{ "data": { "a": { "slug": "convai-laya", "name": "Laya", "vendor": "Convai Innovations", "vendorUrl": "https://convaiinnovations.com", "kind": "model", "category": "decision-models", "summary": "Open-source decision engine from Convai Innovations, released under Apache-2.0.", "url": "https://www.anchorterminal.com/tools/convai-laya", "markdownUrl": "https://www.anchorterminal.com/tools/convai-laya.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/convai-laya.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/convai-laya.json", "repo": "https://github.com/NandhaKishorM/laya", "license": "Apache-2.0", "transports": [ "http", "stdio" ], "packages": [ { "registry": "pypi", "name": "laya" } ], "auth": "none", "authNotes": "No account. `laya-serve` binds to 0.0.0.0:8000 and is open unless `LAYA_API_KEY` is set, after which it requires `Authorization: Bearer \u003ckey\u003e` on every route but liveness. The MCP server runs over stdio. Weights download from Hugging Face without an account.", "pricing": "free", "pricingNotes": "Free and open source, with nothing to buy. You pay for the hardware, and the README's speed figures were measured on a Tesla T4. The maintainer takes donations through Buy Me A Coffee (https://github.com/NandhaKishorM/laya).", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402. Laya is software you run, and its server has no payment route (checked 2026-10-02).", "endpoints": [] }, "toolCount": 8, "popularity": { "githubStars": 29200, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-02" }, "docsUrl": "https://nandhakishorm.github.io/laya/", "capabilities": [ "inference.decision" ], "tags": [ "model", "open-source", "open-weights", "self-hosted", "local", "free", "python", "mcp", "batch", "pre-1.0" ], "lastRelease": "2026-10-01", "graded": true, "anchor": { "graded": true, "score": 69.2, "grade": "B", "agentReady": false, "rank": 163, "ranked": true, "rankOf": 722, "categoryRank": 2, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 80, "maintenance": 83, "payments": 60, "reliability": 65, "schema": 80, "security": 57, "transparency": 62 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": 0, "verdict": "Apache-2.0 code and weights, installed with `pip install laya`, with Python 3.10 to 3.13 tested in CI. Base checkpoints score 0.362 and 0.352 on the maintainers' typed-decisions benchmark against a 0.318 random baseline, so it needs fine-tuning.", "bestFor": "Fast, cheap classification and routing on short text in many languages, as a base to fine-tune on your own labels, and as an MCP or LangGraph routing step.", "strengths": [ "Apache-2.0 code and weights, installed with `pip install laya`, with Python 3.10 to 3.13 tested in CI", "421M and 322M-parameter encoders that the README times at 32.8 to 39.5 ms for one question on a Tesla T4", "A Jev-compatible HTTP server with a batch route for up to 64 states, an 8-tool MCP server, and LangChain, LlamaIndex and CrewAI wrappers", "A multilingual checkpoint for 100+ languages and a router that picks the checkpoint per request", "An honest-limits section in the README, SECURITY.md with private reporting, and CI that runs gitleaks, pip-audit and CodeQL" ], "weaknesses": [ "Base checkpoints score 0.362 and 0.352 on the maintainers' typed-decisions benchmark against a 0.318 random baseline, so it needs fine-tuning", "Choice options share a 192 or 256-token budget, and the README reports 0.425 on Banking77's 77 labels", "512 tokens of context on the English checkpoint and 1,024 by default on the others", "`laya-serve` listens on 0.0.0.0 with no key unless `LAYA_API_KEY` is set", "26 releases in 13 days, still 0.x and marked beta, with 61 open issues and 81 open pull requests" ], "agentNotes": [ "Set `LAYA_API_KEY` before starting `laya-serve`. It listens on every interface by default", "Gate on `answer_confidence`, not `confidence`, which measures entropy and doesn't match Jev's field", "Shortlist choice questions with more than about 20 options using `predict_shortlist` or the `laya_shortlist` tool", "Use semantic or opaque labels such as `A` and `B`, not `yes` and `no`, in choice questions. The checkpoints can follow the label text", "Pass `model=\"multilingual\"` and `max_len=8192` for long documents. The English checkpoint stops at 512 tokens" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 2, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 69.2 } ], "editorialScores": { "ergonomics": 80, "maintenance": 83, "payments": 60, "reliability": 65, "schema": 80, "security": 57, "transparency": 70 }, "provenanceScore": 53 }, "connect": { "install": "pip install \"laya[serve]\"\nLAYA_API_KEY=change-me LAYA_DEVICE=cuda LAYA_PRELOAD=1 laya-serve # 0.0.0.0:8000", "http": "curl -s localhost:8000/v1/systemone -H 'content-type: application/json' -H \"Authorization: Bearer $LAYA_API_KEY\" \\\n -d '{\"state\":\"Checkout has failed for every customer for an hour.\",\"questions\":{\"urgent\":{\"type\":\"noul\",\"instructions\":\"Is this request urgent?\"},\"team\":{\"type\":\"choice\",\"criteria\":{\"billing\":\"Payments and refunds\",\"technical\":\"Outages and errors\"}}}}'", "claudeCode": "pip install \"laya[mcp]\" \u0026\u0026 claude mcp add laya -- laya-mcp-server", "config": { "mcpServers": { "laya": { "command": "laya-mcp-server", "env": { "LAYA_DEVICE": "cpu" } } } } }, "letme": { "capability": "https://letme.dev/inference.decision", "tool": "https://letme.dev/convai-laya" }, "area": "models", "provenance": { "legalEntity": "Convai Innovations Pvt. Ltd.", "domain": "convaiinnovations.com", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/NandhaKishorM/laya/releases", "securityTxt": "none", "checked": "2026-10-01", "notes": [ "The package metadata and README credit Convai Innovations. The company's site names Convai Innovations Pvt. Ltd. at the Kerala Startup Mission office in Kasaragod, Kerala, India, but doesn't mention Laya.", "convaiinnovations.com/.well-known/security.txt returns 404. SECURITY.md in the repository takes private reports through GitHub Security Advisories.", "We didn't read the domain's registration date.", "Software you run, so there's no hosted endpoint. The Apache-2.0 licence stands in for terms." ], "score": 53 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/convai-laya.json", "live": { "slug": "convai-laya", "versions": [ { "registry": "github", "name": "NandhaKishorM/laya", "version": "v0.4.0", "released": "2026-10-07", "seenAt": "2026-10-08T16:06:59.058927231Z" }, { "registry": "pypi", "name": "laya", "version": "0.4.0", "released": "2026-10-07", "seenAt": "2026-10-08T16:06:58.941467636Z" } ], "githubStars": 31667, "pypiWeekly": 77372, "securityTxt": { "url": "https://convaiinnovations.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-08T15:39:09.474636066Z" }, "domain": { "domain": "convaiinnovations.com", "registered": "2021-09-01", "source": "https://rdap.verisign.com/com/v1/domain/convaiinnovations.com", "checkedAt": "2026-10-04T13:08:27.291006176Z" }, "updatedAt": "2026-10-08T16:06:59.058927231Z" } }, "answer": "Laya scores 69.2 (B) on agent readiness against Liquid d1's 43.5 (E), and leads in every scored category.", "b": { "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": 672, "ranked": true, "rankOf": 722, "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": "2026-10-08T19:52:54.560591521Z", "lastOk": true, "lastStatus": 404, "lastMs": 151, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 164, "p95ms24h": 391, "samples24h": 50, "samples30d": 50, "days": [ { "date": "2026-10-08", "probes": 50, "ok": 50 } ] }, "securityTxt": { "url": "https://liquid.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-08T15:39:08.129742302Z" }, "pages": [ { "url": "https://www.liquid.ai/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-08T18:28:45.318974429Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "42d9e4ba3a39" }, { "url": "https://www.liquid.ai/terms-conditions", "kind": "terms", "status": 200, "checkedAt": "2026-10-08T18:28:47.564454912Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "8fd8f3573ffc" } ], "updatedAt": "2026-10-08T19:52:54.560591521Z" } }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Convai Innovations", "b": "Liquid AI", "name": "Vendor" }, { "a": "no (local only)", "b": "https://api.liquid.ai/decisions/v1/systemone", "name": "Hosted endpoint" }, { "a": "HTTP, stdio", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "API key", "name": "Auth" }, { "a": "Free", "b": "Freemium", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0", "b": "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", "name": "Licence" }, { "a": "8", "b": "none", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-01", "b": "2026-10-07", "name": "Last release" }, { "a": "no document linked", "b": "2026-09-30", "name": "Terms last updated" }, { "a": "no document linked", "b": "2026-09-30", "name": "Privacy policy last updated" }, { "a": "", "b": "yes", "name": "Customer content may train models" }, { "a": "", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "29k stars", "b": "none", "name": "Popularity" }, { "a": "2.5/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Laya scores 69.2 (B) on agent readiness against Liquid d1's 43.5 (E), and leads in every scored category.", "question": "Which is better for AI agents, Laya or Liquid d1?" }, { "answer": "Laya needs no key. Liquid d1 needs an API key.", "question": "Do Laya and Liquid d1 need an API key?" }, { "answer": "Laya runs on your own machine, with no hosted endpoint listed. Liquid d1 has a hosted endpoint at https://api.liquid.ai/decisions/v1/systemone.", "question": "Can an agent call Laya and Liquid d1 without installing anything?" }, { "answer": "Laya is open source (Apache-2.0). No open-source release is listed for Liquid d1.", "question": "Are Laya and Liquid d1 open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 65 against 21", "Schema \u0026 documentation, 80 against 59", "Agent ergonomics, 80 against 63", "Security \u0026 auth, 57 against 35", "Payments \u0026 pricing, 60 against 27", "Maintenance \u0026 community, 83 against 60", "Transparency \u0026 trust, 62 against 54" ], "also": [ "No key needed to call it", "Runs on your own machine", "Open source" ], "goodFor": "Fast, cheap classification and routing on short text in many languages, as a base to fine-tune on your own labels, and as an MCP or LangGraph routing step.", "slug": "convai-laya", "watchFor": "Base checkpoints score 0.362 and 0.352 on the maintainers' typed-decisions benchmark against a 0.318 random baseline, so it needs fine-tuning" }, { "aheadOn": null, "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" } ], "job": { "capability": "inference.decision", "name": "Inference decision" }, "others": [ { "json": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-convai-laya.json", "title": "Clef vs Laya", "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-convai-laya" }, { "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/convai-laya-vs-jaredpalmer-kev.json", "title": "Laya vs Kev", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-jaredpalmer-kev" }, { "json": "https://www.anchorterminal.com/compare/convai-laya-vs-openai-decisions-api.json", "title": "Laya vs OpenAI Decisions API", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-openai-decisions-api" }, { "json": "https://www.anchorterminal.com/compare/convai-laya-vs-strands-decider.json", "title": "Laya vs Strands Decider 2B", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-strands-decider" }, { "json": "https://www.anchorterminal.com/compare/convai-laya-vs-typesafe-jev.json", "title": "Laya vs Jev", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-typesafe-jev" }, { "json": "https://www.anchorterminal.com/compare/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/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/liquid-d1-vs-vela.json", "title": "Liquid d1 vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-vela" } ], "scores": [ { "by": 44, "convai-laya": 65, "edge": "convai-laya", "key": "reliability", "liquid-d1": 21, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 21, "convai-laya": 80, "edge": "convai-laya", "key": "schema", "liquid-d1": 59, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 17, "convai-laya": 80, "edge": "convai-laya", "key": "ergonomics", "liquid-d1": 63, "name": "Agent ergonomics", "weight": 13 }, { "by": 22, "convai-laya": 57, "edge": "convai-laya", "key": "security", "liquid-d1": 35, "name": "Security \u0026 auth", "weight": 14 }, { "by": 33, "convai-laya": 60, "edge": "convai-laya", "key": "payments", "liquid-d1": 27, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 23, "convai-laya": 83, "edge": "convai-laya", "key": "maintenance", "liquid-d1": 60, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 8, "convai-laya": 62, "edge": "convai-laya", "key": "transparency", "liquid-d1": 54, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Laya scores 69.2 (B) on agent readiness against Liquid d1's 43.5 (E), and leads in every scored category. Both do inference decision.", "verdicts": { "convai-laya": "Apache-2.0 code and weights, installed with `pip install laya`, with Python 3.10 to 3.13 tested in CI. Base checkpoints score 0.362 and 0.352 on the maintainers' typed-decisions benchmark against a 0.318 random baseline, so it needs fine-tuning.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/convai-laya-vs-liquid-d1", "json": "https://www.anchorterminal.com/compare/convai-laya-vs-liquid-d1.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/convai-laya-vs-liquid-d1.md", "slim": "https://www.anchorterminal.com/compare/convai-laya-vs-liquid-d1.min.md" }, "markdown": "Laya scores 69.2 (B) on agent readiness against Liquid d1's 43.5 (E), and leads in every scored category. Both do inference decision.\n\n- Laya: grade B, 69.2/100, rank #163 of 722. Markdown https://www.anchorterminal.com/tools/convai-laya.md · JSON https://www.anchorterminal.com/api/v1/tools/convai-laya.json\n- Liquid d1: grade E, 43.5/100, rank #672 of 722. Markdown https://www.anchorterminal.com/tools/liquid-d1.md · JSON https://www.anchorterminal.com/api/v1/tools/liquid-d1.json\n\n## Which one, for what\n\n### Laya (B)\n\nGood for: Fast, cheap classification and routing on short text in many languages, as a base to fine-tune on your own labels, and as an MCP or LangGraph routing step.\n\nAhead on:\n- Reliability, 65 against 21\n- Schema \u0026 documentation, 80 against 59\n- Agent ergonomics, 80 against 63\n- Security \u0026 auth, 57 against 35\n- Payments \u0026 pricing, 60 against 27\n- Maintenance \u0026 community, 83 against 60\n- Transparency \u0026 trust, 62 against 54\n\nAlso in its favour:\n- No key needed to call it\n- Runs on your own machine\n- Open source\n\nWatch for: Base checkpoints score 0.362 and 0.352 on the maintainers' typed-decisions benchmark against a 0.318 random baseline, so it needs fine-tuning\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\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\n## Score by category\n\n| Category | Weight | Laya | Liquid d1 | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 65 | 21 | Laya +44 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 80 | 59 | Laya +21 |\n| Agent ergonomics | 13% (16.2 this run) | 80 | 63 | Laya +17 |\n| Security \u0026 auth | 14% (17.5 this run) | 57 | 35 | Laya +22 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 27 | Laya +33 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 60 | Laya +23 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 62 | 54 | Laya +8 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **69.2 · B** | **43.5 · E** | |\n\n## Facts side by side\n\n| Fact | Laya | Liquid d1 |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Convai Innovations | Liquid AI |\n| Hosted endpoint | no (local only) | `https://api.liquid.ai/decisions/v1/systemone` |\n| Transports | HTTP, stdio | HTTP |\n| Auth | None | API key |\n| Pricing | Free | Freemium |\n| x402 | no | no |\n| Licence | Apache-2.0 | 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 |\n| Tools exposed | 8 | none |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-01 | 2026-10-07 |\n| Terms last updated | no document linked | 2026-09-30 |\n| Privacy policy last updated | no document linked | 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 | 29k stars | none |\n| Agent reviews | 2.5/5 (2) | none |\n\n## Verdicts\n\n**Laya.** Apache-2.0 code and weights, installed with `pip install laya`, with Python 3.10 to 3.13 tested in CI. Base checkpoints score 0.362 and 0.352 on the maintainers' typed-decisions benchmark against a 0.318 random baseline, so it needs fine-tuning.\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## Before you call either\n\n### Laya\n\n1. Set `LAYA_API_KEY` before starting `laya-serve`. It listens on every interface by default\n2. Gate on `answer_confidence`, not `confidence`, which measures entropy and doesn't match Jev's field\n3. Shortlist choice questions with more than about 20 options using `predict_shortlist` or the `laya_shortlist` tool\n4. Use semantic or opaque labels such as `A` and `B`, not `yes` and `no`, in choice questions. The checkpoints can follow the label text\n5. Pass `model=\"multilingual\"` and `max_len=8192` for long documents. The English checkpoint stops at 512 tokens\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## Questions\n\n### Which is better for AI agents, Laya or Liquid d1?\n\nLaya scores 69.2 (B) on agent readiness against Liquid d1's 43.5 (E), and leads in every scored category.\n\n### Do Laya and Liquid d1 need an API key?\n\nLaya needs no key. Liquid d1 needs an API key.\n\n### Can an agent call Laya and Liquid d1 without installing anything?\n\nLaya runs on your own machine, with no hosted endpoint listed. Liquid d1 has a hosted endpoint at https://api.liquid.ai/decisions/v1/systemone.\n\n### Are Laya and Liquid d1 open source?\n\nLaya is open source (Apache-2.0). No open-source release is listed for Liquid d1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/convai-laya-vs-liquid-d1.json, and with the fewest tokens: https://www.anchorterminal.com/compare/convai-laya-vs-liquid-d1.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"convai-laya\", \"b\": \"liquid-d1\"}`. From a terminal: `anchor compare convai-laya liquid-d1`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/convai-laya.json and https://www.anchorterminal.com/api/v1/tools/liquid-d1.json\n\n## Other comparisons with Laya or Liquid d1\n\n- [Clef vs Laya](https://www.anchorterminal.com/compare/cloudflare-clef-vs-convai-laya.md)\n- [Clef vs Liquid d1](https://www.anchorterminal.com/compare/cloudflare-clef-vs-liquid-d1.md)\n- [Laya vs Kev](https://www.anchorterminal.com/compare/convai-laya-vs-jaredpalmer-kev.md)\n- [Laya vs OpenAI Decisions API](https://www.anchorterminal.com/compare/convai-laya-vs-openai-decisions-api.md)\n- [Laya vs Strands Decider 2B](https://www.anchorterminal.com/compare/convai-laya-vs-strands-decider.md)\n- [Laya vs Jev](https://www.anchorterminal.com/compare/convai-laya-vs-typesafe-jev.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- [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- [Liquid d1 vs Vela 2.0](https://www.anchorterminal.com/compare/liquid-d1-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": "Laya vs Liquid d1", "url": "" } ], "description": "Laya scores 69.2 (B) on agent readiness against Liquid d1's 43.5 (E), and leads in every scored category. Both do inference decision. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "Laya B 69.2", "Liquid d1 E 43.5", "scores" ], "h1": "Laya vs Liquid d1", "image": "https://www.anchorterminal.com/assets/og/compare-convai-laya-vs-liquid-d1.png", "path": "/compare/convai-laya-vs-liquid-d1", "published": "2026-10-01", "section": "tools", "title": "Laya vs Liquid d1 for AI agents, B 69.2 vs E 43.5 | Anchor Terminal", "toc": null, "updated": "2026-10-08", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-liquid-d1" }, "tokens": { "markdown": 2150, "slim": 780 }, "version": 1 }