{ "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": 202, "ranked": true, "rankOf": 1094, "categoryRank": 4, "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": "v0.4.7", "released": "2026-10-14", "seenAt": "2026-10-14T23:46:28.704482505Z" }, { "registry": "pypi", "name": "laya", "version": "0.4.7", "released": "2026-10-14", "seenAt": "2026-10-14T23:46:28.583585119Z" } ], "githubStars": 32909, "pypiWeekly": 69748, "securityTxt": { "url": "https://convaiinnovations.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-14T15:47:37.965882998Z" }, "domain": { "domain": "convaiinnovations.com", "registered": "2021-09-01", "source": "https://rdap.verisign.com/com/v1/domain/convaiinnovations.com", "checkedAt": "2026-10-11T13:22:10.228622332Z" }, "updatedAt": "2026-10-14T23:46:28.704482505Z" } }, "answer": "Laya scores 69.2 (B) on agent readiness against SPEV's 51.1 (D), and leads in 6 of 7 scored categories.", "b": { "slug": "sprag-spev", "name": "SPEV", "vendor": "Sprag", "vendorUrl": "https://sprag.ai", "kind": "model", "category": "decision-models", "summary": "SPEV is Sprag's open-weight decision model, released on 14 October 2026. It answers predicate, choice and score questions about text, audio or an image with a probability for each answer, through Sprag's hosted API or Apache-2.0 weights.", "url": "https://www.anchorterminal.com/tools/sprag-spev", "markdownUrl": "https://www.anchorterminal.com/tools/sprag-spev.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/sprag-spev.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/sprag-spev.json", "repo": "https://huggingface.co/SpragAI/SPEV", "license": "Apache-2.0 (weights and inference code, following the Qwen3-Omni base). Training code and data aren't published", "transports": [ "http" ], "remoteUrl": "https://api.sprag.ai/v1/decisions", "packages": [], "auth": "api-key", "authNotes": "A Sprag API key as a bearer token, generated in the web app after signing up and shown once. Rotating a key invalidates the old one at once. Keys carry no scopes, and every key in an organisation shares one rate limit. The weights download from Hugging Face without an account.", "pricing": "usage", "pricingNotes": "Hosted SPEV is free through 31 October 2026. The pricing page lists $0.09 per million input text or image tokens and $2.00 per million input audio tokens, with output unbilled. Audio counts one token per 100 ms. The docs list a 402 for an account with no payment method, and whether the free period needs a card wasn't established. The weights are free to run yourself.", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the Decisions docs, the OpenAPI document or the pricing page (checked 2026-10-15). Payment is through Stripe on the account.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-15" }, "docsUrl": "https://sprag.ai/docs/decisions", "llmsTxt": "https://sprag.ai/llms.txt", "openapi": "https://api.sprag.ai/openapi.json", "capabilities": [ "inference.decision" ], "tags": [ "hosted", "model", "open-weights", "llms-txt", "openapi", "usage-priced", "audio" ], "lastRelease": "2026-10-14", "graded": true, "anchor": { "graded": true, "score": 51.1, "grade": "D", "agentReady": false, "rank": 819, "ranked": true, "rankOf": 1094, "categoryRank": 12, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 76, "maintenance": 49, "payments": 30, "reliability": 45, "schema": 81, "security": 33, "transparency": 54 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-15" }, "negative": -2, "negativeNotes": [ "2026-10-14. The launch post's title and first line call SPEV 'the first open-weight omnimodal decision model' (https://sprag.ai/blog/spev-open-weight-omnimodal-decision-model.md). Cloudflare published Clef-omni on Hugging Face on 9 October 2026, Apache-2.0, on the same Qwen3-Omni-30B-A3B base, taking audio and video (https://huggingface.co/Cloudflare/clef-omni, checked 2026-10-15). The post also describes Clef as text or images only. A misleading claim, -2." ], "verdict": "SPEV answers typed questions over text, audio or an image in one call, with a public OpenAPI schema and Apache-2.0 weights on Hugging Face. It is a day old, has an 8,192-token context, no status page or changelog, and Sprag's terms let it train on API content unless the customer opts out by email.", "bestFor": "Typed decisions over raw audio, such as end-of-turn detection, call triage and flagging, plus text and single images, hosted or self-hosted.", "strengths": [ "Native audio evidence, so turn detection and call triage need no transcription step first", "Apache-2.0 weights and inference code on Hugging Face, ungated, with a pinned requirements file", "Public OpenAPI 3.1 contract with typed predicate, choice and score questions and up to 200 questions a call", "Hosted calls free through 31 October 2026, then $0.09 per million text or image tokens and $2.00 per million audio tokens, output unbilled", "One error envelope with `code` and `param`, documented rate limits and `Retry-After` on 429 and 503" ], "weaknesses": [ "Published on 14 October 2026, with no service record, no status page and no API changelog", "Sprag's terms license API content for model training by default. Opting out means emailing privacy@sprag.ai", "8,192-token context on the hosted model and in the weights' config", "No security.txt, disclosure policy or certification found, and API keys carry no scopes", "The launch post calls SPEV the first open-weight omnimodal decision model, five days after Cloudflare published Clef-omni" ], "agentNotes": [ "Send `model: \"spev\"` to `POST https://api.sprag.ai/v1/decisions` with a bearer key. `/v1/systemone` returns 410", "Ask every question about one piece of evidence in one request. Answers come back in question order", "Send audio as base64 in `input_audio` with `format`, not as a data URL, and at most one image across all messages", "Keep evidence and questions under 8,192 tokens. Over the limit returns 400 `model_limit_exceeded`", "Back off on 429 and 503 for `Retry-After` seconds. Limits are 60 requests a minute per organisation by default", "Handle an answer of type `refusal`, which carries no probabilities" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 51.1 } ], "editorialScores": { "ergonomics": 76, "maintenance": 49, "payments": 30, "reliability": 45, "schema": 81, "security": 33, "transparency": 57 }, "provenanceScore": 51 }, "connect": { "http": "curl https://api.sprag.ai/v1/decisions \\\n -H \"Content-Type: application/json\" -H \"Authorization: Bearer $SPRAG_API_KEY\" \\\n -d '{\"model\":\"spev\",\"input\":\"I was charged twice. Please refund the duplicate payment.\",\"questions\":[{\"name\":\"department\",\"type\":\"choice\",\"instructions\":\"Which team should handle this?\",\"choices\":[{\"value\":\"billing\"},{\"value\":\"technical\"}]},{\"name\":\"refund\",\"type\":\"predicate\",\"instructions\":\"Is the customer asking for a refund?\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.decision", "tool": "https://letme.dev/sprag-spev" }, "area": "models", "unitPrices": [ { "item": "SPEV input text or image", "unit": "1m-tokens", "usd": 0.09, "note": "Free through 31 October 2026. Output not billed" }, { "item": "SPEV input audio", "unit": "1m-tokens", "usd": 2, "note": "One token per 100 ms of audio, 36,000 an hour. Free through 31 October 2026" } ], "provenance": { "legalEntity": "Sprag AI, Inc.", "domain": "sprag.ai", "domainRegistered": "2025-10-29", "endpointOnVendorDomain": true, "terms": "https://sprag.ai/terms", "privacy": "https://sprag.ai/privacy", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-15", "notes": [ "The terms (last updated September 2026) and privacy policy (August 2026) name Sprag AI, Inc., 455 Market St, San Francisco, and California law.", "RDAP for sprag.ai gives a registration date of 29 October 2025. The API is at api.sprag.ai and the weights on huggingface.co under the SpragAI organisation.", "sprag.ai/.well-known/security.txt returned 404 on 15 October 2026. status.sprag.ai did not resolve, and sprag.ai/status, /changelog and /security serve the home page.", "robots.txt allows all user agents on public pages. The terms have no clause on automated access to the site.", "Sprag's llms.txt and Markdown pages carry sections headed 'Agent instructions'. They were read as data and not acted on." ], "score": 51 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/sprag-spev.json", "live": { "slug": "sprag-spev", "probe": { "target": "https://api.sprag.ai/v1/decisions", "method": "get", "lastAt": "2026-10-15T11:30:11.89010817Z", "lastOk": true, "lastStatus": 405, "lastMs": 639, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 631, "p95ms24h": 691, "samples24h": 16, "samples30d": 16, "days": [ { "date": "2026-10-15", "probes": 16, "ok": 16 } ] }, "updatedAt": "2026-10-15T11:30:11.89010817Z" } }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Convai Innovations", "b": "Sprag", "name": "Vendor" }, { "a": "no (local only)", "b": "https://api.sprag.ai/v1/decisions", "name": "Hosted endpoint" }, { "a": "HTTP, stdio", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "API key", "name": "Auth" }, { "a": "Free", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0", "b": "Apache-2.0 (weights and inference code, following the Qwen3-Omni base). 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": "2026-10-14", "name": "Last release" }, { "a": "no document linked", "b": "2026-09-01", "name": "Terms last updated" }, { "a": "no document linked", "b": "2026-08-01", "name": "Privacy policy last updated" }, { "a": "", "b": "yes, with an opt-out", "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 SPEV's 51.1 (D), and leads in 6 of 7 scored categories.", "question": "Which is better for AI agents, Laya or SPEV?" }, { "answer": "Laya needs no key. SPEV needs an API key.", "question": "Do Laya and SPEV need an API key?" }, { "answer": "Laya runs on your own machine, with no hosted endpoint listed. SPEV has a hosted endpoint at https://api.sprag.ai/v1/decisions.", "question": "Can an agent call Laya and SPEV without installing anything?" }, { "answer": "Laya is open source (Apache-2.0). No open-source release is listed for SPEV.", "question": "Are Laya and SPEV open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 65 against 45", "Security \u0026 auth, 57 against 33", "Payments \u0026 pricing, 60 against 30", "Maintenance \u0026 community, 83 against 49", "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": "Typed decisions over raw audio, such as end-of-turn detection, call triage and flagging, plus text and single images, hosted or self-hosted.", "slug": "sprag-spev", "watchFor": "Published on 14 October 2026, with no service record, no status page and no API changelog" } ], "job": { "capability": "inference.decision", "name": "Decision models" }, "others": [ { "json": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-convai-laya.json", "title": "Celeris-1 Decision vs Laya", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-convai-laya" }, { "json": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-sprag-spev.json", "title": "Celeris-1 Decision vs SPEV", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-sprag-spev" }, { "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-sprag-spev.json", "title": "Clef vs SPEV", "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-sprag-spev" }, { "json": "https://www.anchorterminal.com/compare/convai-laya-vs-decider.json", "title": "Laya vs Decider", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-decider" }, { "json": "https://www.anchorterminal.com/compare/convai-laya-vs-decision-3.json", "title": "Laya vs Decision 3.0", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-decision-3" }, { "json": "https://www.anchorterminal.com/compare/convai-laya-vs-gliclass.json", "title": "Laya vs GLiClass", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-gliclass" }, { "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-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-microsoft-decision-1.json", "title": "Laya vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-microsoft-decision-1" }, { "json": "https://www.anchorterminal.com/compare/convai-laya-vs-nace-drex.json", "title": "Laya vs Drex 1.5", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-nace-drex" }, { "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-pplx-decider.json", "title": "Laya vs pplx-decider", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-pplx-decider" }, { "json": "https://www.anchorterminal.com/compare/convai-laya-vs-scaledown.json", "title": "Laya vs ScaleDown", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-scaledown" }, { "json": "https://www.anchorterminal.com/compare/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/decider-vs-sprag-spev.json", "title": "Decider vs SPEV", "url": "https://www.anchorterminal.com/compare/decider-vs-sprag-spev" }, { "json": "https://www.anchorterminal.com/compare/decision-3-vs-sprag-spev.json", "title": "Decision 3.0 vs SPEV", "url": "https://www.anchorterminal.com/compare/decision-3-vs-sprag-spev" }, { "json": "https://www.anchorterminal.com/compare/gliclass-vs-sprag-spev.json", "title": "GLiClass vs SPEV", "url": "https://www.anchorterminal.com/compare/gliclass-vs-sprag-spev" }, { "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-sprag-spev.json", "title": "Kev vs SPEV", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-sprag-spev" }, { "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/microsoft-decision-1-vs-sprag-spev.json", "title": "Microsoft-Decision-1 vs SPEV", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-sprag-spev" }, { "json": "https://www.anchorterminal.com/compare/nace-drex-vs-sprag-spev.json", "title": "Drex 1.5 vs SPEV", "url": "https://www.anchorterminal.com/compare/nace-drex-vs-sprag-spev" }, { "json": "https://www.anchorterminal.com/compare/openai-decisions-api-vs-sprag-spev.json", "title": "OpenAI Decisions API vs SPEV", "url": "https://www.anchorterminal.com/compare/openai-decisions-api-vs-sprag-spev" }, { "json": "https://www.anchorterminal.com/compare/pplx-decider-vs-sprag-spev.json", "title": "pplx-decider vs SPEV", "url": "https://www.anchorterminal.com/compare/pplx-decider-vs-sprag-spev" }, { "json": "https://www.anchorterminal.com/compare/scaledown-vs-sprag-spev.json", "title": "ScaleDown vs SPEV", "url": "https://www.anchorterminal.com/compare/scaledown-vs-sprag-spev" }, { "json": "https://www.anchorterminal.com/compare/sprag-spev-vs-strands-decider.json", "title": "SPEV vs Strands Decider 2B", "url": "https://www.anchorterminal.com/compare/sprag-spev-vs-strands-decider" }, { "json": "https://www.anchorterminal.com/compare/sprag-spev-vs-typesafe-jev.json", "title": "SPEV vs Jev", "url": "https://www.anchorterminal.com/compare/sprag-spev-vs-typesafe-jev" }, { "json": "https://www.anchorterminal.com/compare/sprag-spev-vs-vela.json", "title": "SPEV vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/sprag-spev-vs-vela" } ], "scores": [ { "by": 20, "convai-laya": 65, "edge": "convai-laya", "key": "reliability", "name": "Reliability", "sprag-spev": 45, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 1, "convai-laya": 80, "edge": "sprag-spev", "key": "schema", "name": "Schema \u0026 documentation", "sprag-spev": 81, "weight": 13 }, { "by": 4, "convai-laya": 80, "edge": "convai-laya", "key": "ergonomics", "name": "Agent ergonomics", "sprag-spev": 76, "weight": 13 }, { "by": 24, "convai-laya": 57, "edge": "convai-laya", "key": "security", "name": "Security \u0026 auth", "sprag-spev": 33, "weight": 14 }, { "by": 30, "convai-laya": 60, "edge": "convai-laya", "key": "payments", "name": "Payments \u0026 pricing", "sprag-spev": 30, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 34, "convai-laya": 83, "edge": "convai-laya", "key": "maintenance", "name": "Maintenance \u0026 community", "sprag-spev": 49, "weight": 7 }, { "by": 8, "convai-laya": 62, "edge": "convai-laya", "key": "transparency", "name": "Transparency \u0026 trust", "sprag-spev": 54, "weight": 7 } ], "summary": "Laya scores 69.2 (B) on agent readiness against SPEV's 51.1 (D), and leads in 6 of 7 scored categories. Both do decision models.", "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.", "sprag-spev": "SPEV answers typed questions over text, audio or an image in one call, with a public OpenAPI schema and Apache-2.0 weights on Hugging Face. It is a day old, has an 8,192-token context, no status page or changelog, and Sprag's terms let it train on API content unless the customer opts out by email." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/convai-laya-vs-sprag-spev", "json": "https://www.anchorterminal.com/compare/convai-laya-vs-sprag-spev.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/convai-laya-vs-sprag-spev.md", "slim": "https://www.anchorterminal.com/compare/convai-laya-vs-sprag-spev.min.md" }, "markdown": "Laya scores 69.2 (B) on agent readiness against SPEV's 51.1 (D), and leads in 6 of 7 scored categories. Both do decision models.\n\n- Laya: grade B, 69.2/100, rank #202 of 1094. Markdown https://www.anchorterminal.com/tools/convai-laya.md · JSON https://www.anchorterminal.com/api/v1/tools/convai-laya.json\n- SPEV: grade D, 51.1/100, rank #819 of 1094. Markdown https://www.anchorterminal.com/tools/sprag-spev.md · JSON https://www.anchorterminal.com/api/v1/tools/sprag-spev.json\n- Best decision models for AI agents: https://www.anchorterminal.com/best/decision-models/index.md\n- All 136 decisions comparisons: https://www.anchorterminal.com/compare/decision-models/index.md\n\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 45\n- Security \u0026 auth, 57 against 33\n- Payments \u0026 pricing, 60 against 30\n- Maintenance \u0026 community, 83 against 49\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### SPEV (D)\n\nGood for: Typed decisions over raw audio, such as end-of-turn detection, call triage and flagging, plus text and single images, hosted or self-hosted.\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: Published on 14 October 2026, with no service record, no status page and no API changelog\n\n\n## Score by category\n\n| Category | Weight | Laya | SPEV | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 65 | 45 | Laya +20 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 80 | 81 | SPEV +1 |\n| Agent ergonomics | 13% (16.2 this run) | 80 | 76 | Laya +4 |\n| Security \u0026 auth | 14% (17.5 this run) | 57 | 33 | Laya +24 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 30 | Laya +30 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 49 | Laya +34 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 62 | 54 | Laya +8 |\n| Negative events | ≤15 | 0 | -2 | |\n| **Total** | | **69.2 · B** | **51.1 · D** | |\n\n## Facts side by side\n\n| Fact | Laya | SPEV |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Convai Innovations | Sprag |\n| Hosted endpoint | no (local only) | `https://api.sprag.ai/v1/decisions` |\n| Transports | HTTP, stdio | HTTP |\n| Auth | None | API key |\n| Pricing | Free | Pay per use |\n| x402 | no | no |\n| Licence | Apache-2.0 | Apache-2.0 (weights and inference code, following the Qwen3-Omni base). 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 | 2026-10-14 |\n| Terms last updated | no document linked | 2026-09-01 |\n| Privacy policy last updated | no document linked | 2026-08-01 |\n| Customer content may train models | | yes, with an opt-out |\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**SPEV.** SPEV answers typed questions over text, audio or an image in one call, with a public OpenAPI schema and Apache-2.0 weights on Hugging Face. It is a day old, has an 8,192-token context, no status page or changelog, and Sprag's terms let it train on API content unless the customer opts out by email.\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### SPEV\n\n1. Send `model: \"spev\"` to `POST https://api.sprag.ai/v1/decisions` with a bearer key. `/v1/systemone` returns 410\n2. Ask every question about one piece of evidence in one request. Answers come back in question order\n3. Send audio as base64 in `input_audio` with `format`, not as a data URL, and at most one image across all messages\n4. Keep evidence and questions under 8,192 tokens. Over the limit returns 400 `model_limit_exceeded`\n5. Back off on 429 and 503 for `Retry-After` seconds. Limits are 60 requests a minute per organisation by default\n6. Handle an answer of type `refusal`, which carries no probabilities\n\n## Questions\n\n### Which is better for AI agents, Laya or SPEV?\n\nLaya scores 69.2 (B) on agent readiness against SPEV's 51.1 (D), and leads in 6 of 7 scored categories.\n\n### Do Laya and SPEV need an API key?\n\nLaya needs no key. SPEV needs an API key.\n\n### Can an agent call Laya and SPEV without installing anything?\n\nLaya runs on your own machine, with no hosted endpoint listed. SPEV has a hosted endpoint at https://api.sprag.ai/v1/decisions.\n\n### Are Laya and SPEV open source?\n\nLaya is open source (Apache-2.0). No open-source release is listed for SPEV.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/convai-laya-vs-sprag-spev.json, and with the fewest tokens: https://www.anchorterminal.com/compare/convai-laya-vs-sprag-spev.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"convai-laya\", \"b\": \"sprag-spev\"}`. From a terminal: `anchor compare convai-laya sprag-spev`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/convai-laya.json and https://www.anchorterminal.com/api/v1/tools/sprag-spev.json\n\n## Other comparisons with Laya or SPEV\n\n- [Celeris-1 Decision vs Laya](https://www.anchorterminal.com/compare/celeris-1-decision-vs-convai-laya.md)\n- [Celeris-1 Decision vs SPEV](https://www.anchorterminal.com/compare/celeris-1-decision-vs-sprag-spev.md)\n- [Clef vs Laya](https://www.anchorterminal.com/compare/cloudflare-clef-vs-convai-laya.md)\n- [Clef vs SPEV](https://www.anchorterminal.com/compare/cloudflare-clef-vs-sprag-spev.md)\n- [Laya vs Decider](https://www.anchorterminal.com/compare/convai-laya-vs-decider.md)\n- [Laya vs Decision 3.0](https://www.anchorterminal.com/compare/convai-laya-vs-decision-3.md)\n- [Laya vs GLiClass](https://www.anchorterminal.com/compare/convai-laya-vs-gliclass.md)\n- [Laya vs Kev](https://www.anchorterminal.com/compare/convai-laya-vs-jaredpalmer-kev.md)\n- [Laya vs Liquid d1](https://www.anchorterminal.com/compare/convai-laya-vs-liquid-d1.md)\n- [Laya vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/convai-laya-vs-microsoft-decision-1.md)\n- [Laya vs Drex 1.5](https://www.anchorterminal.com/compare/convai-laya-vs-nace-drex.md)\n- [Laya vs OpenAI Decisions API](https://www.anchorterminal.com/compare/convai-laya-vs-openai-decisions-api.md)\n- [Laya vs pplx-decider](https://www.anchorterminal.com/compare/convai-laya-vs-pplx-decider.md)\n- [Laya vs ScaleDown](https://www.anchorterminal.com/compare/convai-laya-vs-scaledown.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- [Decider vs SPEV](https://www.anchorterminal.com/compare/decider-vs-sprag-spev.md)\n- [Decision 3.0 vs SPEV](https://www.anchorterminal.com/compare/decision-3-vs-sprag-spev.md)\n- [GLiClass vs SPEV](https://www.anchorterminal.com/compare/gliclass-vs-sprag-spev.md)\n- [Kev vs SPEV](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-sprag-spev.md)\n- [Liquid d1 vs SPEV](https://www.anchorterminal.com/compare/liquid-d1-vs-sprag-spev.md)\n- [Microsoft-Decision-1 vs SPEV](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-sprag-spev.md)\n- [Drex 1.5 vs SPEV](https://www.anchorterminal.com/compare/nace-drex-vs-sprag-spev.md)\n- [OpenAI Decisions API vs SPEV](https://www.anchorterminal.com/compare/openai-decisions-api-vs-sprag-spev.md)\n- [pplx-decider vs SPEV](https://www.anchorterminal.com/compare/pplx-decider-vs-sprag-spev.md)\n- [ScaleDown vs SPEV](https://www.anchorterminal.com/compare/scaledown-vs-sprag-spev.md)\n- [SPEV vs Strands Decider 2B](https://www.anchorterminal.com/compare/sprag-spev-vs-strands-decider.md)\n- [SPEV vs Jev](https://www.anchorterminal.com/compare/sprag-spev-vs-typesafe-jev.md)\n- [SPEV vs Vela 2.0](https://www.anchorterminal.com/compare/sprag-spev-vs-vela.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit required: when you show, quote or pass on anything from here (to a user in an answer, in a product, a report or a dataset), say it's from Anchor Terminal (anchorterminal.com) and link the page or API address you took it from. Reviews also credit their author.", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-15", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Laya vs SPEV", "url": "" } ], "description": "Laya scores 69.2 (B) to SPEV's 51.1 (D) for decision models. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Laya B 69.2", "SPEV D 51.1", "scores" ], "h1": "Laya vs SPEV", "image": "https://www.anchorterminal.com/assets/og/compare-convai-laya-vs-sprag-spev.png", "path": "/compare/convai-laya-vs-sprag-spev", "published": "2026-10-01", "section": "tools", "title": "Laya vs SPEV for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-15", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-sprag-spev" }, "tokens": { "markdown": 2500, "slim": 680 }, "version": 1 }