{
  "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 a hosted API and the open-weight d1-3B and d1-omni-600M models.",
      "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": "The hosted `d1` model costs $0.04 per million input tokens and bills no output tokens, per the launch post of 5 October 2026 (https://www.liquid.ai/blog/d1-decision-model). Each question is billed as its own prompt, and an image counts 1.5 tokens per 32 by 32 pixel patch. A text-only `d1:free` model exists, with no published limits. Liquid's pricing page covers model licensing only. 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": "2026-10-07",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 43.5,
        "grade": "E",
        "agentReady": false,
        "rank": 582,
        "ranked": true,
        "rankOf": 629,
        "categoryRank": 8,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 63,
          "maintenance": 60,
          "payments": 27,
          "reliability": 21,
          "schema": 59,
          "security": 35,
          "transparency": 54
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-08"
        },
        "negative": 0,
        "verdict": "The hosted API costs $0.04 per million input tokens and takes TypeSafe's System One request, 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. The family launched between 22 September and 7 October 2026.",
        "bestFor": "Classification, routing, yes or no gates and rubric scoring over text and images at a low per-token price, or on your own hardware with d1-3B where data can't leave.",
        "strengths": [
          "$0.04 per million input tokens with no output tokens billed, per the launch post, and a text-only `d1:free` model",
          "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` model accepts 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, API changelog or versioned model IDs. The hosted models are `d1` and `d1:free`",
          "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` for images. `d1:free` is text-only and answers that it does not accept images",
          "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": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "E",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 43.5
          }
        ],
        "editorialScores": {
          "ergonomics": 63,
          "maintenance": 60,
          "payments": 27,
          "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": 0.04,
          "note": "No output tokens. Each question is billed as its own prompt, images at 1.5 tokens per 32 by 32 pixel patch"
        }
      ],
      "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": "2026-10-08T18:20:33.689995579Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 139,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 164,
          "p95ms24h": 391,
          "samples24h": 33,
          "samples30d": 33,
          "days": [
            {
              "date": "2026-10-08",
              "probes": 33,
              "ok": 33
            }
          ]
        },
        "securityTxt": {
          "url": "https://liquid.ai/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-08T15:39:08.129742302Z"
        },
        "updatedAt": "2026-10-08T18:20:33.689995579Z"
      }
    },
    "answer": "Vela 2.0 scores 66.5 (B) on agent readiness against Liquid d1's 43.5 (E), and leads in 6 of 7 scored categories. Liquid d1 leads on transparency \u0026 trust.",
    "b": {
      "slug": "vela",
      "name": "Vela 2.0",
      "vendor": "vLLM Semantic Router project and KR Labs",
      "vendorUrl": "https://vllm-sr.ai",
      "kind": "model",
      "category": "decision-models",
      "summary": "Vela 2.0 is a family of four open-weight decision models from the vLLM Semantic Router project and KR Labs, released on 6 October 2026 under Apache-2.0 for routing, safety checks, personal-data spans and hallucination checks.",
      "url": "https://www.anchorterminal.com/tools/vela",
      "markdownUrl": "https://www.anchorterminal.com/tools/vela.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/vela.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/vela.json",
      "repo": "https://github.com/vllm-project/semantic-router",
      "license": "Apache-2.0 (weights, code and documentation). The 0.3B's tokeniser keeps the Gemma Terms of Use, and training data keeps its own licences",
      "transports": [
        "http"
      ],
      "packages": [
        {
          "registry": "pypi",
          "name": "vllm-sr"
        }
      ],
      "auth": "none",
      "authNotes": "No account. The weights are public and ungated on Hugging Face. The bundled `vela2_serve.py` binds to 127.0.0.1 and ignores the Authorization header unless `VELA2_API_KEY` is set, after which it requires `Authorization: Bearer \u003ckey\u003e` and answers 401 otherwise. The router's model runtime has no authentication and publishes on 127.0.0.1 unless `--host` is passed.",
      "pricing": "free",
      "pricingNotes": "Free and open source, with nothing to buy and no hosted API. Hardware is the owner's cost. The 0.3B runs on a CPU, and the cards put GPU parameter memory at about 17 GB for the 4B. The router docs list about 32 GB for the 9B (checked 2026-10-08).",
      "priceSummary": "Free · OSS",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402. Vela 2.0 is software the owner runs, and neither server has a payment route (checked 2026-10-08).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 6054,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-08"
      },
      "docsUrl": "https://huggingface.co/collections/vllm-sr/vela-20",
      "openapi": "https://raw.githubusercontent.com/vllm-project/semantic-router/main/src/model-runtime/vllm_srun/api/openapi.yaml",
      "capabilities": [
        "inference.decision",
        "guard.pii",
        "guard.injection",
        "guard.moderation",
        "guard.self-host"
      ],
      "tags": [
        "model",
        "open-source",
        "open-weights",
        "self-hosted",
        "local",
        "free",
        "python",
        "openapi"
      ],
      "lastRelease": "2026-10-06",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 66.5,
        "grade": "B",
        "agentReady": false,
        "rank": 219,
        "ranked": true,
        "rankOf": 629,
        "categoryRank": 4,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 79,
          "maintenance": 84,
          "payments": 60,
          "reliability": 57,
          "schema": 78,
          "security": 60,
          "transparency": 48
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-08"
        },
        "negative": 0,
        "verdict": "One self-hosted call answers routing, prompt-attack, personal-data and unsupported-claim questions with probabilities and character offsets, under Apache-2.0 with SHA-256 manifests. The models are days old and carry no Hub version tags, and the three larger sizes keep 74 to 89 per cent of their Decision 2.0 bases on the Jev Decision Index by the authors' figures.",
        "bestFor": "Self-hosted routing and guardrail checks in one call, where span offsets for personal data or unsupported claims matter.",
        "strengths": [
          "Five question types in one request (choice, noul, score, set and span), with span answers as labelled character offsets and a probability each",
          "Apache-2.0 weights, code and documentation, ungated on Hugging Face, with safetensors files and a SHA256SUMS manifest in the three decoder repositories",
          "Two serving routes. A bundled FastAPI server on `POST /v1/systemone`, and the router's model runtime with an OpenAPI 3.0.3 contract and Prometheus metrics",
          "The model cards disclose evaluation protocol, including that the 0.3B release selection considered test results and that SQuAD v2 isn't zero-shot",
          "The router's release note lists where the 0.3B default is behind Vela 1.0, with numbers, and how to restore each Vela 1.0 model"
        ],
        "weaknesses": [
          "No version tags on the four Hub repositories, and the 4B and 9B weights were replaced in place on 3 October 2026",
          "Loading with `transformers` needs `trust_remote_code=True`, which runs Python from the model repository",
          "The router's `vllm-sr serve MODEL` engine mode is newer than the 0.4.0 stable release and needs the development channel",
          "By the authors' figures the 4B scores 31.63 on the Jev Decision Index 0.2.1 against 42.55 for its Decision 2.0 base",
          "The model runtime has no authentication, and the bundled server is open unless `VELA2_API_KEY` is set"
        ],
        "agentNotes": [
          "Pin a commit hash with `revision=` when loading from the Hub. The repositories have no tags and `main` has changed since launch",
          "Send the served name in `model`, for example `vllm-sr/Vela-2.0-4B`. The bundled server answers 422 to any other name",
          "Name span questions `pii`, `halu` or `toxic`, or set `\"head\": \"router\"`, to get the trained router head. Other labels go to the broad head",
          "Keep input under 16,384 tokens a sequence (8,192 on the 0.3B). The bundled server answers 413 when the questions alone don't fit",
          "Set `VELA2_API_KEY` before binding the bundled server beyond 127.0.0.1, and keep the model runtime on a trusted network"
        ],
        "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": 66.5
          }
        ],
        "editorialScores": {
          "ergonomics": 79,
          "maintenance": 84,
          "payments": 60,
          "reliability": 57,
          "schema": 78,
          "security": 60,
          "transparency": 68
        },
        "provenanceScore": 27
      },
      "connect": {
        "install": "pip install torch \"transformers\u003e=5.17\" safetensors tokenizers numpy fastapi uvicorn\n# from a local snapshot of vllm-sr/Vela-2.0-4B\npython vela2_serve.py --model . --device cuda --port 8001",
        "http": "curl -s localhost:8001/v1/systemone -H 'content-type: application/json' \\\n  -d '{\"model\":\"vllm-sr/Vela-2.0-4B\",\"state\":\"My card was charged twice and the parcel never arrived.\",\"questions\":{\"issues\":{\"type\":\"set\",\"instructions\":\"Which issues does the customer report?\",\"criteria\":{\"billing\":\"payments, charges, refunds or invoices\",\"shipping\":\"delivery of an order or a parcel\",\"login\":\"signing in, passwords or account access\"}}}}'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.decision",
        "tool": "https://letme.dev/vela"
      },
      "area": "models",
      "provenance": {
        "legalEntity": "",
        "domain": "vllm-sr.ai",
        "domainRegistered": "2026-07-13",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://vllm-sr.ai/docs/release-notes/vela-2-0-built-in-signals",
        "securityTxt": "none",
        "checked": "2026-10-08",
        "notes": [
          "An open-source project with no company named as publisher. The site footer reads vLLM Semantic Router Team, and the model cards credit KR Labs and vLLM Semantic Router.",
          "RDAP gives 13 July 2026 as the registration date of vllm-sr.ai.",
          "Software the owner runs, so there's no hosted endpoint, terms or privacy policy. The Apache-2.0 licence stands in for terms.",
          "vllm-sr.ai/.well-known/security.txt returns 404. SECURITY.md in the repository takes private reports through GitHub Security Advisories.",
          "The weights are on huggingface.co under the vllm-sr organisation, and the code for the router and its model runtime is at github.com/vllm-project/semantic-router."
        ],
        "score": 27
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/vela.json",
      "live": {
        "slug": "vela",
        "versions": [
          {
            "registry": "github",
            "name": "vllm-project/semantic-router",
            "version": "v0.4.0",
            "released": "2026-09-27",
            "seenAt": "2026-10-08T16:33:55.54175052Z"
          },
          {
            "registry": "pypi",
            "name": "vllm-sr",
            "version": "0.4.0",
            "released": "2026-09-27",
            "seenAt": "2026-10-08T16:33:55.414998665Z"
          }
        ],
        "githubStars": 6055,
        "pypiWeekly": 16024,
        "securityTxt": {
          "url": "https://vllm-sr.ai/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-08T15:38:46.503839021Z"
        },
        "updatedAt": "2026-10-08T16:33:55.54175052Z"
      }
    },
    "facts": [
      {
        "a": "Model API",
        "b": "Model API",
        "name": "Kind"
      },
      {
        "a": "Liquid AI",
        "b": "vLLM Semantic Router project and KR Labs",
        "name": "Vendor"
      },
      {
        "a": "https://api.liquid.ai/decisions/v1/systemone",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP",
        "b": "HTTP",
        "name": "Transports"
      },
      {
        "a": "API key",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Freemium",
        "b": "Free",
        "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": "Apache-2.0 (weights, code and documentation). The 0.3B's tokeniser keeps the Gemma Terms of Use, and training data keeps its own licences",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-07",
        "b": "2026-10-06",
        "name": "Last release"
      },
      {
        "a": "2026-09-30",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "2026-09-30",
        "b": "no document linked",
        "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": "6.1k stars",
        "name": "Popularity"
      }
    ],
    "faq": [
      {
        "answer": "Vela 2.0 scores 66.5 (B) on agent readiness against Liquid d1's 43.5 (E), and leads in 6 of 7 scored categories. Liquid d1 leads on transparency \u0026 trust.",
        "question": "Which is better for AI agents, Liquid d1 or Vela 2.0?"
      },
      {
        "answer": "Liquid d1 needs an API key. Vela 2.0 needs no key.",
        "question": "Do Liquid d1 and Vela 2.0 need an API key?"
      },
      {
        "answer": "Liquid d1 has a hosted endpoint at https://api.liquid.ai/decisions/v1/systemone. No hosted endpoint is listed for Vela 2.0.",
        "question": "Can an agent call Liquid d1 and Vela 2.0 without installing anything?"
      },
      {
        "answer": "No open-source release is listed for Liquid d1. Vela 2.0 is open source (Apache-2.0 (weights, code and documentation). The 0.3B's tokeniser keeps the Gemma Terms of Use, and training data keeps its own licences).",
        "question": "Are Liquid d1 and Vela 2.0 open source?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Transparency \u0026 trust, 54 against 48"
        ],
        "also": [
          "A hosted endpoint, with nothing to install"
        ],
        "goodFor": "Classification, routing, yes or no gates and rubric scoring over text and images at a low per-token price, 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, 57 against 21",
          "Schema \u0026 documentation, 78 against 59",
          "Agent ergonomics, 79 against 63",
          "Security \u0026 auth, 60 against 35",
          "Payments \u0026 pricing, 60 against 27",
          "Maintenance \u0026 community, 84 against 60"
        ],
        "also": [
          "No key needed to call it",
          "Open source"
        ],
        "goodFor": "Self-hosted routing and guardrail checks in one call, where span offsets for personal data or unsupported claims matter.",
        "slug": "vela",
        "watchFor": "No version tags on the four Hub repositories, and the 4B and 9B weights were replaced in place on 3 October 2026"
      }
    ],
    "job": {
      "capability": "inference.decision",
      "name": "Inference decision"
    },
    "others": [
      {
        "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-vela.json",
        "title": "Clef vs Vela 2.0",
        "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-vela"
      },
      {
        "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-vela.json",
        "title": "Laya vs Vela 2.0",
        "url": "https://www.anchorterminal.com/compare/convai-laya-vs-vela"
      },
      {
        "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-vela.json",
        "title": "Kev vs Vela 2.0",
        "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-vela"
      },
      {
        "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-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/openai-decisions-api-vs-vela.json",
        "title": "OpenAI Decisions API vs Vela 2.0",
        "url": "https://www.anchorterminal.com/compare/openai-decisions-api-vs-vela"
      },
      {
        "json": "https://www.anchorterminal.com/compare/strands-decider-vs-vela.json",
        "title": "Strands Decider 2B vs Vela 2.0",
        "url": "https://www.anchorterminal.com/compare/strands-decider-vs-vela"
      },
      {
        "json": "https://www.anchorterminal.com/compare/typesafe-jev-vs-vela.json",
        "title": "Jev vs Vela 2.0",
        "url": "https://www.anchorterminal.com/compare/typesafe-jev-vs-vela"
      }
    ],
    "scores": [
      {
        "by": 36,
        "edge": "vela",
        "key": "reliability",
        "liquid-d1": 21,
        "name": "Reliability",
        "vela": 57,
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 19,
        "edge": "vela",
        "key": "schema",
        "liquid-d1": 59,
        "name": "Schema \u0026 documentation",
        "vela": 78,
        "weight": 13
      },
      {
        "by": 16,
        "edge": "vela",
        "key": "ergonomics",
        "liquid-d1": 63,
        "name": "Agent ergonomics",
        "vela": 79,
        "weight": 13
      },
      {
        "by": 25,
        "edge": "vela",
        "key": "security",
        "liquid-d1": 35,
        "name": "Security \u0026 auth",
        "vela": 60,
        "weight": 14
      },
      {
        "by": 33,
        "edge": "vela",
        "key": "payments",
        "liquid-d1": 27,
        "name": "Payments \u0026 pricing",
        "vela": 60,
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 24,
        "edge": "vela",
        "key": "maintenance",
        "liquid-d1": 60,
        "name": "Maintenance \u0026 community",
        "vela": 84,
        "weight": 7
      },
      {
        "by": 6,
        "edge": "liquid-d1",
        "key": "transparency",
        "liquid-d1": 54,
        "name": "Transparency \u0026 trust",
        "vela": 48,
        "weight": 7
      }
    ],
    "summary": "Vela 2.0 scores 66.5 (B) on agent readiness against Liquid d1's 43.5 (E), and leads in 6 of 7 scored categories. Liquid d1 leads on transparency \u0026 trust. Both do inference decision.",
    "verdicts": {
      "liquid-d1": "The hosted API costs $0.04 per million input tokens and takes TypeSafe's System One request, 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. The family launched between 22 September and 7 October 2026.",
      "vela": "One self-hosted call answers routing, prompt-attack, personal-data and unsupported-claim questions with probabilities and character offsets, under Apache-2.0 with SHA-256 manifests. The models are days old and carry no Hub version tags, and the three larger sizes keep 74 to 89 per cent of their Decision 2.0 bases on the Jev Decision Index by the authors' figures."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/liquid-d1-vs-vela",
    "json": "https://www.anchorterminal.com/compare/liquid-d1-vs-vela.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/liquid-d1-vs-vela.md",
    "slim": "https://www.anchorterminal.com/compare/liquid-d1-vs-vela.min.md"
  },
  "markdown": "Vela 2.0 scores 66.5 (B) on agent readiness against Liquid d1's 43.5 (E), and leads in 6 of 7 scored categories. Liquid d1 leads on transparency \u0026 trust. Both do inference decision.\n\n- Liquid d1: grade E, 43.5/100, rank #582 of 629. Markdown https://www.anchorterminal.com/tools/liquid-d1.md · JSON https://www.anchorterminal.com/api/v1/tools/liquid-d1.json\n- Vela 2.0: grade B, 66.5/100, rank #219 of 629. Markdown https://www.anchorterminal.com/tools/vela.md · JSON https://www.anchorterminal.com/api/v1/tools/vela.json\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, or on your own hardware with d1-3B where data can't leave.\n\nAhead on:\n- Transparency \u0026 trust, 54 against 48\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\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### Vela 2.0 (B)\n\nGood for: Self-hosted routing and guardrail checks in one call, where span offsets for personal data or unsupported claims matter.\n\nAhead on:\n- Reliability, 57 against 21\n- Schema \u0026 documentation, 78 against 59\n- Agent ergonomics, 79 against 63\n- Security \u0026 auth, 60 against 35\n- Payments \u0026 pricing, 60 against 27\n- Maintenance \u0026 community, 84 against 60\n\nAlso in its favour:\n- No key needed to call it\n- Open source\n\nWatch for: No version tags on the four Hub repositories, and the 4B and 9B weights were replaced in place on 3 October 2026\n\n\n## Score by category\n\n| Category | Weight | Liquid d1 | Vela 2.0 | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 21 | 57 | Vela 2.0 +36 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 59 | 78 | Vela 2.0 +19 |\n| Agent ergonomics | 13% (16.2 this run) | 63 | 79 | Vela 2.0 +16 |\n| Security \u0026 auth | 14% (17.5 this run) | 35 | 60 | Vela 2.0 +25 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 27 | 60 | Vela 2.0 +33 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 60 | 84 | Vela 2.0 +24 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 54 | 48 | Liquid d1 +6 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **43.5 · E** | **66.5 · B** | |\n\n## Facts side by side\n\n| Fact | Liquid d1 | Vela 2.0 |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Liquid AI | vLLM Semantic Router project and KR Labs |\n| Hosted endpoint | `https://api.liquid.ai/decisions/v1/systemone` | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | API key | None |\n| Pricing | Freemium | Free |\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 | Apache-2.0 (weights, code and documentation). The 0.3B's tokeniser keeps the Gemma Terms of Use, and training data keeps its own licences |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| Last release | 2026-10-07 | 2026-10-06 |\n| Terms last updated | 2026-09-30 | no document linked |\n| Privacy policy last updated | 2026-09-30 | no document linked |\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 | 6.1k stars |\n\n## Verdicts\n\n**Liquid d1.** The hosted API costs $0.04 per million input tokens and takes TypeSafe's System One request, 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. The family launched between 22 September and 7 October 2026.\n\n**Vela 2.0.** One self-hosted call answers routing, prompt-attack, personal-data and unsupported-claim questions with probabilities and character offsets, under Apache-2.0 with SHA-256 manifests. The models are days old and carry no Hub version tags, and the three larger sizes keep 74 to 89 per cent of their Decision 2.0 bases on the Jev Decision Index by the authors' figures.\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` for images. `d1:free` is text-only and answers that it does not accept images\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### Vela 2.0\n\n1. Pin a commit hash with `revision=` when loading from the Hub. The repositories have no tags and `main` has changed since launch\n2. Send the served name in `model`, for example `vllm-sr/Vela-2.0-4B`. The bundled server answers 422 to any other name\n3. Name span questions `pii`, `halu` or `toxic`, or set `\"head\": \"router\"`, to get the trained router head. Other labels go to the broad head\n4. Keep input under 16,384 tokens a sequence (8,192 on the 0.3B). The bundled server answers 413 when the questions alone don't fit\n5. Set `VELA2_API_KEY` before binding the bundled server beyond 127.0.0.1, and keep the model runtime on a trusted network\n\n## Questions\n\n### Which is better for AI agents, Liquid d1 or Vela 2.0?\n\nVela 2.0 scores 66.5 (B) on agent readiness against Liquid d1's 43.5 (E), and leads in 6 of 7 scored categories. Liquid d1 leads on transparency \u0026 trust.\n\n### Do Liquid d1 and Vela 2.0 need an API key?\n\nLiquid d1 needs an API key. Vela 2.0 needs no key.\n\n### Can an agent call Liquid d1 and Vela 2.0 without installing anything?\n\nLiquid d1 has a hosted endpoint at https://api.liquid.ai/decisions/v1/systemone. No hosted endpoint is listed for Vela 2.0.\n\n### Are Liquid d1 and Vela 2.0 open source?\n\nNo open-source release is listed for Liquid d1. Vela 2.0 is open source (Apache-2.0 (weights, code and documentation). The 0.3B's tokeniser keeps the Gemma Terms of Use, and training data keeps its own licences).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/liquid-d1-vs-vela.json, and with the fewest tokens: https://www.anchorterminal.com/compare/liquid-d1-vs-vela.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"liquid-d1\", \"b\": \"vela\"}`. From a terminal: `anchor compare liquid-d1 vela`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/liquid-d1.json and https://www.anchorterminal.com/api/v1/tools/vela.json\n\n## Other comparisons with Liquid d1 or Vela 2.0\n\n- [Clef vs Liquid d1](https://www.anchorterminal.com/compare/cloudflare-clef-vs-liquid-d1.md)\n- [Clef vs Vela 2.0](https://www.anchorterminal.com/compare/cloudflare-clef-vs-vela.md)\n- [Laya vs Liquid d1](https://www.anchorterminal.com/compare/convai-laya-vs-liquid-d1.md)\n- [Laya vs Vela 2.0](https://www.anchorterminal.com/compare/convai-laya-vs-vela.md)\n- [Kev vs Liquid d1](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-liquid-d1.md)\n- [Kev vs Vela 2.0](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-vela.md)\n- [Liquid d1 vs OpenAI Decisions API](https://www.anchorterminal.com/compare/liquid-d1-vs-openai-decisions-api.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- [OpenAI Decisions API vs Vela 2.0](https://www.anchorterminal.com/compare/openai-decisions-api-vs-vela.md)\n- [Strands Decider 2B vs Vela 2.0](https://www.anchorterminal.com/compare/strands-decider-vs-vela.md)\n- [Jev vs Vela 2.0](https://www.anchorterminal.com/compare/typesafe-jev-vs-vela.md)\n",
  "meta": {
    "attribution": "Anchor Terminal (https://www.anchorterminal.com)",
    "docs": "https://www.anchorterminal.com/docs/",
    "generatedAt": "2026-10-08",
    "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"
  },
  "page": {
    "breadcrumbs": [
      {
        "name": "Home",
        "url": "https://www.anchorterminal.com/"
      },
      {
        "name": "Compare",
        "url": "https://www.anchorterminal.com/compare/"
      },
      {
        "name": "Liquid d1 vs Vela 2.0",
        "url": ""
      }
    ],
    "description": "Vela 2.0 scores 66.5 (B) on agent readiness against Liquid d1's 43.5 (E), and leads in 6 of 7 scored categories. Liquid d1 leads on transparency \u0026 trust. Both do inference decision. Category scores, facts, verdicts and agent notes side by side.",
    "facts": [
      "Liquid d1 E 43.5",
      "Vela 2.0 B 66.5",
      "scores"
    ],
    "h1": "Liquid d1 vs Vela 2.0",
    "image": "https://www.anchorterminal.com/assets/og/compare-liquid-d1-vs-vela.png",
    "path": "/compare/liquid-d1-vs-vela",
    "published": "2026-10-01",
    "section": "tools",
    "title": "Liquid d1 vs Vela 2.0 for AI agents, E 43.5 vs B 66.5",
    "toc": null,
    "updated": "2026-10-08",
    "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-vela"
  },
  "tokens": {
    "markdown": 2250,
    "slim": 780
  },
  "version": 1
}