{ "data": { "a": { "slug": "jaredpalmer-kev", "name": "Kev", "vendor": "Jared Palmer", "vendorUrl": "https://github.com/jaredpalmer", "kind": "model", "category": "decision-models", "summary": "Kev is a family of four open-weight decision models by Jared Palmer, released together as Kev 1.0 on 1 October 2026 under Apache-2.0.", "url": "https://www.anchorterminal.com/tools/jaredpalmer-kev", "markdownUrl": "https://www.anchorterminal.com/tools/jaredpalmer-kev.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/jaredpalmer-kev.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/jaredpalmer-kev.json", "repo": "https://github.com/jaredpalmer/kev", "license": "Apache-2.0 (code, adapters and weights)", "transports": [ "http" ], "packages": [], "auth": "none", "authNotes": "No account. `kev.serve` binds to 127.0.0.1 and is open by default. Setting `KEV_API_KEY` makes it require `Authorization: Bearer \u003ckey\u003e` on `/v1/*`, which the TypeSafe clients always send. The weights download from Hugging Face without an account.", "pricing": "free", "pricingNotes": "Free and open source, with nothing to buy. You pay for the hardware. The Modal deploy skill lists $0.80 an hour for Kev-0.8B on an L4, $1.95 for Kev-4B on an L40S, $3.95 for Kev-9B on an H100 and $6.25 for Kev-27B on a B200 while a container is up, scaling to zero after five idle minutes (https://github.com/jaredpalmer/kev/blob/main/skills/kev-deploy/SKILL.md). Those are Modal's GPU rates as the skill records them, not a Kev price.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402. Kev is software you run, and its server has no payment route (checked 2026-10-02).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-02" }, "docsUrl": "https://github.com/jaredpalmer/kev#readme", "capabilities": [ "inference.decision" ], "tags": [ "model", "open-source", "open-weights", "self-hosted", "local", "free", "python" ], "lastRelease": "2026-10-01", "graded": true, "anchor": { "graded": true, "score": 67.4, "grade": "B", "agentReady": false, "rank": 270, "ranked": true, "rankOf": 1094, "categoryRank": 5, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 78, "maintenance": 83, "payments": 60, "reliability": 73, "schema": 77, "security": 49, "transparency": 49 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": 0, "verdict": "Apache-2.0 code, adapters and heads on Apache-2.0 Qwen bases, with release tarballs and SHA-256 checksums for the 0.8B, 4B and 9B models. No package. `pip install kev` installs an unrelated 2021 ORM, so Kev runs from a Git clone with uv.", "bestFor": "Self-hosted classification, routing, triage and rubric scoring where a probability matters, especially for teams already calling Jev who want the same API on their own hardware.", "strengths": [ "Apache-2.0 code, adapters and heads on Apache-2.0 Qwen bases, with release tarballs and SHA-256 checksums for the 0.8B, 4B and 9B models", "The same `/v1/systemone` request and answer shapes as Jev, and the README says TypeSafe's Python SDK works against it unchanged", "A fitted temperature per checkpoint, with Brier scores, calibration error and confident-error rates published for each model", "Runs on CUDA, ROCm and Apple Silicon, from a 4 GB GPU for Kev-0.8B to one 80 GB GPU for Kev-27B, and deploys to Modal with one command", "Release notes that list known failures with numbers, such as date arithmetic and Kev-0.8B's tool-routing accuracy" ], "weaknesses": [ "No package. `pip install kev` installs an unrelated 2021 ORM, so Kev runs from a Git clone with uv", "Kev-0.8B, 4B and 9B are validated to 8,192 tokens of state, though the server accepts 65,536", "Jared Palmer wrote 312 of the 333 commits we cloned", "No SECURITY.md, disclosure policy or advisories, and the server is open unless `KEV_API_KEY` is set", "Below 27B it trails Jev on knowledge questions and date arithmetic, with MMLU-Pro at 0.59 for Kev-9B against Jev's 0.84" ], "agentNotes": [ "Install from the repository. The `kev` package on PyPI is an unrelated project", "Pin a checkpoint with `@v1.0`, as in `jaredpalmer/kev-4b@v1.0`, so tuned thresholds keep their meaning", "Keep states under 8,192 tokens on Kev-0.8B, 4B and 9B, or use Kev-27B for long documents", "Set `KEV_DATE_FACTS=1` when a decision depends on the gap between two dates", "Expect a 422 naming the token count when a state passes 65,536 tokens. The server refuses it instead of cutting it" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 2, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 67.4 } ], "editorialScores": { "ergonomics": 78, "maintenance": 83, "payments": 60, "reliability": 73, "schema": 77, "security": 49, "transparency": 70 }, "provenanceScore": 27 }, "connect": { "install": "git clone https://github.com/jaredpalmer/kev.git \u0026\u0026 cd kev \u0026\u0026 uv sync --extra serve\nuv run --extra serve python -m kev.serve --run jaredpalmer/kev-4b@v1.0 --port 8009", "http": "curl -s localhost:8009/v1/systemone -H 'content-type: application/json' \\\n -d '{\"model\":\"kev-latest\",\"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\"}}}}'" }, "letme": { "capability": "https://letme.dev/inference.decision", "tool": "https://letme.dev/jaredpalmer-kev" }, "area": "models", "provenance": { "legalEntity": "", "domain": "github.com/jaredpalmer", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/jaredpalmer/kev/releases", "securityTxt": "none", "checked": "2026-10-01", "notes": [ "An individual's open-source project under Apache-2.0, with no company named in the licence, README or package metadata. The pyproject names Jared Palmer as author.", "No vendor domain. The code is at github.com/jaredpalmer/kev and the weights at huggingface.co/jaredpalmer, so the domain line names the GitHub account and scores no domain age.", "Software you run, so there's no hosted endpoint, terms or privacy policy to check.", "The changelog is the GitHub releases page (`kev-1.0`, 1 October 2026) and docs/releases/kev-1.0.md." ], "score": 27 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/jaredpalmer-kev.json", "live": { "slug": "jaredpalmer-kev", "versions": [ { "registry": "github", "name": "jaredpalmer/kev", "version": "kev-1.0", "released": "2026-10-01", "seenAt": "2026-10-14T23:59:18.029041397Z" } ], "githubStars": 9128, "domain": { "domain": "github.com/jaredpalmer", "checkedAt": "2026-10-11T13:20:17.496325718Z" }, "updatedAt": "2026-10-14T23:59:18.029041397Z" } }, "answer": "Kev scores 67.4 (B) on agent readiness against SPEV's 51.1 (D), and leads in 5 of 7 scored categories. SPEV leads on transparency \u0026 trust.", "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": "Jared Palmer", "b": "Sprag", "name": "Vendor" }, { "a": "no (local only)", "b": "https://api.sprag.ai/v1/decisions", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "API key", "name": "Auth" }, { "a": "Free", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0 (code, adapters and weights)", "b": "Apache-2.0 (weights and inference code, following the Qwen3-Omni base). Training code and data aren't published", "name": "Licence" }, { "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": "3.5/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Kev scores 67.4 (B) on agent readiness against SPEV's 51.1 (D), and leads in 5 of 7 scored categories. SPEV leads on transparency \u0026 trust.", "question": "Which is better for AI agents, Kev or SPEV?" }, { "answer": "Kev needs no key. SPEV needs an API key.", "question": "Do Kev and SPEV need an API key?" }, { "answer": "No hosted endpoint is listed for Kev. SPEV has a hosted endpoint at https://api.sprag.ai/v1/decisions.", "question": "Can an agent call Kev and SPEV without installing anything?" }, { "answer": "Kev is open source (Apache-2.0 (code, adapters and weights)). No open-source release is listed for SPEV.", "question": "Are Kev and SPEV open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 73 against 45", "Security \u0026 auth, 49 against 33", "Payments \u0026 pricing, 60 against 30", "Maintenance \u0026 community, 83 against 49" ], "also": [ "No key needed to call it", "Open source" ], "goodFor": "Self-hosted classification, routing, triage and rubric scoring where a probability matters, especially for teams already calling Jev who want the same API on their own hardware.", "slug": "jaredpalmer-kev", "watchFor": "No package. `pip install kev` installs an unrelated 2021 ORM, so Kev runs from a Git clone with uv" }, { "aheadOn": [ "Transparency \u0026 trust, 54 against 49" ], "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-jaredpalmer-kev.json", "title": "Celeris-1 Decision vs Kev", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-jaredpalmer-kev" }, { "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-jaredpalmer-kev.json", "title": "Clef vs Kev", "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-jaredpalmer-kev" }, { "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-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-sprag-spev.json", "title": "Laya vs SPEV", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-sprag-spev" }, { "json": "https://www.anchorterminal.com/compare/decider-vs-jaredpalmer-kev.json", "title": "Decider vs Kev", "url": "https://www.anchorterminal.com/compare/decider-vs-jaredpalmer-kev" }, { "json": "https://www.anchorterminal.com/compare/decider-vs-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-jaredpalmer-kev.json", "title": "Decision 3.0 vs Kev", "url": "https://www.anchorterminal.com/compare/decision-3-vs-jaredpalmer-kev" }, { "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-jaredpalmer-kev.json", "title": "GLiClass vs Kev", "url": "https://www.anchorterminal.com/compare/gliclass-vs-jaredpalmer-kev" }, { "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-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-microsoft-decision-1.json", "title": "Kev vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-microsoft-decision-1" }, { "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-nace-drex.json", "title": "Kev vs Drex 1.5", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-nace-drex" }, { "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-openai-decisions-api.json", "title": "Kev vs OpenAI Decisions API", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-openai-decisions-api" }, { "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-pplx-decider.json", "title": "Kev vs pplx-decider", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-pplx-decider" }, { "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-scaledown.json", "title": "Kev vs ScaleDown", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-scaledown" }, { "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-strands-decider.json", "title": "Kev vs Strands Decider 2B", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-strands-decider" }, { "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-typesafe-jev.json", "title": "Kev vs Jev", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-typesafe-jev" }, { "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-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": 28, "edge": "jaredpalmer-kev", "jaredpalmer-kev": 73, "key": "reliability", "name": "Reliability", "sprag-spev": 45, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 4, "edge": "sprag-spev", "jaredpalmer-kev": 77, "key": "schema", "name": "Schema \u0026 documentation", "sprag-spev": 81, "weight": 13 }, { "by": 2, "edge": "jaredpalmer-kev", "jaredpalmer-kev": 78, "key": "ergonomics", "name": "Agent ergonomics", "sprag-spev": 76, "weight": 13 }, { "by": 16, "edge": "jaredpalmer-kev", "jaredpalmer-kev": 49, "key": "security", "name": "Security \u0026 auth", "sprag-spev": 33, "weight": 14 }, { "by": 30, "edge": "jaredpalmer-kev", "jaredpalmer-kev": 60, "key": "payments", "name": "Payments \u0026 pricing", "sprag-spev": 30, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 34, "edge": "jaredpalmer-kev", "jaredpalmer-kev": 83, "key": "maintenance", "name": "Maintenance \u0026 community", "sprag-spev": 49, "weight": 7 }, { "by": 5, "edge": "sprag-spev", "jaredpalmer-kev": 49, "key": "transparency", "name": "Transparency \u0026 trust", "sprag-spev": 54, "weight": 7 } ], "summary": "Kev scores 67.4 (B) on agent readiness against SPEV's 51.1 (D), and leads in 5 of 7 scored categories. SPEV leads on transparency \u0026 trust. Both do decision models.", "verdicts": { "jaredpalmer-kev": "Apache-2.0 code, adapters and heads on Apache-2.0 Qwen bases, with release tarballs and SHA-256 checksums for the 0.8B, 4B and 9B models. No package. `pip install kev` installs an unrelated 2021 ORM, so Kev runs from a Git clone with uv.", "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/jaredpalmer-kev-vs-sprag-spev", "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-sprag-spev.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-sprag-spev.md", "slim": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-sprag-spev.min.md" }, "markdown": "Kev scores 67.4 (B) on agent readiness against SPEV's 51.1 (D), and leads in 5 of 7 scored categories. SPEV leads on transparency \u0026 trust. Both do decision models.\n\n- Kev: grade B, 67.4/100, rank #270 of 1094. Markdown https://www.anchorterminal.com/tools/jaredpalmer-kev.md · JSON https://www.anchorterminal.com/api/v1/tools/jaredpalmer-kev.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### Kev (B)\n\nGood for: Self-hosted classification, routing, triage and rubric scoring where a probability matters, especially for teams already calling Jev who want the same API on their own hardware.\n\nAhead on:\n- Reliability, 73 against 45\n- Security \u0026 auth, 49 against 33\n- Payments \u0026 pricing, 60 against 30\n- Maintenance \u0026 community, 83 against 49\n\nAlso in its favour:\n- No key needed to call it\n- Open source\n\nWatch for: No package. `pip install kev` installs an unrelated 2021 ORM, so Kev runs from a Git clone with uv\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\nAhead on:\n- Transparency \u0026 trust, 54 against 49\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 | Kev | SPEV | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 73 | 45 | Kev +28 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 77 | 81 | SPEV +4 |\n| Agent ergonomics | 13% (16.2 this run) | 78 | 76 | Kev +2 |\n| Security \u0026 auth | 14% (17.5 this run) | 49 | 33 | Kev +16 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 30 | Kev +30 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 49 | Kev +34 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 49 | 54 | SPEV +5 |\n| Negative events | ≤15 | 0 | -2 | |\n| **Total** | | **67.4 · B** | **51.1 · D** | |\n\n## Facts side by side\n\n| Fact | Kev | SPEV |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Jared Palmer | Sprag |\n| Hosted endpoint | no (local only) | `https://api.sprag.ai/v1/decisions` |\n| Transports | HTTP | HTTP |\n| Auth | None | API key |\n| Pricing | Free | Pay per use |\n| x402 | no | no |\n| Licence | Apache-2.0 (code, adapters and weights) | Apache-2.0 (weights and inference code, following the Qwen3-Omni base). Training code and data aren't published |\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| Agent reviews | 3.5/5 (2) | none |\n\n## Verdicts\n\n**Kev.** Apache-2.0 code, adapters and heads on Apache-2.0 Qwen bases, with release tarballs and SHA-256 checksums for the 0.8B, 4B and 9B models. No package. `pip install kev` installs an unrelated 2021 ORM, so Kev runs from a Git clone with uv.\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### Kev\n\n1. Install from the repository. The `kev` package on PyPI is an unrelated project\n2. Pin a checkpoint with `@v1.0`, as in `jaredpalmer/kev-4b@v1.0`, so tuned thresholds keep their meaning\n3. Keep states under 8,192 tokens on Kev-0.8B, 4B and 9B, or use Kev-27B for long documents\n4. Set `KEV_DATE_FACTS=1` when a decision depends on the gap between two dates\n5. Expect a 422 naming the token count when a state passes 65,536 tokens. The server refuses it instead of cutting it\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, Kev or SPEV?\n\nKev scores 67.4 (B) on agent readiness against SPEV's 51.1 (D), and leads in 5 of 7 scored categories. SPEV leads on transparency \u0026 trust.\n\n### Do Kev and SPEV need an API key?\n\nKev needs no key. SPEV needs an API key.\n\n### Can an agent call Kev and SPEV without installing anything?\n\nNo hosted endpoint is listed for Kev. SPEV has a hosted endpoint at https://api.sprag.ai/v1/decisions.\n\n### Are Kev and SPEV open source?\n\nKev is open source (Apache-2.0 (code, adapters and weights)). No open-source release is listed for SPEV.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-sprag-spev.json, and with the fewest tokens: https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-sprag-spev.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"jaredpalmer-kev\", \"b\": \"sprag-spev\"}`. From a terminal: `anchor compare jaredpalmer-kev sprag-spev`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/jaredpalmer-kev.json and https://www.anchorterminal.com/api/v1/tools/sprag-spev.json\n\n## Other comparisons with Kev or SPEV\n\n- [Celeris-1 Decision vs Kev](https://www.anchorterminal.com/compare/celeris-1-decision-vs-jaredpalmer-kev.md)\n- [Celeris-1 Decision vs SPEV](https://www.anchorterminal.com/compare/celeris-1-decision-vs-sprag-spev.md)\n- [Clef vs Kev](https://www.anchorterminal.com/compare/cloudflare-clef-vs-jaredpalmer-kev.md)\n- [Clef vs SPEV](https://www.anchorterminal.com/compare/cloudflare-clef-vs-sprag-spev.md)\n- [Laya vs Kev](https://www.anchorterminal.com/compare/convai-laya-vs-jaredpalmer-kev.md)\n- [Laya vs SPEV](https://www.anchorterminal.com/compare/convai-laya-vs-sprag-spev.md)\n- [Decider vs Kev](https://www.anchorterminal.com/compare/decider-vs-jaredpalmer-kev.md)\n- [Decider vs SPEV](https://www.anchorterminal.com/compare/decider-vs-sprag-spev.md)\n- [Decision 3.0 vs Kev](https://www.anchorterminal.com/compare/decision-3-vs-jaredpalmer-kev.md)\n- [Decision 3.0 vs SPEV](https://www.anchorterminal.com/compare/decision-3-vs-sprag-spev.md)\n- [GLiClass vs Kev](https://www.anchorterminal.com/compare/gliclass-vs-jaredpalmer-kev.md)\n- [GLiClass vs SPEV](https://www.anchorterminal.com/compare/gliclass-vs-sprag-spev.md)\n- [Kev vs Liquid d1](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-liquid-d1.md)\n- [Kev vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-microsoft-decision-1.md)\n- [Kev vs Drex 1.5](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-nace-drex.md)\n- [Kev vs OpenAI Decisions API](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-openai-decisions-api.md)\n- [Kev vs pplx-decider](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-pplx-decider.md)\n- [Kev vs ScaleDown](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-scaledown.md)\n- [Kev vs Strands Decider 2B](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-strands-decider.md)\n- [Kev vs Jev](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-typesafe-jev.md)\n- [Kev vs Vela 2.0](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-vela.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": "Kev vs SPEV", "url": "" } ], "description": "Kev scores 67.4 (B) to SPEV's 51.1 (D) for decision models. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Kev B 67.4", "SPEV D 51.1", "scores" ], "h1": "Kev vs SPEV", "image": "https://www.anchorterminal.com/assets/og/compare-jaredpalmer-kev-vs-sprag-spev.png", "path": "/compare/jaredpalmer-kev-vs-sprag-spev", "published": "2026-10-01", "section": "tools", "title": "Kev vs SPEV for AI agents in 2026: scores and prices | Anchor Terminal", "toc": null, "updated": "2026-10-15", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-sprag-spev" }, "tokens": { "markdown": 2500, "slim": 680 }, "version": 1 }