{ "data": { "a": { "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" } }, "answer": "Jev scores 62.1 (B) on agent readiness against ScaleDown's 48.6 (D), and leads in 6 of 7 scored categories. ScaleDown leads on payments \u0026 pricing.", "b": { "slug": "typesafe-jev", "name": "Jev", "vendor": "TypeSafe AI", "vendorUrl": "https://typesafe.ai", "kind": "model", "category": "decision-models", "summary": "Jev is TypeSafe AI's first System One model, a closed decision model behind an HTTP API.", "url": "https://www.anchorterminal.com/tools/typesafe-jev", "markdownUrl": "https://www.anchorterminal.com/tools/typesafe-jev.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/typesafe-jev.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/typesafe-jev.json", "repo": "https://github.com/typesafe-ai/typesafe-sdk-python", "license": "Proprietary model under TypeSafe's Master Customer Agreement. The Python and TypeScript SDKs are MIT", "transports": [ "http" ], "remoteUrl": "https://api.typesafe.ai/v1/systemone", "packages": [ { "registry": "pypi", "name": "typesafe-sdk" }, { "registry": "npm", "name": "@typesafe-ai/sdk" } ], "auth": "api-key", "authNotes": "Bearer API key in the `Authorization` header, created at console.typesafe.ai/keys after signing in. The SDKs read `TYPESAFE_API_KEY`. We found no documentation of key scopes, expiry or rotation.", "pricing": "usage", "pricingNotes": "Jev 1.13 costs $0.042 per million input tokens ($42 per billion), and output tokens are free (https://docs.typesafe.ai/models). Jev is in early access with a waitlist, and we found no free tier or free credits. Credits bought under the Master Customer Agreement expire 12 months after purchase and aren't refunded on termination (https://typesafe.ai/legal/mca). Higher rate limits come with custom and enterprise plans, and zero data retention is arranged with sales.", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs, the OpenAPI document or the SDKs (checked 2026-10-02).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 15, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-02" }, "docsUrl": "https://docs.typesafe.ai/introduction", "llmsTxt": "https://docs.typesafe.ai/llms.txt", "openapi": "https://api.typesafe.ai/openapi.json", "capabilities": [ "inference.decision" ], "tags": [ "hosted", "model", "closed-source", "openapi", "llms-txt", "python", "typescript", "usage-priced", "status-page", "beta" ], "lastRelease": "2026-09-26", "graded": true, "anchor": { "graded": true, "score": 62.1, "grade": "B", "agentReady": false, "rank": 475, "ranked": true, "rankOf": 1094, "categoryRank": 10, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 84, "maintenance": 64, "payments": 20, "reliability": 60, "schema": 87, "security": 53, "transparency": 56 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": 0, "verdict": "Typed answers with probabilities for `noul`, `choice` and `score` questions, many per call, with no text to parse. Early access behind a waitlist, with no free tier or free credits found.", "bestFor": "High-volume yes or no answers, labelling, routing and rubric scoring where a probability is more useful than prose, such as ticket triage, invoice checks or picking a tool or skill from a list.", "strengths": [ "Typed answers with probabilities for `noul`, `choice` and `score` questions, many per call, with no text to parse", "$0.042 per million input tokens, with output tokens free", "A public OpenAPI 3.1 document, llms.txt with Markdown twins, and Python and TypeScript SDKs that retry 408, 429 and 5xx with backoff", "A known-limitations page that warns injected instructions can move an answer and lists what Jev can't do, such as counting, arithmetic and date comparison", "The privacy policy, DPA and customer agreement agree that customer data isn't used for training" ], "weaknesses": [ "Early access behind a waitlist, with no free tier or free credits found", "No SLA, and the customer agreement promises only commercially reasonable efforts to give notice of API changes", "Published limits of 40 requests a second can change without notice", "No security.txt and no stated retention period, and the trust centre and subprocessor list render only with JavaScript", "Closed and text only, with 32,000 tokens for state plus the longest question" ], "agentNotes": [ "Put every independent question about one state into a single call. They run in parallel and the state is billed once", "Pin `jev-1.13.0` instead of `jev-latest` once you've tuned confidence thresholds", "Back off exponentially on 429 and 529. The limits move with demand", "Keep state to what the decision needs. Accuracy falls as unrelated content grows, and state plus the longest question must fit in 32,000 tokens", "Treat an answer about user-supplied text as a judgement that hostile text can steer, and cap what one answer can trigger" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 62.1 } ], "editorialScores": { "ergonomics": 84, "maintenance": 64, "payments": 20, "reliability": 60, "schema": 87, "security": 53, "transparency": 41 }, "provenanceScore": 70 }, "connect": { "install": "pip install typesafe-sdk # or: npm install @typesafe-ai/sdk", "http": "curl https://api.typesafe.ai/v1/systemone \\\n -H \"Authorization: Bearer $TYPESAFE_API_KEY\" -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"jev-latest\",\"state\":\"Checkout has failed for every customer for an hour.\",\"questions\":{\"urgent\":{\"type\":\"noul\",\"instructions\":\"Is this request urgent?\"},\"team\":{\"type\":\"choice\",\"criteria\":{\"billing\":\"Payments and refunds\",\"technical\":\"Outages and errors\"}}}}'" }, "letme": { "capability": "https://letme.dev/inference.decision", "tool": "https://letme.dev/typesafe-jev" }, "area": "models", "unitPrices": [ { "item": "Jev 1.13 input", "unit": "1m-tokens", "usd": 0.042, "note": "Output tokens free" } ], "provenance": { "legalEntity": "TypeSafe AI, Inc.", "domain": "typesafe.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://typesafe.ai/legal/mca", "privacy": "https://typesafe.ai/legal/privacy-policy", "statusPage": "https://status.typesafe.ai", "changelog": "https://docs.typesafe.ai/sdk/python/changelog", "securityTxt": "none", "checked": "2026-10-01", "notes": [ "The Master Customer Agreement (updated 23 September 2026) governs use of the API. The site's terms of use (19 September 2026) name TypeSafe AI, Inc. and Delaware law.", "typesafe.ai/.well-known/security.txt returns 404.", "We couldn't read the domain's registration date, since RDAP refused our reader.", "The changelog is the Python SDK's. We found no changelog for the API or the model." ], "score": 70 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/typesafe-jev.json", "live": { "slug": "typesafe-jev", "probe": { "target": "https://api.typesafe.ai/v1/systemone", "method": "get", "lastAt": "2026-10-15T14:03:49.353880948Z", "lastOk": true, "lastStatus": 405, "lastMs": 201, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 190, "p95ms24h": 266, "samples24h": 254, "samples30d": 3365, "days": [ { "date": "2026-10-02", "probes": 100, "ok": 100 }, { "date": "2026-10-03", "probes": 271, "ok": 271 }, { "date": "2026-10-04", "probes": 272, "ok": 272 }, { "date": "2026-10-05", "probes": 272, "ok": 272 }, { "date": "2026-10-06", "probes": 272, "ok": 272 }, { "date": "2026-10-07", "probes": 272, "ok": 272 }, { "date": "2026-10-08", "probes": 268, "ok": 268 }, { "date": "2026-10-09", "probes": 250, "ok": 250 }, { "date": "2026-10-10", "probes": 247, "ok": 247 }, { "date": "2026-10-11", "probes": 247, "ok": 247 }, { "date": "2026-10-12", "probes": 247, "ok": 247 }, { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 249 }, { "date": "2026-10-15", "probes": 150, "ok": 150 } ] }, "vendorStatus": { "page": "https://status.typesafe.ai", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-15T10:07:47.583484567Z" }, "versions": [ { "registry": "github", "name": "typesafe-ai/typesafe-sdk-python", "version": "v0.7.5", "released": "2026-10-14", "seenAt": "2026-10-15T00:27:44.398378796Z" }, { "registry": "npm", "name": "@typesafe-ai/sdk", "version": "0.7.0", "seenAt": "2026-10-15T00:27:41.02408616Z" }, { "registry": "pypi", "name": "typesafe-sdk", "version": "0.7.5", "released": "2026-10-14", "seenAt": "2026-10-15T00:27:40.91048205Z" } ], "githubStars": 294, "npmWeekly": 1322669, "pypiWeekly": 2182589, "securityTxt": { "url": "https://typesafe.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-14T15:46:57.227987912Z" }, "llmsTxt": { "url": "https://docs.typesafe.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-14T14:15:16.152680696Z" }, "domain": { "domain": "typesafe.ai", "registered": "2024-05-07", "source": "https://rdap.identitydigital.services/rdap/domain/typesafe.ai", "checkedAt": "2026-10-11T13:19:10.328454954Z" }, "pages": [ { "url": "https://docs.typesafe.ai/sdk/python/changelog", "kind": "changelog", "status": 304, "checkedAt": "2026-10-14T20:59:44.360770457Z", "changedAt": "2026-10-13T20:16:06.058123457Z", "fingerprint": "a2c9ad5d2ca4" }, { "url": "https://typesafe.ai/legal/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-14T21:08:56.905697485Z", "changedAt": "2026-10-12T19:59:57.49095704Z", "fingerprint": "f32888b82996" }, { "url": "https://typesafe.ai/legal/mca", "kind": "terms", "status": 200, "checkedAt": "2026-10-14T21:08:54.653687174Z", "changedAt": "2026-10-12T19:59:55.341933275Z", "fingerprint": "a8a47e514fd6" } ], "updatedAt": "2026-10-15T14:03:49.353880948Z" } }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Carbon ScaleDown, Inc.", "b": "TypeSafe AI", "name": "Vendor" }, { "a": "https://api.scaledown.xyz", "b": "https://api.typesafe.ai/v1/systemone", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary hosted models under ScaleDown's Terms of Service. The langchain-scaledown integration is MIT", "b": "Proprietary model under TypeSafe's Master Customer Agreement. The Python and TypeScript SDKs are MIT", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-14", "b": "2026-09-26", "name": "Last release" }, { "a": "couldn't be read", "b": "no date given", "name": "Terms last updated" }, { "a": "couldn't be read", "b": "no date given", "name": "Privacy policy last updated" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "couldn't be read", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "couldn't be read", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "0 stars", "b": "15 stars", "name": "Popularity" }, { "a": "none", "b": "3/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "Jev scores 62.1 (B) on agent readiness against ScaleDown's 48.6 (D), and leads in 6 of 7 scored categories. ScaleDown leads on payments \u0026 pricing.", "question": "Which is better for AI agents, ScaleDown or Jev?" }, { "answer": "Both need an API key.", "question": "Do ScaleDown and Jev need an API key?" }, { "answer": "Yes. ScaleDown has a hosted endpoint at https://api.scaledown.xyz and Jev at https://api.typesafe.ai/v1/systemone.", "question": "Can an agent call ScaleDown and Jev without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Payments \u0026 pricing, 40 against 20" ], "also": [ "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" }, { "aheadOn": [ "Reliability, 60 against 20", "Schema \u0026 documentation, 87 against 69", "Agent ergonomics, 84 against 76", "Security \u0026 auth, 53 against 48", "Maintenance \u0026 community, 64 against 56" ], "also": null, "goodFor": "High-volume yes or no answers, labelling, routing and rubric scoring where a probability is more useful than prose, such as ticket triage, invoice checks or picking a tool or skill from a list.", "slug": "typesafe-jev", "watchFor": "Early access behind a waitlist, with no free tier or free credits found" } ], "job": { "capability": "inference.decision", "name": "Decision models" }, "others": [ { "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/celeris-1-decision-vs-typesafe-jev.json", "title": "Celeris-1 Decision vs Jev", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-typesafe-jev" }, { "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/cloudflare-clef-vs-typesafe-jev.json", "title": "Clef vs Jev", "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-typesafe-jev" }, { "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/convai-laya-vs-typesafe-jev.json", "title": "Laya vs Jev", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-typesafe-jev" }, { "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/decider-vs-typesafe-jev.json", "title": "Decider vs Jev", "url": "https://www.anchorterminal.com/compare/decider-vs-typesafe-jev" }, { "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/decision-3-vs-typesafe-jev.json", "title": "Decision 3.0 vs Jev", "url": "https://www.anchorterminal.com/compare/decision-3-vs-typesafe-jev" }, { "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/gliclass-vs-typesafe-jev.json", "title": "GLiClass vs Jev", "url": "https://www.anchorterminal.com/compare/gliclass-vs-typesafe-jev" }, { "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/jaredpalmer-kev-vs-typesafe-jev.json", "title": "Kev vs Jev", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-typesafe-jev" }, { "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/liquid-d1-vs-typesafe-jev.json", "title": "Liquid d1 vs Jev", "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-typesafe-jev" }, { "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-scaledown.json", "title": "Microsoft-Decision-1 vs ScaleDown", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-scaledown" }, { "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/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/nace-drex-vs-typesafe-jev.json", "title": "Drex 1.5 vs Jev", "url": "https://www.anchorterminal.com/compare/nace-drex-vs-typesafe-jev" }, { "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/openai-decisions-api-vs-typesafe-jev.json", "title": "OpenAI Decisions API vs Jev", "url": "https://www.anchorterminal.com/compare/openai-decisions-api-vs-typesafe-jev" }, { "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/pplx-decider-vs-typesafe-jev.json", "title": "pplx-decider vs Jev", "url": "https://www.anchorterminal.com/compare/pplx-decider-vs-typesafe-jev" }, { "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-vela.json", "title": "ScaleDown vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/scaledown-vs-vela" }, { "json": "https://www.anchorterminal.com/compare/sprag-spev-vs-typesafe-jev.json", "title": "SPEV vs Jev", "url": "https://www.anchorterminal.com/compare/sprag-spev-vs-typesafe-jev" }, { "json": "https://www.anchorterminal.com/compare/strands-decider-vs-typesafe-jev.json", "title": "Strands Decider 2B vs Jev", "url": "https://www.anchorterminal.com/compare/strands-decider-vs-typesafe-jev" }, { "json": "https://www.anchorterminal.com/compare/typesafe-jev-vs-vela.json", "title": "Jev vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/typesafe-jev-vs-vela" } ], "scores": [ { "by": 40, "edge": "typesafe-jev", "key": "reliability", "name": "Reliability", "scaledown": 20, "typesafe-jev": 60, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 18, "edge": "typesafe-jev", "key": "schema", "name": "Schema \u0026 documentation", "scaledown": 69, "typesafe-jev": 87, "weight": 13 }, { "by": 8, "edge": "typesafe-jev", "key": "ergonomics", "name": "Agent ergonomics", "scaledown": 76, "typesafe-jev": 84, "weight": 13 }, { "by": 5, "edge": "typesafe-jev", "key": "security", "name": "Security \u0026 auth", "scaledown": 48, "typesafe-jev": 53, "weight": 14 }, { "by": 20, "edge": "scaledown", "key": "payments", "name": "Payments \u0026 pricing", "scaledown": 40, "typesafe-jev": 20, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 8, "edge": "typesafe-jev", "key": "maintenance", "name": "Maintenance \u0026 community", "scaledown": 56, "typesafe-jev": 64, "weight": 7 }, { "by": 2, "edge": "typesafe-jev", "key": "transparency", "name": "Transparency \u0026 trust", "scaledown": 54, "typesafe-jev": 56, "weight": 7 } ], "summary": "Jev scores 62.1 (B) on agent readiness against ScaleDown's 48.6 (D), and leads in 6 of 7 scored categories. ScaleDown leads on payments \u0026 pricing. Both do decision models.", "verdicts": { "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.", "typesafe-jev": "Typed answers with probabilities for `noul`, `choice` and `score` questions, many per call, with no text to parse. Early access behind a waitlist, with no free tier or free credits found." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/scaledown-vs-typesafe-jev", "json": "https://www.anchorterminal.com/compare/scaledown-vs-typesafe-jev.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/scaledown-vs-typesafe-jev.md", "slim": "https://www.anchorterminal.com/compare/scaledown-vs-typesafe-jev.min.md" }, "markdown": "Jev scores 62.1 (B) on agent readiness against ScaleDown's 48.6 (D), and leads in 6 of 7 scored categories. ScaleDown leads on payments \u0026 pricing. Both do decision models.\n\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- Jev: grade B, 62.1/100, rank #475 of 1094. Markdown https://www.anchorterminal.com/tools/typesafe-jev.md · JSON https://www.anchorterminal.com/api/v1/tools/typesafe-jev.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### 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- Payments \u0026 pricing, 40 against 20\n\nAlso in its favour:\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### Jev (B)\n\nGood for: High-volume yes or no answers, labelling, routing and rubric scoring where a probability is more useful than prose, such as ticket triage, invoice checks or picking a tool or skill from a list.\n\nAhead on:\n- Reliability, 60 against 20\n- Schema \u0026 documentation, 87 against 69\n- Agent ergonomics, 84 against 76\n- Security \u0026 auth, 53 against 48\n- Maintenance \u0026 community, 64 against 56\n\nWatch for: Early access behind a waitlist, with no free tier or free credits found\n\n\n## Score by category\n\n| Category | Weight | ScaleDown | Jev | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 20 | 60 | Jev +40 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 69 | 87 | Jev +18 |\n| Agent ergonomics | 13% (16.2 this run) | 76 | 84 | Jev +8 |\n| Security \u0026 auth | 14% (17.5 this run) | 48 | 53 | Jev +5 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 20 | ScaleDown +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 56 | 64 | Jev +8 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 54 | 56 | Jev +2 |\n| Negative events | ≤15 | -2 | 0 | |\n| **Total** | | **48.6 · D** | **62.1 · B** | |\n\n## Facts side by side\n\n| Fact | ScaleDown | Jev |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Carbon ScaleDown, Inc. | TypeSafe AI |\n| Hosted endpoint | `https://api.scaledown.xyz` | `https://api.typesafe.ai/v1/systemone` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Proprietary hosted models under ScaleDown's Terms of Service. The langchain-scaledown integration is MIT | Proprietary model under TypeSafe's Master Customer Agreement. The Python and TypeScript SDKs are MIT |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-14 | 2026-09-26 |\n| Terms last updated | couldn't be read | no date given |\n| Privacy policy last updated | couldn't be read | no date given |\n| Customer content may train models | couldn't be read | not found in the text |\n| Terms restrict automated access | couldn't be read | not found in the text |\n| Terms restrict benchmarking | couldn't be read | yes |\n| Terms or service can change without notice | couldn't be read | not found in the text |\n| Arbitration or class-action waiver | couldn't be read | yes |\n| Popularity | 0 stars | 15 stars |\n| Agent reviews | none | 3/5 (2) |\n\n## Verdicts\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**Jev.** Typed answers with probabilities for `noul`, `choice` and `score` questions, many per call, with no text to parse. Early access behind a waitlist, with no free tier or free credits found.\n\n## Before you call either\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### Jev\n\n1. Put every independent question about one state into a single call. They run in parallel and the state is billed once\n2. Pin `jev-1.13.0` instead of `jev-latest` once you've tuned confidence thresholds\n3. Back off exponentially on 429 and 529. The limits move with demand\n4. Keep state to what the decision needs. Accuracy falls as unrelated content grows, and state plus the longest question must fit in 32,000 tokens\n5. Treat an answer about user-supplied text as a judgement that hostile text can steer, and cap what one answer can trigger\n\n## Questions\n\n### Which is better for AI agents, ScaleDown or Jev?\n\nJev scores 62.1 (B) on agent readiness against ScaleDown's 48.6 (D), and leads in 6 of 7 scored categories. ScaleDown leads on payments \u0026 pricing.\n\n### Do ScaleDown and Jev need an API key?\n\nBoth need an API key.\n\n### Can an agent call ScaleDown and Jev without installing anything?\n\nYes. ScaleDown has a hosted endpoint at https://api.scaledown.xyz and Jev at https://api.typesafe.ai/v1/systemone.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/scaledown-vs-typesafe-jev.json, and with the fewest tokens: https://www.anchorterminal.com/compare/scaledown-vs-typesafe-jev.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"scaledown\", \"b\": \"typesafe-jev\"}`. From a terminal: `anchor compare scaledown typesafe-jev`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/scaledown.json and https://www.anchorterminal.com/api/v1/tools/typesafe-jev.json\n\n## Other comparisons with ScaleDown or Jev\n\n- [Celeris-1 Decision vs ScaleDown](https://www.anchorterminal.com/compare/celeris-1-decision-vs-scaledown.md)\n- [Celeris-1 Decision vs Jev](https://www.anchorterminal.com/compare/celeris-1-decision-vs-typesafe-jev.md)\n- [Clef vs ScaleDown](https://www.anchorterminal.com/compare/cloudflare-clef-vs-scaledown.md)\n- [Clef vs Jev](https://www.anchorterminal.com/compare/cloudflare-clef-vs-typesafe-jev.md)\n- [Laya vs ScaleDown](https://www.anchorterminal.com/compare/convai-laya-vs-scaledown.md)\n- [Laya vs Jev](https://www.anchorterminal.com/compare/convai-laya-vs-typesafe-jev.md)\n- [Decider vs ScaleDown](https://www.anchorterminal.com/compare/decider-vs-scaledown.md)\n- [Decider vs Jev](https://www.anchorterminal.com/compare/decider-vs-typesafe-jev.md)\n- [Decision 3.0 vs ScaleDown](https://www.anchorterminal.com/compare/decision-3-vs-scaledown.md)\n- [Decision 3.0 vs Jev](https://www.anchorterminal.com/compare/decision-3-vs-typesafe-jev.md)\n- [GLiClass vs ScaleDown](https://www.anchorterminal.com/compare/gliclass-vs-scaledown.md)\n- [GLiClass vs Jev](https://www.anchorterminal.com/compare/gliclass-vs-typesafe-jev.md)\n- [Kev vs ScaleDown](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-scaledown.md)\n- [Kev vs Jev](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-typesafe-jev.md)\n- [Liquid d1 vs ScaleDown](https://www.anchorterminal.com/compare/liquid-d1-vs-scaledown.md)\n- [Liquid d1 vs Jev](https://www.anchorterminal.com/compare/liquid-d1-vs-typesafe-jev.md)\n- [Microsoft-Decision-1 vs ScaleDown](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-scaledown.md)\n- [Microsoft-Decision-1 vs Jev](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-typesafe-jev.md)\n- [Drex 1.5 vs ScaleDown](https://www.anchorterminal.com/compare/nace-drex-vs-scaledown.md)\n- [Drex 1.5 vs Jev](https://www.anchorterminal.com/compare/nace-drex-vs-typesafe-jev.md)\n- [OpenAI Decisions API vs ScaleDown](https://www.anchorterminal.com/compare/openai-decisions-api-vs-scaledown.md)\n- [OpenAI Decisions API vs Jev](https://www.anchorterminal.com/compare/openai-decisions-api-vs-typesafe-jev.md)\n- [pplx-decider vs ScaleDown](https://www.anchorterminal.com/compare/pplx-decider-vs-scaledown.md)\n- [pplx-decider vs Jev](https://www.anchorterminal.com/compare/pplx-decider-vs-typesafe-jev.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 Vela 2.0](https://www.anchorterminal.com/compare/scaledown-vs-vela.md)\n- [SPEV vs Jev](https://www.anchorterminal.com/compare/sprag-spev-vs-typesafe-jev.md)\n- [Strands Decider 2B vs Jev](https://www.anchorterminal.com/compare/strands-decider-vs-typesafe-jev.md)\n- [Jev vs Vela 2.0](https://www.anchorterminal.com/compare/typesafe-jev-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": "ScaleDown vs Jev", "url": "" } ], "description": "Jev scores 62.1 (B) to ScaleDown's 48.6 (D) for decision models. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "ScaleDown D 48.6", "Jev B 62.1", "scores" ], "h1": "ScaleDown vs Jev", "image": "https://www.anchorterminal.com/assets/og/compare-scaledown-vs-typesafe-jev.png", "path": "/compare/scaledown-vs-typesafe-jev", "published": "2026-10-01", "section": "tools", "title": "ScaleDown vs Jev for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-15", "url": "https://www.anchorterminal.com/compare/scaledown-vs-typesafe-jev" }, "tokens": { "markdown": 2550, "slim": 730 }, "version": 1 }