{ "data": { "a": { "slug": "decider", "name": "Decider", "vendor": "Mark Marosi (Mapika)", "vendorUrl": "https://github.com/Mapika", "kind": "model", "category": "decision-models", "summary": "Decider is a family of open-weight decision models by Mark Marosi (Mapika), from 0.8B to 35B parameters under Apache-2.0. It answers typed yes or no, choice and score questions with probabilities, and runs locally from the `decider-ai` Python package.", "url": "https://www.anchorterminal.com/tools/decider", "markdownUrl": "https://www.anchorterminal.com/tools/decider.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/decider.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/decider.json", "repo": "https://github.com/Mapika/decider", "license": "Apache-2.0 (code and weights)", "transports": [ "http" ], "packages": [ { "registry": "pypi", "name": "decider-ai" } ], "auth": "none", "authNotes": "No account. `decider.serve` has no authentication option. `scripts/serve.sh` binds to 127.0.0.1 since 1.7.1, and `DECIDER_HOST=0.0.0.0` opens it to the network. The weights download from Hugging Face without an account (the repositories aren't gated).", "pricing": "free", "pricingNotes": "Free and open source, with nothing to buy. You pay for your own hardware. The README puts the 2B at about 4 GB of GPU memory, the 4B at 8.4 GB and the 35B at 65 GB in bf16, with GGUF files of 1.3 GB and 2.7 GB for CPU (https://github.com/Mapika/decider). No hosted API was found.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402. Decider is software you run, and its server has no payment route (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 1100, "npmWeekly": null, "pypiWeekly": 2680, "asOf": "2026-10-08" }, "docsUrl": "https://github.com/Mapika/decider#readme", "capabilities": [ "inference.decision" ], "tags": [ "model", "open-source", "open-weights", "self-hosted", "local", "free", "python" ], "lastRelease": "2026-10-07", "graded": true, "anchor": { "graded": true, "score": 69.5, "grade": "B", "agentReady": false, "rank": 190, "ranked": true, "rankOf": 1094, "categoryRank": 2, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 80, "maintenance": 87, "payments": 60, "reliability": 90, "schema": 78, "security": 38, "transparency": 46 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "An Apache-2.0 decision model family with a dated changelog, passing CI, 21 package releases since 22 September 2026 and model cards that list measured regressions. One person maintains it, the local server has no authentication option, states over 32,768 tokens are cut without an error, and no security policy is published.", "bestFor": "Local classification, routing, triage and checks where a team wants open weights in several sizes and a Jev-shaped route.", "strengths": [ "Apache-2.0 code and weights, with the training code, data builders and per-version measurements in the repository", "Sizes from 0.8B to 35B parameters, with GGUF files for CPU and builds for CUDA, Apple silicon and vLLM", "`POST /v1/systemone` follows TypeSafe's wire format, and the README says TypeSafe's SDKs work with `TYPESAFE_BASE_URL` set to the local server", "Dated changelog entries for all 21 `decider-ai` releases from 1.0.0 (22 September 2026) to 1.9.0 (7 October 2026)", "Size limits return 413, overload 503 and invalid questions 422, each with a message documented in `docs/SERVING.md`" ], "weaknesses": [ "The local server has no authentication option. It binds to 127.0.0.1 since 1.7.1", "States over 32,768 tokens are truncated (`DECIDER_MAX_STATE_TOKENS`) without an error", "No SECURITY.md, disclosure policy or security contact was found in the repository", "One maintainer wrote 95 of 98 commits, and the project is three weeks old", "The README says calibration on hard items is weak, the models are English only, and one pass can't do multi-step arithmetic", "No hosted API, and the HTTP server doesn't serve the GGUF files" ], "agentNotes": [ "Pin weights by Hub tag (`v10`, `v2`) when results must repeat. The `main` branch of each model repository changes with new versions", "Read `x_p_max` for the top probability. Since 1.3.0 `confidence` on choice and score answers follows TypeSafe's rescaled definition, not the top probability", "Keep the server on 127.0.0.1 or put an authenticating proxy in front. It has no key option", "Count state tokens before sending. Over 32,768 the state is cut silently, and `/decide` caps context at 1,536 tokens", "Split multi-step arithmetic or multi-hop judgements into several questions, and don't write long rules into a question. The README says both fail" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 69.5 } ], "editorialScores": { "ergonomics": 80, "maintenance": 87, "payments": 60, "reliability": 90, "schema": 78, "security": 38, "transparency": 64 }, "provenanceScore": 27 }, "connect": { "install": "pip install decider-ai" }, "letme": { "capability": "https://letme.dev/inference.decision", "tool": "https://letme.dev/decider" }, "area": "models", "provenance": { "legalEntity": "", "domain": "github.com/Mapika", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/Mapika/decider/blob/main/docs/CHANGELOG.md", "securityTxt": "none", "checked": "2026-10-08", "notes": [ "An individual's open-source project under Apache-2.0. The pyproject and the README citation name Mark Marosi as author, and no company is named.", "No vendor domain. The code is at github.com/Mapika/decider and the weights at huggingface.co/Mapika, so the domain line names the GitHub account and scores no domain age.", "Software you run, so there's no hosted endpoint, service terms or privacy policy. The author publishes none, and the Apache-2.0 licence stands in for terms.", "The changelog is `docs/CHANGELOG.md`, with a dated entry for each package release and model update. Release tags v1.0.2 to v1.9.0 match the PyPI versions." ], "score": 27 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/decider.json", "live": { "slug": "decider", "versions": [ { "registry": "pypi", "name": "decider-ai", "version": "1.9.0", "released": "2026-10-07", "seenAt": "2026-10-14T23:47:55.453433014Z" } ], "githubStars": 1142, "pypiWeekly": 2359, "domain": { "domain": "github.com/mapika", "checkedAt": "2026-10-11T13:26:29.542802311Z" }, "pages": [ { "url": "https://raw.githubusercontent.com/Mapika/decider/main/docs/CHANGELOG.md", "kind": "changelog", "status": 304, "checkedAt": "2026-10-14T21:06:11.595507836Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "533fad35e7c7" } ], "updatedAt": "2026-10-14T23:47:55.644532853Z" } }, "answer": "Decider scores 69.5 (B) on agent readiness against ScaleDown's 48.6 (D), and leads in 5 of 7 scored categories. ScaleDown leads on security \u0026 auth and transparency \u0026 trust.", "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": "Mark Marosi (Mapika)", "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": "None", "b": "API key", "name": "Auth" }, { "a": "Free", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0 (code and weights)", "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": "2026-10-07", "b": "2026-10-14", "name": "Last release" }, { "a": "no document linked", "b": "couldn't be read", "name": "Terms last updated" }, { "a": "no document linked", "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": "1.1k stars, 2.7k PyPI/wk", "b": "0 stars", "name": "Popularity" } ], "faq": [ { "answer": "Decider scores 69.5 (B) on agent readiness against ScaleDown's 48.6 (D), and leads in 5 of 7 scored categories. ScaleDown leads on security \u0026 auth and transparency \u0026 trust.", "question": "Which is better for AI agents, Decider or ScaleDown?" }, { "answer": "Decider needs no key. ScaleDown needs an API key.", "question": "Do Decider and ScaleDown need an API key?" }, { "answer": "No hosted endpoint is listed for Decider. ScaleDown has a hosted endpoint at https://api.scaledown.xyz.", "question": "Can an agent call Decider and ScaleDown without installing anything?" }, { "answer": "Decider is open source (Apache-2.0 (code and weights)). No open-source release is listed for ScaleDown.", "question": "Are Decider and ScaleDown open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 90 against 20", "Schema \u0026 documentation, 78 against 69", "Payments \u0026 pricing, 60 against 40", "Maintenance \u0026 community, 87 against 56" ], "also": [ "No key needed to call it", "Open source" ], "goodFor": "Local classification, routing, triage and checks where a team wants open weights in several sizes and a Jev-shaped route.", "slug": "decider", "watchFor": "The local server has no authentication option. It binds to 127.0.0.1 since 1.7.1" }, { "aheadOn": [ "Security \u0026 auth, 48 against 38", "Transparency \u0026 trust, 54 against 46" ], "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-decider.json", "title": "Celeris-1 Decision vs Decider", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-decider" }, { "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-decider.json", "title": "Clef vs Decider", "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-decider" }, { "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-decider.json", "title": "Laya vs Decider", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-decider" }, { "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-decision-3.json", "title": "Decider vs Decision 3.0", "url": "https://www.anchorterminal.com/compare/decider-vs-decision-3" }, { "json": "https://www.anchorterminal.com/compare/decider-vs-gliclass.json", "title": "Decider vs GLiClass", "url": "https://www.anchorterminal.com/compare/decider-vs-gliclass" }, { "json": "https://www.anchorterminal.com/compare/decider-vs-jaredpalmer-kev.json", "title": "Decider vs Kev", "url": "https://www.anchorterminal.com/compare/decider-vs-jaredpalmer-kev" }, { "json": "https://www.anchorterminal.com/compare/decider-vs-liquid-d1.json", "title": "Decider vs Liquid d1", "url": "https://www.anchorterminal.com/compare/decider-vs-liquid-d1" }, { "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-nace-drex.json", "title": "Decider vs Drex 1.5", "url": "https://www.anchorterminal.com/compare/decider-vs-nace-drex" }, { "json": "https://www.anchorterminal.com/compare/decider-vs-openai-decisions-api.json", "title": "Decider vs OpenAI Decisions API", "url": "https://www.anchorterminal.com/compare/decider-vs-openai-decisions-api" }, { "json": "https://www.anchorterminal.com/compare/decider-vs-pplx-decider.json", "title": "Decider vs pplx-decider", "url": "https://www.anchorterminal.com/compare/decider-vs-pplx-decider" }, { "json": "https://www.anchorterminal.com/compare/decider-vs-sprag-spev.json", "title": "Decider vs SPEV", "url": "https://www.anchorterminal.com/compare/decider-vs-sprag-spev" }, { "json": "https://www.anchorterminal.com/compare/decider-vs-strands-decider.json", "title": "Decider vs Strands Decider 2B", "url": "https://www.anchorterminal.com/compare/decider-vs-strands-decider" }, { "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/decider-vs-vela.json", "title": "Decider vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/decider-vs-vela" }, { "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-scaledown.json", "title": "GLiClass vs ScaleDown", "url": "https://www.anchorterminal.com/compare/gliclass-vs-scaledown" }, { "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-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-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/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": 70, "decider": 90, "edge": "decider", "key": "reliability", "name": "Reliability", "scaledown": 20, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 9, "decider": 78, "edge": "decider", "key": "schema", "name": "Schema \u0026 documentation", "scaledown": 69, "weight": 13 }, { "by": 4, "decider": 80, "edge": "decider", "key": "ergonomics", "name": "Agent ergonomics", "scaledown": 76, "weight": 13 }, { "by": 10, "decider": 38, "edge": "scaledown", "key": "security", "name": "Security \u0026 auth", "scaledown": 48, "weight": 14 }, { "by": 20, "decider": 60, "edge": "decider", "key": "payments", "name": "Payments \u0026 pricing", "scaledown": 40, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 31, "decider": 87, "edge": "decider", "key": "maintenance", "name": "Maintenance \u0026 community", "scaledown": 56, "weight": 7 }, { "by": 8, "decider": 46, "edge": "scaledown", "key": "transparency", "name": "Transparency \u0026 trust", "scaledown": 54, "weight": 7 } ], "summary": "Decider scores 69.5 (B) on agent readiness against ScaleDown's 48.6 (D), and leads in 5 of 7 scored categories. ScaleDown leads on security \u0026 auth and transparency \u0026 trust. Both do decision models.", "verdicts": { "decider": "An Apache-2.0 decision model family with a dated changelog, passing CI, 21 package releases since 22 September 2026 and model cards that list measured regressions. One person maintains it, the local server has no authentication option, states over 32,768 tokens are cut without an error, and no security policy is published.", "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/decider-vs-scaledown", "json": "https://www.anchorterminal.com/compare/decider-vs-scaledown.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/decider-vs-scaledown.md", "slim": "https://www.anchorterminal.com/compare/decider-vs-scaledown.min.md" }, "markdown": "Decider scores 69.5 (B) on agent readiness against ScaleDown's 48.6 (D), and leads in 5 of 7 scored categories. ScaleDown leads on security \u0026 auth and transparency \u0026 trust. Both do decision models.\n\n- Decider: grade B, 69.5/100, rank #190 of 1094. Markdown https://www.anchorterminal.com/tools/decider.md · JSON https://www.anchorterminal.com/api/v1/tools/decider.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### Decider (B)\n\nGood for: Local classification, routing, triage and checks where a team wants open weights in several sizes and a Jev-shaped route.\n\nAhead on:\n- Reliability, 90 against 20\n- Schema \u0026 documentation, 78 against 69\n- Payments \u0026 pricing, 60 against 40\n- Maintenance \u0026 community, 87 against 56\n\nAlso in its favour:\n- No key needed to call it\n- Open source\n\nWatch for: The local server has no authentication option. It binds to 127.0.0.1 since 1.7.1\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- Security \u0026 auth, 48 against 38\n- Transparency \u0026 trust, 54 against 46\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 | Decider | ScaleDown | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 90 | 20 | Decider +70 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 78 | 69 | Decider +9 |\n| Agent ergonomics | 13% (16.2 this run) | 80 | 76 | Decider +4 |\n| Security \u0026 auth | 14% (17.5 this run) | 38 | 48 | ScaleDown +10 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 40 | Decider +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 87 | 56 | Decider +31 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 46 | 54 | ScaleDown +8 |\n| Negative events | ≤15 | 0 | -2 | |\n| **Total** | | **69.5 · B** | **48.6 · D** | |\n\n## Facts side by side\n\n| Fact | Decider | ScaleDown |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Mark Marosi (Mapika) | Carbon ScaleDown, Inc. |\n| Hosted endpoint | no (local only) | `https://api.scaledown.xyz` |\n| Transports | HTTP | HTTP |\n| Auth | None | API key |\n| Pricing | Free | Pay per use |\n| x402 | no | no |\n| Licence | Apache-2.0 (code and weights) | 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 | 2026-10-07 | 2026-10-14 |\n| Terms last updated | no document linked | couldn't be read |\n| Privacy policy last updated | no document linked | 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 | 1.1k stars, 2.7k PyPI/wk | 0 stars |\n\n## Verdicts\n\n**Decider.** An Apache-2.0 decision model family with a dated changelog, passing CI, 21 package releases since 22 September 2026 and model cards that list measured regressions. One person maintains it, the local server has no authentication option, states over 32,768 tokens are cut without an error, and no security policy is published.\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### Decider\n\n1. Pin weights by Hub tag (`v10`, `v2`) when results must repeat. The `main` branch of each model repository changes with new versions\n2. Read `x_p_max` for the top probability. Since 1.3.0 `confidence` on choice and score answers follows TypeSafe's rescaled definition, not the top probability\n3. Keep the server on 127.0.0.1 or put an authenticating proxy in front. It has no key option\n4. Count state tokens before sending. Over 32,768 the state is cut silently, and `/decide` caps context at 1,536 tokens\n5. Split multi-step arithmetic or multi-hop judgements into several questions, and don't write long rules into a question. The README says both fail\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, Decider or ScaleDown?\n\nDecider scores 69.5 (B) on agent readiness against ScaleDown's 48.6 (D), and leads in 5 of 7 scored categories. ScaleDown leads on security \u0026 auth and transparency \u0026 trust.\n\n### Do Decider and ScaleDown need an API key?\n\nDecider needs no key. ScaleDown needs an API key.\n\n### Can an agent call Decider and ScaleDown without installing anything?\n\nNo hosted endpoint is listed for Decider. ScaleDown has a hosted endpoint at https://api.scaledown.xyz.\n\n### Are Decider and ScaleDown open source?\n\nDecider is open source (Apache-2.0 (code and weights)). No open-source release is listed for ScaleDown.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/decider-vs-scaledown.json, and with the fewest tokens: https://www.anchorterminal.com/compare/decider-vs-scaledown.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"decider\", \"b\": \"scaledown\"}`. From a terminal: `anchor compare decider scaledown`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/decider.json and https://www.anchorterminal.com/api/v1/tools/scaledown.json\n\n## Other comparisons with Decider or ScaleDown\n\n- [Celeris-1 Decision vs Decider](https://www.anchorterminal.com/compare/celeris-1-decision-vs-decider.md)\n- [Celeris-1 Decision vs ScaleDown](https://www.anchorterminal.com/compare/celeris-1-decision-vs-scaledown.md)\n- [Clef vs Decider](https://www.anchorterminal.com/compare/cloudflare-clef-vs-decider.md)\n- [Clef vs ScaleDown](https://www.anchorterminal.com/compare/cloudflare-clef-vs-scaledown.md)\n- [Laya vs Decider](https://www.anchorterminal.com/compare/convai-laya-vs-decider.md)\n- [Laya vs ScaleDown](https://www.anchorterminal.com/compare/convai-laya-vs-scaledown.md)\n- [Decider vs Decision 3.0](https://www.anchorterminal.com/compare/decider-vs-decision-3.md)\n- [Decider vs GLiClass](https://www.anchorterminal.com/compare/decider-vs-gliclass.md)\n- [Decider vs Kev](https://www.anchorterminal.com/compare/decider-vs-jaredpalmer-kev.md)\n- [Decider vs Liquid d1](https://www.anchorterminal.com/compare/decider-vs-liquid-d1.md)\n- [Decider vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/decider-vs-microsoft-decision-1.md)\n- [Decider vs Drex 1.5](https://www.anchorterminal.com/compare/decider-vs-nace-drex.md)\n- [Decider vs OpenAI Decisions API](https://www.anchorterminal.com/compare/decider-vs-openai-decisions-api.md)\n- [Decider vs pplx-decider](https://www.anchorterminal.com/compare/decider-vs-pplx-decider.md)\n- [Decider vs SPEV](https://www.anchorterminal.com/compare/decider-vs-sprag-spev.md)\n- [Decider vs Strands Decider 2B](https://www.anchorterminal.com/compare/decider-vs-strands-decider.md)\n- [Decider vs Jev](https://www.anchorterminal.com/compare/decider-vs-typesafe-jev.md)\n- [Decider vs Vela 2.0](https://www.anchorterminal.com/compare/decider-vs-vela.md)\n- [Decision 3.0 vs ScaleDown](https://www.anchorterminal.com/compare/decision-3-vs-scaledown.md)\n- [GLiClass vs ScaleDown](https://www.anchorterminal.com/compare/gliclass-vs-scaledown.md)\n- [Kev vs ScaleDown](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-scaledown.md)\n- [Liquid d1 vs ScaleDown](https://www.anchorterminal.com/compare/liquid-d1-vs-scaledown.md)\n- [Microsoft-Decision-1 vs ScaleDown](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-scaledown.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": "Decider vs ScaleDown", "url": "" } ], "description": "Decider scores 69.5 (B) to ScaleDown's 48.6 (D) for decision models. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Decider B 69.5", "ScaleDown D 48.6", "scores" ], "h1": "Decider vs ScaleDown", "image": "https://www.anchorterminal.com/assets/og/compare-decider-vs-scaledown.png", "path": "/compare/decider-vs-scaledown", "published": "2026-10-01", "section": "tools", "title": "Decider vs ScaleDown for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-15", "url": "https://www.anchorterminal.com/compare/decider-vs-scaledown" }, "tokens": { "markdown": 2650, "slim": 730 }, "version": 1 }