vs-scaledown.md)\n- [Microsoft-Decision-1 vs Drex 1.5](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-nace-drex.md)\n- [Microsoft-Decision-1 vs OpenAI Decisions API](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-openai-decisions-api.md)\n- [Microsoft-Decision-1 vs pplx-decider](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-pplx-decider.md)\n- [Microsoft-Decision-1 vs SPEV](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-sprag-spev.md)\n- [Microsoft-Decision-1 vs Strands Decider 2B](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-strands-decider.md)\n- [Microsoft-Decision-1 vs Jev](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-typesafe-jev.md)\n- [Microsoft-Decision-1 vs Vela 2.0](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-vela.md)\n- [Drex 1.5 vs ScaleDown](https://www.anchorterminal.com/compare/nace-drex-vs-scaledown.md)\n- [OpenAI Decisions API vs ScaleDown](https://www.anchorterminal.com/compare/openai-decisions-api-vs-scaledown.md)\n- [pplx-decider vs ScaleDown](https://www.anchorterminal.com/compare/pplx-decider-vs-scaledown.md)\n- [ScaleDown vs SPEV](https://www.anchorterminal.com/compare/scaledown-vs-sprag-spev.md)\n- [ScaleDown vs Strands Decider 2B](https://www.anchorterminal.com/compare/scaledown-vs-strands-decider.md)\n- [ScaleDown vs Jev](https://www.anchorterminal.com/compare/scaledown-vs-typesafe-jev.md)\n- [ScaleDown vs Vela 2.0](https://www.anchorterminal.com/compare/scaledown-vs-vela.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": "Microsoft-Decision-1 vs ScaleDown", "url": "" } ], "description": "ScaleDown scores 48.6 (D) to Microsoft-Decision-1's 38.8 (E) for decision models. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Microsoft-Decision-1 E 38.8", "ScaleDown D 48.6", "scores" ], "h1": "Microsoft-Decision-1 vs ScaleDown", "image": "https://www.anchorterminal.com/assets/og/compare-microsoft-decision-1-vs-scaledown.png", "path": "/compare/microsoft-decision-1-vs-scaledown", "published": "2026-10-01", "section": "tools", "title": "Microsoft-Decision-1 vs ScaleDown for AI agents (2026)", "toc": null, "updated": "2026-10-15", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-scaledown" }, "tokens": { "markdown": 2850, "slim": 730 }, "version": 1 }