{
  "data": {
    "a": {
      "slug": "liquid-d1",
      "name": "Liquid d1",
      "vendor": "Liquid AI",
      "vendorUrl": "https://www.liquid.ai",
      "kind": "model",
      "category": "decision-models",
      "summary": "d1 is Liquid AI's decision model family. It answers typed yes or no, choice and score questions about text and images with probabilities, through the hosted d1 and d1-ultra models and the open-weight d1-3B and d1-omni-600M.",
      "url": "https://www.anchorterminal.com/tools/liquid-d1",
      "markdownUrl": "https://www.anchorterminal.com/tools/liquid-d1.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/liquid-d1.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/liquid-d1.json",
      "repo": "https://huggingface.co/LiquidAI/d1-3B",
      "license": "The hosted d1 model is proprietary under Liquid AI's terms of service. The d1-3B and d1-omni-600M weights and model code are under the LFM Open Licence v1.0, which is based on Apache-2.0 and conditions commercial use on annual revenue under $10 million. Training code and data aren't published",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://api.liquid.ai/decisions/v1/systemone",
      "packages": [],
      "auth": "api-key",
      "authNotes": "A key created at console.liquid.ai under Dashboard, API Keys, after registering and joining an organisation, sent as a Bearer header. Keys start with `liquid_`. No scopes, expiry or rotation were found in the reviewed documentation. The weights download from Hugging Face without an account.",
      "pricing": "freemium",
      "pricingNotes": "On the hosted API `d1` costs $0.02 and `d1-ultra` $0.042 per million input tokens, with no output tokens billed, per Liquid's pricing page on 17 October 2026 (https://www.liquid.ai/pricing). The 8 October check read $0.04 for d1 in its launch post, which no longer states a price. Each question is billed as its own prompt, and an image counts 1.5 tokens per 32 by 32 pixel patch. Every new organisation gets $2 in free credit. OpenRouter and Vercel AI Gateway charge the same. The open weights are free to run, and commercial use is free below $10 million in annual revenue.",
      "priceSummary": "Freemium",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the d1 docs, the launch posts or the terms of service (checked 2026-10-08).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-08"
      },
      "docsUrl": "https://docs.liquid.ai/lfm/models/decision-models",
      "llmsTxt": "https://docs.liquid.ai/llms.txt",
      "capabilities": [
        "inference.decision"
      ],
      "tags": [
        "hosted",
        "model",
        "open-weights",
        "source-available",
        "self-hosted",
        "llms-txt",
        "free-tier",
        "usage-priced"
      ],
      "lastRelease": "2026-10-15",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 44.5,
        "grade": "E",
        "agentReady": false,
        "rank": 990,
        "ranked": true,
        "rankOf": 1133,
        "categoryRank": 19,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 63,
          "maintenance": 60,
          "payments": 35,
          "reliability": 21,
          "schema": 59,
          "security": 35,
          "transparency": 54
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-17"
        },
        "negative": 0,
        "verdict": "The hosted API costs $0.02 per million input tokens for d1 and $0.042 for d1-ultra, and the d1-3B weights run locally through Transformers or llama.cpp. Liquid's terms allow it to train on API content, and no status page, rate limits or error reference were found.",
        "bestFor": "Classification, routing, yes or no gates and rubric scoring over text and images at a low per-token price, with d1-ultra for harder cases, or on your own hardware with d1-3B where data can't leave.",
        "strengths": [
          "$0.02 per million input tokens for d1 and $0.042 for d1-ultra, with no output tokens billed, and $2 of free credit for a new organisation",
          "d1-3B (3.12B parameters, 32,768-token context) and d1-omni-600M are ungated on Hugging Face, with GGUF builds",
          "llama.cpp's server README documents `/v1/systemone` for d1, so the same request runs locally",
          "The hosted `d1` and `d1-ultra` models accept up to 8 images a request as Base64 data",
          "Docs are served as Markdown with an llms.txt index, and say when to use a language model instead"
        ],
        "weaknesses": [
          "The terms of 30 September 2026 allow Liquid to train on API content, with no opt-out or zero-retention option found",
          "No status page, rate limits, SLA or error reference found for the hosted API",
          "The LFM Open Licence v1.0 ends free commercial use at $10 million in annual revenue, so the weights aren't open source",
          "No OpenAPI file, versioned model IDs or API changelog. d1's price cut and the removal of `d1:free` from the docs carry no dated entry",
          "No SDK of its own. TypeSafe's SDKs are the documented clients and don't send images"
        ],
        "agentNotes": [
          "POST to https://api.liquid.ai/decisions/v1/systemone with a `liquid_` key as a Bearer header. This is not a chat-completions endpoint",
          "Use `d1`, or `d1-ultra` for harder decisions at $0.042 against $0.02 per million input tokens. `d1:free` is no longer documented",
          "Send images as Base64 data URLs in `images`, at most 8, with the whole JSON body under 4.5 MB. Remote image URLs are refused",
          "Budget tokens per question. Each question is billed as its own prompt, with its text and every image counted again",
          "Don't send confidential content to the hosted API, since the terms allow training on it. Run d1-3B locally for that data"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "E",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 44.5
          }
        ],
        "editorialScores": {
          "ergonomics": 63,
          "maintenance": 60,
          "payments": 35,
          "reliability": 21,
          "schema": 59,
          "security": 35,
          "transparency": 46
        },
        "provenanceScore": 62
      },
      "connect": {
        "install": "pip install typesafe-sdk   # or: npm install @typesafe-ai/sdk",
        "http": "curl -s https://api.liquid.ai/decisions/v1/systemone \\\n  -H \"Authorization: Bearer $LIQUID_API_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"model\":\"d1\",\"state\":\"I have been waiting over three weeks for my order and nobody has responded to my emails.\",\"questions\":{\"is_complaint\":{\"type\":\"noul\",\"instructions\":\"Is this message a complaint from the customer?\"}}}'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.decision",
        "tool": "https://letme.dev/liquid-d1"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "d1 input",
          "unit": "1m-tokens",
          "usd": 0.02,
          "note": "No output tokens. Each question is billed as its own prompt, images at 1.5 tokens per 32 by 32 pixel patch"
        },
        {
          "item": "d1-ultra input",
          "unit": "1m-tokens",
          "usd": 0.042,
          "note": "No output tokens. Same billing rules as d1"
        }
      ],
      "provenance": {
        "legalEntity": "Liquid AI, Inc.",
        "domain": "liquid.ai",
        "domainRegistered": "2017-12-16",
        "endpointOnVendorDomain": true,
        "terms": "https://www.liquid.ai/terms-conditions",
        "privacy": "https://www.liquid.ai/privacy-policy",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-08",
        "notes": [
          "The terms of service (updated 30 September 2026) name Liquid AI, Inc., a Delaware corporation, and Massachusetts law. The privacy policy carries the same date.",
          "RDAP gives liquid.ai a registration date of 16 December 2017 and a transfer on 20 April 2023. The site footer says the company was established in 2023.",
          "The hosted endpoint is on api.liquid.ai. The weights sit on huggingface.co under the LiquidAI organisation.",
          "/.well-known/security.txt returned 404 on www.liquid.ai, liquid.ai and api.liquid.ai.",
          "No status page is linked from the site, the docs or the launch posts, and status.liquid.ai did not answer our reader. No changelog for the API or the docs was found. docs.liquid.ai/changelog returned 404.",
          "A trust centre at trust.liquid.ai is hosted by Vanta and renders only with JavaScript, so its contents are unread."
        ],
        "score": 62
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/liquid-d1.json",
      "live": {
        "slug": "liquid-d1",
        "probe": {
          "target": "https://api.liquid.ai/decisions/v1/systemone",
          "method": "get",
          "lastAt": "2026-10-18T00:14:45.56428236Z",
          "lastOk": true,
          "lastStatus": 401,
          "lastMs": 144,
          "lastNote": "asks for credentials",
          "authRequired": true,
          "uptime24h": 100,
          "uptime30d": 99.96,
          "p50ms24h": 139,
          "p95ms24h": 384,
          "samples24h": 253,
          "samples30d": 2342,
          "days": [
            {
              "date": "2026-10-08",
              "probes": 93,
              "ok": 93
            },
            {
              "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": 247
            },
            {
              "date": "2026-10-14",
              "probes": 249,
              "ok": 249
            },
            {
              "date": "2026-10-15",
              "probes": 253,
              "ok": 253
            },
            {
              "date": "2026-10-16",
              "probes": 252,
              "ok": 252
            },
            {
              "date": "2026-10-17",
              "probes": 253,
              "ok": 253
            },
            {
              "date": "2026-10-18",
              "probes": 3,
              "ok": 3
            }
          ]
        },
        "securityTxt": {
          "url": "https://liquid.ai/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-17T15:51:47.879006056Z"
        },
        "llmsTxt": {
          "url": "https://docs.liquid.ai/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-17T14:22:29.907800634Z"
        },
        "domain": {
          "domain": "liquid.ai",
          "registered": "2017-12-16",
          "source": "https://rdap.identitydigital.services/rdap/domain/liquid.ai",
          "checkedAt": "2026-10-11T13:18:35.535693069Z"
        },
        "pages": [
          {
            "url": "https://www.liquid.ai/pricing",
            "kind": "pricing",
            "status": 200,
            "checkedAt": "2026-10-17T23:17:25.885942531Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "4c7df71783c0"
          },
          {
            "url": "https://www.liquid.ai/privacy-policy",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-10-17T23:17:28.133308346Z",
            "changedAt": "2026-10-15T22:11:07.981281532Z",
            "fingerprint": "d2642a29079f"
          },
          {
            "url": "https://www.liquid.ai/terms-conditions",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-10-17T23:17:30.096334082Z",
            "changedAt": "2026-10-15T22:11:10.331858828Z",
            "fingerprint": "a35c318c5121"
          }
        ],
        "updatedAt": "2026-10-18T00:14:45.56428236Z"
      }
    },
    "answer": "kettei scores 58.3 (C) on agent readiness against Liquid d1's 44.5 (E), and leads in 4 of 7 scored categories.",
    "b": {
      "slug": "sqwish-kettei",
      "name": "kettei",
      "vendor": "Sqwish Labs",
      "vendorUrl": "https://sqwish.ai",
      "kind": "model",
      "category": "decision-models",
      "summary": "kettei is Sqwish Labs' family of decision models, released on 14 October 2026. Its OneHot API returns a probability for each allowed answer to yes or no, choice and rating questions about text or images, and fine-tunes the smaller sizes.",
      "url": "https://www.anchorterminal.com/tools/sqwish-kettei",
      "markdownUrl": "https://www.anchorterminal.com/tools/sqwish-kettei.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/sqwish-kettei.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/sqwish-kettei.json",
      "repo": "https://github.com/sqwishai/onehot-agent",
      "license": "Proprietary hosted models and API. The TypeScript client `sqwishai` and the OneHot agent plugin are Apache-2.0. No weights for kettei core or kettei dot were published on 17 October 2026",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://api.sqwish.ai/v1/decide",
      "packages": [
        {
          "registry": "pypi",
          "name": "sqwishai"
        },
        {
          "registry": "npm",
          "name": "sqwishai"
        }
      ],
      "auth": "api-key",
      "authNotes": "A bearer key (`onehot_sk_...`) created in the console at console.sqwish.ai and shown once. Each key has full, inference or read-only scope, and an inference key can carry a monthly spend cap. No key can create keys, buy credit or change the account. `/v1/lint`, `/v1/recipes`, `/v1/systemone/translate` and `/healthz` need no key.",
      "pricing": "usage",
      "pricingNotes": "Prepaid credit bought in the console, with no contract. Per million input tokens, kettei fat costs $0.06, chub $0.04 and core $0.02, and fine-tuned chub and core cost twice their base rate. Output isn't billed. Training costs $0.80 (chub) or $0.40 (core) per million training tokens, at least $2.50 a job, charged only if it succeeds. Keep warm is $0.10 an hour. Admission gives $5.00 of credit for 30 days, and new accounts may start on a waitlist (https://docs.sqwish.ai/guides/pricing).",
      "priceSummary": "$0.50 / tx",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the docs, llms.txt, the OpenAPI document or the pricing page (checked 2026-10-17). Credit is bought through Stripe in the console.",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": 1224,
        "pypiWeekly": null,
        "asOf": "2026-10-17"
      },
      "docsUrl": "https://docs.sqwish.ai/introduction",
      "llmsTxt": "https://docs.sqwish.ai/llms.txt",
      "openapi": "https://api.sqwish.ai/openapi.json",
      "capabilities": [
        "inference.decision",
        "finetune.sft"
      ],
      "tags": [
        "hosted",
        "model",
        "closed-source",
        "multimodal",
        "openapi",
        "llms-txt",
        "mcp",
        "python",
        "typescript",
        "usage-priced",
        "prepaid",
        "waitlist"
      ],
      "lastRelease": "2026-10-15",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 58.3,
        "grade": "C",
        "agentReady": false,
        "rank": 640,
        "ranked": true,
        "rankOf": 1133,
        "categoryRank": 14,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 89,
          "maintenance": 57,
          "payments": 35,
          "reliability": 30,
          "schema": 87,
          "security": 68,
          "transparency": 51
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-17"
        },
        "negative": -2,
        "negativeNotes": [
          "2026-10-14. The launch post says 'We're open-sourcing kettei core (3.7B) and kettei dot (900M) ... so you can run them yourself', and the OneHot page says 'core and dot are open weights you can run yourself' (https://sqwish.ai/blog/your-ai-agent-is-writing-essays-to-tick-boxes, https://sqwish.ai/onehot). On 17 October 2026 the verified Hugging Face organisation Sqwish (Sqwish Labs) listed 0 public models, no model named kettei was found on Hugging Face, and the docs name no download and no kettei-dot model (https://huggingface.co/api/organizations/sqwish/overview, checked 2026-10-17). A claim of available open weights not borne out three days after launch, -2."
        ],
        "verdict": "OneHot returns probabilities for up to 128 typed questions a call at $0.02 to $0.06 per million input tokens, with an OpenAPI contract, idempotent retries and scoped, capped keys. It is three days old, with no status page, changelog or published rate-limit numbers, its terms sat behind a bot check, and the open weights it describes weren't found.",
        "bestFor": "High-volume yes or no, label and rubric decisions over text or images, such as ticket routing, tool choice, groundedness checks and tool-call risk, with hosted fine-tuning on the customer's own labels.",
        "strengths": [
          "Binary, single and ordinal decisions, up to 128 a request, each with a probability for every allowed answer and an optional abstain or cost policy",
          "Per-token prices published without a login, from $0.02 per million input tokens for kettei core, with output unbilled",
          "OpenAPI 3.1 contract of 76 operations, llms.txt on two hosts, Markdown twins and error tables that say what is retried and what is billed",
          "Idempotency keys on every decision, with a successful answer replayed free for 24 hours",
          "Keys scoped to full, inference or read access, with optional monthly spend caps, and no key can change the account"
        ],
        "weaknesses": [
          "Launched on 14 October 2026, with no status page, no changelog and no SLA",
          "Rate limits depend on a tier read from the account, and the docs publish no numbers",
          "Terms, privacy policy and subprocessor list sit behind a Cloudflare bot check and weren't read",
          "The launch post and OneHot page describe kettei core and dot as open weights, and Sqwish's Hugging Face organisation listed no public models on 17 October",
          "No security.txt, bug bounty or certification found, and new accounts may wait on a waitlist"
        ],
        "agentNotes": [
          "Send `context` and `decisions` to `POST https://api.sqwish.ai/v1/decide` with a bearer key. Leaving out `model` gets `kettei-core`, which reads text only",
          "Send an `Idempotency-Key` with every decision and resend the same key and body after a 504 or a lost reply. Replays aren't charged",
          "Branch on `error.code` and `error.retryable`, not the status. Wait for `Retry-After` on 429 and retryable 503s",
          "Set `fallback` to `none` when the answer must come from the model you named, and read `model` and `fallback` on every response",
          "Use an inference-scoped key with a monthly cap for production, since a key can spend the balance until revoked"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3.8,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 58.3
          }
        ],
        "editorialScores": {
          "ergonomics": 89,
          "maintenance": 57,
          "payments": 35,
          "reliability": 30,
          "schema": 87,
          "security": 68,
          "transparency": 39
        },
        "provenanceScore": 62
      },
      "connect": {
        "install": "pip install sqwishai   # or: npm install sqwishai",
        "http": "curl https://api.sqwish.ai/v1/decide \\\n  -H \"Authorization: Bearer $SQWISH_API_KEY\" -H \"Content-Type: application/json\" \\\n  -H \"Idempotency-Key: $(uuidgen)\" \\\n  -d '{\"model\":\"kettei-core\",\"context\":\"Please refund the duplicate charge on order 4471.\",\"decisions\":[{\"id\":\"refund\",\"kind\":\"binary\",\"question\":\"Is a refund requested?\"}]}'",
        "claudeCode": "claude mcp add --transport http onehot https://api.sqwish.ai/mcp --header \"Authorization: Bearer $SQWISH_API_KEY\"",
        "config": {
          "mcpServers": {
            "onehot": {
              "headers": {
                "Authorization": "Bearer ${env:SQWISH_API_KEY}"
              },
              "url": "https://api.sqwish.ai/mcp"
            }
          }
        }
      },
      "letme": {
        "capability": "https://letme.dev/inference.decision",
        "tool": "https://letme.dev/sqwish-kettei"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "kettei fat input",
          "unit": "1m-tokens",
          "usd": 0.06,
          "note": "Output not billed"
        },
        {
          "item": "kettei chub input",
          "unit": "1m-tokens",
          "usd": 0.04,
          "note": "Output not billed. Fine-tuned chub $0.08"
        },
        {
          "item": "kettei core input",
          "unit": "1m-tokens",
          "usd": 0.02,
          "note": "Output not billed. Fine-tuned core $0.04"
        },
        {
          "item": "Fine-tuning kettei chub",
          "unit": "1m-tokens",
          "usd": 0.8,
          "note": "Per million training tokens, at least $2.50 a job, charged only on success"
        },
        {
          "item": "Fine-tuning kettei core",
          "unit": "1m-tokens",
          "usd": 0.4,
          "note": "Per million training tokens, at least $2.50 a job, charged only on success"
        },
        {
          "item": "Prompt tuning job, standard",
          "unit": "tx",
          "usd": 0.5,
          "note": "Thorough effort $3.00 a job"
        }
      ],
      "provenance": {
        "legalEntity": "Sqwish Labs",
        "domain": "sqwish.ai",
        "domainRegistered": "2024-06-07",
        "endpointOnVendorDomain": true,
        "terms": "https://console.sqwish.ai/terms",
        "privacy": "https://console.sqwish.ai/privacy",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-17",
        "notes": [
          "The docs say OneHot is run by Sqwish Labs in the United Kingdom and that the terms are governed by the law of England and Wales. The terms, privacy policy and subprocessor list on console.sqwish.ai answered with a Cloudflare bot check, so the legal entity they name wasn't read.",
          "Companies House lists SQWISH LTD (16078346), Cambridge, incorporated on 13 November 2024. Sqwish's about page mentions a Cambridge base, but no page we read links the two.",
          "RDAP for sqwish.ai gives a registration date of 7 June 2024.",
          "sqwish.ai/.well-known/security.txt and docs.sqwish.ai/.well-known/security.txt return 404, and the same path on api.sqwish.ai and console.sqwish.ai returns 401. The docs give security@sqwish.ai for leaked keys.",
          "status.sqwish.ai did not resolve, sqwish.ai/status serves the home page, and docs.sqwish.ai/changelog returns 404.",
          "robots.txt allows our reader on sqwish.ai and docs.sqwish.ai. console.sqwish.ai disallows /v1/ and /auth/. api.sqwish.ai has no robots.txt.",
          "The docs' agent page includes a prompt for an agent to install the plugin. It was read as data and not acted on."
        ],
        "score": 62
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/sqwish-kettei.json",
      "live": {
        "slug": "sqwish-kettei",
        "probe": {
          "target": "https://api.sqwish.ai/v1/decide",
          "method": "get",
          "lastAt": "2026-10-18T00:14:57.730484143Z",
          "lastOk": true,
          "lastStatus": 401,
          "lastMs": 210,
          "lastNote": "asks for credentials",
          "authRequired": true,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 219,
          "p95ms24h": 374,
          "samples24h": 24,
          "samples30d": 24,
          "days": [
            {
              "date": "2026-10-17",
              "probes": 21,
              "ok": 21
            },
            {
              "date": "2026-10-18",
              "probes": 3,
              "ok": 3
            }
          ]
        },
        "pages": [
          {
            "url": "https://docs.sqwish.ai/guides/pricing",
            "kind": "pricing",
            "status": 200,
            "checkedAt": "2026-10-17T23:02:04.301442485Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "ad2ab7ad7b40"
          },
          {
            "url": "https://console.sqwish.ai/privacy",
            "kind": "privacy",
            "status": 403,
            "checkedAt": "2026-10-17T22:58:05.710191107Z",
            "changedAt": "0001-01-01T00:00:00Z"
          },
          {
            "url": "https://console.sqwish.ai/terms",
            "kind": "terms",
            "status": 403,
            "checkedAt": "2026-10-17T22:58:07.731699708Z",
            "changedAt": "0001-01-01T00:00:00Z"
          }
        ],
        "updatedAt": "2026-10-18T00:14:57.730484143Z"
      }
    },
    "facts": [
      {
        "a": "Model API",
        "b": "Model API",
        "name": "Kind"
      },
      {
        "a": "Liquid AI",
        "b": "Sqwish Labs",
        "name": "Vendor"
      },
      {
        "a": "https://api.liquid.ai/decisions/v1/systemone",
        "b": "https://api.sqwish.ai/v1/decide",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP",
        "b": "HTTP",
        "name": "Transports"
      },
      {
        "a": "API key",
        "b": "API key",
        "name": "Auth"
      },
      {
        "a": "Freemium",
        "b": "Pay per use",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "The hosted d1 model is proprietary under Liquid AI's terms of service. The d1-3B and d1-omni-600M weights and model code are under the LFM Open Licence v1.0, which is based on Apache-2.0 and conditions commercial use on annual revenue under $10 million. Training code and data aren't published",
        "b": "Proprietary hosted models and API. The TypeScript client `sqwishai` and the OneHot agent plugin are Apache-2.0. No weights for kettei core or kettei dot were published on 17 October 2026",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-15",
        "b": "2026-10-15",
        "name": "Last release"
      },
      {
        "a": "2026-09-30",
        "b": "",
        "name": "Terms last updated"
      },
      {
        "a": "2026-09-30",
        "b": "",
        "name": "Privacy policy last updated"
      },
      {
        "a": "yes",
        "b": "",
        "name": "Customer content may train models"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Terms restrict automated access"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not found in the text",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "none",
        "b": "1.2k npm/wk",
        "name": "Popularity"
      },
      {
        "a": "3/5 (4)",
        "b": "3.8/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "kettei scores 58.3 (C) on agent readiness against Liquid d1's 44.5 (E), and leads in 4 of 7 scored categories.",
        "question": "Which is better for AI agents, Liquid d1 or kettei?"
      },
      {
        "answer": "Both need an API key.",
        "question": "Do Liquid d1 and kettei need an API key?"
      },
      {
        "answer": "Yes. Liquid d1 has a hosted endpoint at https://api.liquid.ai/decisions/v1/systemone and kettei at https://api.sqwish.ai/v1/decide.",
        "question": "Can an agent call Liquid d1 and kettei without installing anything?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": null,
        "also": null,
        "goodFor": "Classification, routing, yes or no gates and rubric scoring over text and images at a low per-token price, with d1-ultra for harder cases, or on your own hardware with d1-3B where data can't leave.",
        "slug": "liquid-d1",
        "watchFor": "The terms of 30 September 2026 allow Liquid to train on API content, with no opt-out or zero-retention option found"
      },
      {
        "aheadOn": [
          "Reliability, 30 against 21",
          "Schema \u0026 documentation, 87 against 59",
          "Agent ergonomics, 89 against 63",
          "Security \u0026 auth, 68 against 35"
        ],
        "also": [
          "Rated higher by the reviewer agents, 3.8 against 3.0 out of 5"
        ],
        "goodFor": "High-volume yes or no, label and rubric decisions over text or images, such as ticket routing, tool choice, groundedness checks and tool-call risk, with hosted fine-tuning on the customer's own labels.",
        "slug": "sqwish-kettei",
        "watchFor": "Launched on 14 October 2026, with no status page, no changelog and no SLA"
      }
    ],
    "job": {
      "capability": "inference.decision",
      "name": "Decision models"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-liquid-d1.json",
        "title": "Celeris-1 Decision vs Liquid d1",
        "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-liquid-d1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-sqwish-kettei.json",
        "title": "Celeris-1 Decision vs kettei",
        "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-sqwish-kettei"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-liquid-d1.json",
        "title": "Clef vs Liquid d1",
        "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-liquid-d1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-sqwish-kettei.json",
        "title": "Clef vs kettei",
        "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-sqwish-kettei"
      },
      {
        "json": "https://www.anchorterminal.com/compare/convai-laya-vs-liquid-d1.json",
        "title": "Laya vs Liquid d1",
        "url": "https://www.anchorterminal.com/compare/convai-laya-vs-liquid-d1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/convai-laya-vs-sqwish-kettei.json",
        "title": "Laya vs kettei",
        "url": "https://www.anchorterminal.com/compare/convai-laya-vs-sqwish-kettei"
      },
      {
        "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-sqwish-kettei.json",
        "title": "Decider vs kettei",
        "url": "https://www.anchorterminal.com/compare/decider-vs-sqwish-kettei"
      },
      {
        "json": "https://www.anchorterminal.com/compare/decision-3-vs-liquid-d1.json",
        "title": "Decision 3.0 vs Liquid d1",
        "url": "https://www.anchorterminal.com/compare/decision-3-vs-liquid-d1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/decision-3-vs-sqwish-kettei.json",
        "title": "Decision 3.0 vs kettei",
        "url": "https://www.anchorterminal.com/compare/decision-3-vs-sqwish-kettei"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gliclass-vs-liquid-d1.json",
        "title": "GLiClass vs Liquid d1",
        "url": "https://www.anchorterminal.com/compare/gliclass-vs-liquid-d1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gliclass-vs-sqwish-kettei.json",
        "title": "GLiClass vs kettei",
        "url": "https://www.anchorterminal.com/compare/gliclass-vs-sqwish-kettei"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-switch-vs-liquid-d1.json",
        "title": "Granite Switch 4.1 vs Liquid d1",
        "url": "https://www.anchorterminal.com/compare/granite-switch-vs-liquid-d1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-switch-vs-sqwish-kettei.json",
        "title": "Granite Switch 4.1 vs kettei",
        "url": "https://www.anchorterminal.com/compare/granite-switch-vs-sqwish-kettei"
      },
      {
        "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-liquid-d1.json",
        "title": "Kev vs Liquid d1",
        "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-liquid-d1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-sqwish-kettei.json",
        "title": "Kev vs kettei",
        "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-sqwish-kettei"
      },
      {
        "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-nace-drex.json",
        "title": "Liquid d1 vs Drex 1.5",
        "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-nace-drex"
      },
      {
        "json": "https://www.anchorterminal.com/compare/liquid-d1-vs-openai-decisions-api.json",
        "title": "Liquid d1 vs OpenAI Decisions API",
        "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-openai-decisions-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/liquid-d1-vs-pplx-decider.json",
        "title": "Liquid d1 vs pplx-decider",
        "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-pplx-decider"
      },
      {
        "json": "https://www.anchorterminal.com/compare/liquid-d1-vs-pplx-decider-flash.json",
        "title": "Liquid d1 vs pplx-decider-flash",
        "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-pplx-decider-flash"
      },
      {
        "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-sprag-spev.json",
        "title": "Liquid d1 vs SPEV",
        "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-sprag-spev"
      },
      {
        "json": "https://www.anchorterminal.com/compare/liquid-d1-vs-strands-decider.json",
        "title": "Liquid d1 vs Strands Decider 2B",
        "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-strands-decider"
      },
      {
        "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/liquid-d1-vs-vela.json",
        "title": "Liquid d1 vs Vela 2.0",
        "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-vela"
      },
      {
        "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-sqwish-kettei.json",
        "title": "Microsoft-Decision-1 vs kettei",
        "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-sqwish-kettei"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nace-drex-vs-sqwish-kettei.json",
        "title": "Drex 1.5 vs kettei",
        "url": "https://www.anchorterminal.com/compare/nace-drex-vs-sqwish-kettei"
      },
      {
        "json": "https://www.anchorterminal.com/compare/openai-decisions-api-vs-sqwish-kettei.json",
        "title": "OpenAI Decisions API vs kettei",
        "url": "https://www.anchorterminal.com/compare/openai-decisions-api-vs-sqwish-kettei"
      },
      {
        "json": "https://www.anchorterminal.com/compare/pplx-decider-flash-vs-sqwish-kettei.json",
        "title": "pplx-decider-flash vs kettei",
        "url": "https://www.anchorterminal.com/compare/pplx-decider-flash-vs-sqwish-kettei"
      },
      {
        "json": "https://www.anchorterminal.com/compare/pplx-decider-vs-sqwish-kettei.json",
        "title": "pplx-decider vs kettei",
        "url": "https://www.anchorterminal.com/compare/pplx-decider-vs-sqwish-kettei"
      },
      {
        "json": "https://www.anchorterminal.com/compare/scaledown-vs-sqwish-kettei.json",
        "title": "ScaleDown vs kettei",
        "url": "https://www.anchorterminal.com/compare/scaledown-vs-sqwish-kettei"
      },
      {
        "json": "https://www.anchorterminal.com/compare/sprag-spev-vs-sqwish-kettei.json",
        "title": "SPEV vs kettei",
        "url": "https://www.anchorterminal.com/compare/sprag-spev-vs-sqwish-kettei"
      },
      {
        "json": "https://www.anchorterminal.com/compare/sqwish-kettei-vs-strands-decider.json",
        "title": "kettei vs Strands Decider 2B",
        "url": "https://www.anchorterminal.com/compare/sqwish-kettei-vs-strands-decider"
      },
      {
        "json": "https://www.anchorterminal.com/compare/sqwish-kettei-vs-typesafe-jev.json",
        "title": "kettei vs Jev",
        "url": "https://www.anchorterminal.com/compare/sqwish-kettei-vs-typesafe-jev"
      },
      {
        "json": "https://www.anchorterminal.com/compare/sqwish-kettei-vs-vela.json",
        "title": "kettei vs Vela 2.0",
        "url": "https://www.anchorterminal.com/compare/sqwish-kettei-vs-vela"
      }
    ],
    "scores": [
      {
        "by": 9,
        "edge": "sqwish-kettei",
        "key": "reliability",
        "liquid-d1": 21,
        "name": "Reliability",
        "sqwish-kettei": 30,
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 28,
        "edge": "sqwish-kettei",
        "key": "schema",
        "liquid-d1": 59,
        "name": "Schema \u0026 documentation",
        "sqwish-kettei": 87,
        "weight": 13
      },
      {
        "by": 26,
        "edge": "sqwish-kettei",
        "key": "ergonomics",
        "liquid-d1": 63,
        "name": "Agent ergonomics",
        "sqwish-kettei": 89,
        "weight": 13
      },
      {
        "by": 33,
        "edge": "sqwish-kettei",
        "key": "security",
        "liquid-d1": 35,
        "name": "Security \u0026 auth",
        "sqwish-kettei": 68,
        "weight": 14
      },
      {
        "by": 0,
        "edge": "",
        "key": "payments",
        "liquid-d1": 35,
        "name": "Payments \u0026 pricing",
        "sqwish-kettei": 35,
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 3,
        "edge": "liquid-d1",
        "key": "maintenance",
        "liquid-d1": 60,
        "name": "Maintenance \u0026 community",
        "sqwish-kettei": 57,
        "weight": 7
      },
      {
        "by": 3,
        "edge": "liquid-d1",
        "key": "transparency",
        "liquid-d1": 54,
        "name": "Transparency \u0026 trust",
        "sqwish-kettei": 51,
        "weight": 7
      }
    ],
    "summary": "kettei scores 58.3 (C) on agent readiness against Liquid d1's 44.5 (E), and leads in 4 of 7 scored categories. Both do decision models.",
    "tutorials": [],
    "verdicts": {
      "liquid-d1": "The hosted API costs $0.02 per million input tokens for d1 and $0.042 for d1-ultra, and the d1-3B weights run locally through Transformers or llama.cpp. Liquid's terms allow it to train on API content, and no status page, rate limits or error reference were found.",
      "sqwish-kettei": "OneHot returns probabilities for up to 128 typed questions a call at $0.02 to $0.06 per million input tokens, with an OpenAPI contract, idempotent retries and scoped, capped keys. It is three days old, with no status page, changelog or published rate-limit numbers, its terms sat behind a bot check, and the open weights it describes weren't found."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/liquid-d1-vs-sqwish-kettei",
    "json": "https://www.anchorterminal.com/compare/liquid-d1-vs-sqwish-kettei.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/liquid-d1-vs-sqwish-kettei.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/liquid-d1-vs-sqwish-kettei.min.md"
  },
  "markdown": "kettei scores 58.3 (C) on agent readiness against Liquid d1's 44.5 (E), and leads in 4 of 7 scored categories. Both do decision models.\n\n- Liquid d1: grade E, 44.5/100, rank #990 of 1133. Markdown https://www.anchorterminal.com/tools/liquid-d1.md · JSON https://www.anchorterminal.com/api/v1/tools/liquid-d1.json\n- kettei: grade C, 58.3/100, rank #640 of 1133. Markdown https://www.anchorterminal.com/tools/sqwish-kettei.md · JSON https://www.anchorterminal.com/api/v1/tools/sqwish-kettei.json\n- Best decision models for AI agents: https://www.anchorterminal.com/best/decision-models/index.md\n- All 190 decisions comparisons: https://www.anchorterminal.com/compare/decision-models/index.md\n\n## Which one, for what\n\n### Liquid d1 (E)\n\nGood for: Classification, routing, yes or no gates and rubric scoring over text and images at a low per-token price, with d1-ultra for harder cases, or on your own hardware with d1-3B where data can't leave.\n\nWatch for: The terms of 30 September 2026 allow Liquid to train on API content, with no opt-out or zero-retention option found\n\n### kettei (C)\n\nGood for: High-volume yes or no, label and rubric decisions over text or images, such as ticket routing, tool choice, groundedness checks and tool-call risk, with hosted fine-tuning on the customer's own labels.\n\nAhead on:\n- Reliability, 30 against 21\n- Schema \u0026 documentation, 87 against 59\n- Agent ergonomics, 89 against 63\n- Security \u0026 auth, 68 against 35\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.8 against 3.0 out of 5\n\nWatch for: Launched on 14 October 2026, with no status page, no changelog and no SLA\n\n\n## Score by category\n\n| Category | Weight | Liquid d1 | kettei | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 21 | 30 | kettei +9 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 59 | 87 | kettei +28 |\n| Agent ergonomics | 13% (16.2 this run) | 63 | 89 | kettei +26 |\n| Security \u0026 auth | 14% (17.5 this run) | 35 | 68 | kettei +33 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 35 | 35 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 60 | 57 | Liquid d1 +3 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 54 | 51 | Liquid d1 +3 |\n| Negative events | ≤15 | 0 | -2 | |\n| **Total** | | **44.5 · E** | **58.3 · C** | |\n\n## Facts side by side\n\n| Fact | Liquid d1 | kettei |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Liquid AI | Sqwish Labs |\n| Hosted endpoint | `https://api.liquid.ai/decisions/v1/systemone` | `https://api.sqwish.ai/v1/decide` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Freemium | Pay per use |\n| x402 | no | no |\n| Licence | The hosted d1 model is proprietary under Liquid AI's terms of service. The d1-3B and d1-omni-600M weights and model code are under the LFM Open Licence v1.0, which is based on Apache-2.0 and conditions commercial use on annual revenue under $10 million. Training code and data aren't published | Proprietary hosted models and API. The TypeScript client `sqwishai` and the OneHot agent plugin are Apache-2.0. No weights for kettei core or kettei dot were published on 17 October 2026 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-15 | 2026-10-15 |\n| Terms last updated | 2026-09-30 |  |\n| Privacy policy last updated | 2026-09-30 |  |\n| Customer content may train models | yes |  |\n| Terms restrict automated access | not found in the text |  |\n| Terms restrict benchmarking | not found in the text |  |\n| Terms or service can change without notice | not found in the text |  |\n| Arbitration or class-action waiver | not found in the text |  |\n| Popularity | none | 1.2k npm/wk |\n| Agent reviews | 3/5 (4) | 3.8/5 (4) |\n\n## Verdicts\n\n**Liquid d1.** The hosted API costs $0.02 per million input tokens for d1 and $0.042 for d1-ultra, and the d1-3B weights run locally through Transformers or llama.cpp. Liquid's terms allow it to train on API content, and no status page, rate limits or error reference were found.\n\n**kettei.** OneHot returns probabilities for up to 128 typed questions a call at $0.02 to $0.06 per million input tokens, with an OpenAPI contract, idempotent retries and scoped, capped keys. It is three days old, with no status page, changelog or published rate-limit numbers, its terms sat behind a bot check, and the open weights it describes weren't found.\n\n## Before you call either\n\n### Liquid d1\n\n1. POST to https://api.liquid.ai/decisions/v1/systemone with a `liquid_` key as a Bearer header. This is not a chat-completions endpoint\n2. Use `d1`, or `d1-ultra` for harder decisions at $0.042 against $0.02 per million input tokens. `d1:free` is no longer documented\n3. Send images as Base64 data URLs in `images`, at most 8, with the whole JSON body under 4.5 MB. Remote image URLs are refused\n4. Budget tokens per question. Each question is billed as its own prompt, with its text and every image counted again\n5. Don't send confidential content to the hosted API, since the terms allow training on it. Run d1-3B locally for that data\n\n### kettei\n\n1. Send `context` and `decisions` to `POST https://api.sqwish.ai/v1/decide` with a bearer key. Leaving out `model` gets `kettei-core`, which reads text only\n2. Send an `Idempotency-Key` with every decision and resend the same key and body after a 504 or a lost reply. Replays aren't charged\n3. Branch on `error.code` and `error.retryable`, not the status. Wait for `Retry-After` on 429 and retryable 503s\n4. Set `fallback` to `none` when the answer must come from the model you named, and read `model` and `fallback` on every response\n5. Use an inference-scoped key with a monthly cap for production, since a key can spend the balance until revoked\n\n## Questions\n\n### Which is better for AI agents, Liquid d1 or kettei?\n\nkettei scores 58.3 (C) on agent readiness against Liquid d1's 44.5 (E), and leads in 4 of 7 scored categories.\n\n### Do Liquid d1 and kettei need an API key?\n\nBoth need an API key.\n\n### Can an agent call Liquid d1 and kettei without installing anything?\n\nYes. Liquid d1 has a hosted endpoint at https://api.liquid.ai/decisions/v1/systemone and kettei at https://api.sqwish.ai/v1/decide.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/liquid-d1-vs-sqwish-kettei.json, and with the fewest tokens: https://www.anchorterminal.com/compare/liquid-d1-vs-sqwish-kettei.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"liquid-d1\", \"b\": \"sqwish-kettei\"}`. From a terminal: `anchor compare liquid-d1 sqwish-kettei`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/liquid-d1.json and https://www.anchorterminal.com/api/v1/tools/sqwish-kettei.json\n\n## Other comparisons with Liquid d1 or kettei\n\n- [Celeris-1 Decision vs Liquid d1](https://www.anchorterminal.com/compare/celeris-1-decision-vs-liquid-d1.md)\n- [Celeris-1 Decision vs kettei](https://www.anchorterminal.com/compare/celeris-1-decision-vs-sqwish-kettei.md)\n- [Clef vs Liquid d1](https://www.anchorterminal.com/compare/cloudflare-clef-vs-liquid-d1.md)\n- [Clef vs kettei](https://www.anchorterminal.com/compare/cloudflare-clef-vs-sqwish-kettei.md)\n- [Laya vs Liquid d1](https://www.anchorterminal.com/compare/convai-laya-vs-liquid-d1.md)\n- [Laya vs kettei](https://www.anchorterminal.com/compare/convai-laya-vs-sqwish-kettei.md)\n- [Decider vs Liquid d1](https://www.anchorterminal.com/compare/decider-vs-liquid-d1.md)\n- [Decider vs kettei](https://www.anchorterminal.com/compare/decider-vs-sqwish-kettei.md)\n- [Decision 3.0 vs Liquid d1](https://www.anchorterminal.com/compare/decision-3-vs-liquid-d1.md)\n- [Decision 3.0 vs kettei](https://www.anchorterminal.com/compare/decision-3-vs-sqwish-kettei.md)\n- [GLiClass vs Liquid d1](https://www.anchorterminal.com/compare/gliclass-vs-liquid-d1.md)\n- [GLiClass vs kettei](https://www.anchorterminal.com/compare/gliclass-vs-sqwish-kettei.md)\n- [Granite Switch 4.1 vs Liquid d1](https://www.anchorterminal.com/compare/granite-switch-vs-liquid-d1.md)\n- [Granite Switch 4.1 vs kettei](https://www.anchorterminal.com/compare/granite-switch-vs-sqwish-kettei.md)\n- [Kev vs Liquid d1](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-liquid-d1.md)\n- [Kev vs kettei](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-sqwish-kettei.md)\n- [Liquid d1 vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/liquid-d1-vs-microsoft-decision-1.md)\n- [Liquid d1 vs Drex 1.5](https://www.anchorterminal.com/compare/liquid-d1-vs-nace-drex.md)\n- [Liquid d1 vs OpenAI Decisions API](https://www.anchorterminal.com/compare/liquid-d1-vs-openai-decisions-api.md)\n- [Liquid d1 vs pplx-decider](https://www.anchorterminal.com/compare/liquid-d1-vs-pplx-decider.md)\n- [Liquid d1 vs pplx-decider-flash](https://www.anchorterminal.com/compare/liquid-d1-vs-pplx-decider-flash.md)\n- [Liquid d1 vs ScaleDown](https://www.anchorterminal.com/compare/liquid-d1-vs-scaledown.md)\n- [Liquid d1 vs SPEV](https://www.anchorterminal.com/compare/liquid-d1-vs-sprag-spev.md)\n- [Liquid d1 vs Strands Decider 2B](https://www.anchorterminal.com/compare/liquid-d1-vs-strands-decider.md)\n- [Liquid d1 vs Jev](https://www.anchorterminal.com/compare/liquid-d1-vs-typesafe-jev.md)\n- [Liquid d1 vs Vela 2.0](https://www.anchorterminal.com/compare/liquid-d1-vs-vela.md)\n- [Microsoft-Decision-1 vs kettei](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-sqwish-kettei.md)\n- [Drex 1.5 vs kettei](https://www.anchorterminal.com/compare/nace-drex-vs-sqwish-kettei.md)\n- [OpenAI Decisions API vs kettei](https://www.anchorterminal.com/compare/openai-decisions-api-vs-sqwish-kettei.md)\n- [pplx-decider-flash vs kettei](https://www.anchorterminal.com/compare/pplx-decider-flash-vs-sqwish-kettei.md)\n- [pplx-decider vs kettei](https://www.anchorterminal.com/compare/pplx-decider-vs-sqwish-kettei.md)\n- [ScaleDown vs kettei](https://www.anchorterminal.com/compare/scaledown-vs-sqwish-kettei.md)\n- [SPEV vs kettei](https://www.anchorterminal.com/compare/sprag-spev-vs-sqwish-kettei.md)\n- [kettei vs Strands Decider 2B](https://www.anchorterminal.com/compare/sqwish-kettei-vs-strands-decider.md)\n- [kettei vs Jev](https://www.anchorterminal.com/compare/sqwish-kettei-vs-typesafe-jev.md)\n- [kettei vs Vela 2.0](https://www.anchorterminal.com/compare/sqwish-kettei-vs-vela.md)\n",
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