{ "data": { "a": { "slug": "gliclass", "name": "GLiClass", "vendor": "Knowledgator", "vendorUrl": "https://www.knowledgator.com", "kind": "model", "category": "decision-models", "summary": "GLiClass is an open-source Python library and family of open-weight zero-shot text classifiers from Knowledgator. It scores every candidate label in one forward pass and runs locally through a pipeline or a Ray Serve endpoint.", "url": "https://www.anchorterminal.com/tools/gliclass", "markdownUrl": "https://www.anchorterminal.com/tools/gliclass.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/gliclass.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/gliclass.json", "repo": "https://github.com/Knowledgator/GLiClass", "license": "Apache-2.0 (library and the model weights we checked)", "transports": [ "http" ], "packages": [ { "registry": "pypi", "name": "gliclass" } ], "auth": "none", "authNotes": "No account or key. The weights are public and ungated on Hugging Face. The bundled Ray Serve deployment has no authentication of any kind, and `python -m gliclass.serve` binds to 0.0.0.0 unless `--host` is passed, so the owner has to restrict the port.", "pricing": "free", "pricingNotes": "Free and open source, with nothing to buy for the library or the weights. Hardware is the owner's cost. Knowledgator's site links a hosted platform with plans at platform.knowledgator.com, which we couldn't reach on 8 October 2026, so whether it serves GLiClass and at what price is unchecked.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402. GLiClass is software the owner runs, and its server has no payment route (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 555, "npmWeekly": null, "pypiWeekly": 13204, "asOf": "2026-10-08" }, "docsUrl": "https://docs.knowledgator.com/docs/frameworks/gliclass/", "capabilities": [ "inference.decision" ], "tags": [ "model", "open-source", "open-weights", "self-hosted", "local", "free", "python", "no-auth" ], "lastRelease": "2026-07-21", "graded": true, "anchor": { "graded": true, "score": 49.9, "grade": "D", "agentReady": false, "rank": 848, "ranked": true, "rankOf": 1094, "categoryRank": 13, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 60, "maintenance": 44, "payments": 60, "reliability": 43, "schema": 49, "security": 38, "transparency": 64 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "An Apache-2.0 classifier that scores a whole label set in one encoder pass on the owner's hardware, with single-label, multi-label, hierarchical and few-shot modes. It returns label scores with no calibration claim, the bundled server has no authentication, and the last three test runs on the main branch, on 24 September 2026, failed.", "bestFor": "Topic, intent and sentiment routing over a known label set on the owner's own CPU or GPU, where many labels must be scored at once.", "strengths": [ "Apache-2.0 code and weights, with `train.py`, the training datasets named on the model cards and an arXiv paper (2508.07662)", "One forward pass scores every label. The base v3.0 card reports 51.6 examples a second averaged over 1 to 128 labels on an A6000 (vendor figures)", "Single-label (softmax) and multi-label (sigmoid) modes, hierarchical label sets, task prompts and few-shot examples in one pipeline call", "A Ray Serve deployment with dynamic batching ships in the `gliclass[serve]` extra, with a documented request table for `POST /gliclass`", "31 public, ungated GLiClass checkpoints on Hugging Face, from 32.7M to 439M parameters, as safetensors" ], "weaknesses": [ "No calibration evidence. The cards report F1 only, and the docs tell users to calibrate thresholds on their own traffic", "The bundled server has no authentication, and `python -m gliclass.serve` binds to 0.0.0.0 by default", "The last three runs of the Tests workflow on main, all on 24 September 2026, failed", "Still 0.1.x with no changelog file. 0.1.18 raised the `transformers` floor to 5.0, and issue #44 on v5 loading has been open since 6 July 2026", "No OpenAPI file, no llms.txt, no SECURITY.md and no documented error responses" ], "agentNotes": [ "Pass `--host 127.0.0.1` to `python -m gliclass.serve`, or put the port behind your own gateway. The server checks no credential", "On a machine without a GPU add `--device cpu --dtype float32 --num-gpus-per-replica 0`. The default configuration expects CUDA", "Send one text a request to `POST /gliclass`. An array in `texts` is cut to its first item without an error", "Set `multi_label` to false for one label from a set. The default scores each label independently, so scores do not sum to 1", "Keep text plus labels under the pipeline's 1,024-token `max_length`, or use `ZeroShotClassificationWithChunkingPipeline`. Longer input is truncated silently" ], "metrics": { "kind": "local", "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": 49.9 } ], "editorialScores": { "ergonomics": 60, "maintenance": 44, "payments": 60, "reliability": 43, "schema": 49, "security": 38, "transparency": 60 }, "provenanceScore": 68 }, "connect": { "install": "pip install gliclass", "http": "pip install \"gliclass[serve]\"\npython -m gliclass.serve --model knowledgator/gliclass-edge-v3.0 --port 8000\ncurl -X POST http://localhost:8000/gliclass \\\n -H \"Content-Type: application/json\" \\\n -d '{\"text\": \"This is a great product.\", \"labels\": [\"positive\", \"negative\", \"neutral\"], \"threshold\": 0.3, \"multi_label\": true}'" }, "letme": { "capability": "https://letme.dev/inference.decision", "tool": "https://letme.dev/gliclass" }, "area": "models", "provenance": { "legalEntity": "Knowledgator Engineering Ltd.", "domain": "knowledgator.com", "domainRegistered": "2021-06-25", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/Knowledgator/GLiClass/releases", "securityTxt": "none", "checked": "2026-10-08", "notes": [ "The terms of use and privacy policy linked from knowledgator.com name Knowledgator Engineering Ltd., London, United Kingdom. Both are dated 21 September 2023.", "Those two documents govern the website and Knowledgator's hosted services, not the library, so `terms` and `privacy` are left out. The Apache-2.0 licence governs what an agent would run.", "Software the owner runs, so there is no hosted endpoint and no status page for it.", "www.knowledgator.com/.well-known/security.txt returns 404, and the repository has no SECURITY.md.", "RDAP for knowledgator.com gives a registration date of 2021-06-25.", "The code is on github.com under the Knowledgator organisation and the weights on huggingface.co under knowledgator." ], "score": 68 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/gliclass.json", "live": { "slug": "gliclass", "versions": [ { "registry": "github", "name": "Knowledgator/GLiClass", "version": "v0.1.20", "released": "2026-07-21", "seenAt": "2026-10-14T23:54:33.912165118Z" }, { "registry": "pypi", "name": "gliclass", "version": "0.1.20", "released": "2026-07-21", "seenAt": "2026-10-14T23:54:33.720749948Z" } ], "githubStars": 559, "pypiWeekly": 11061, "securityTxt": { "url": "https://knowledgator.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-14T15:46:55.370320351Z" }, "domain": { "domain": "knowledgator.com", "registered": "2021-06-25", "source": "https://rdap.verisign.com/com/v1/domain/knowledgator.com", "checkedAt": "2026-10-11T13:24:38.717810411Z" }, "updatedAt": "2026-10-14T23:54:33.912165118Z" } }, "answer": "SPEV scores 51.1 (D) on agent readiness against GLiClass's 49.9 (D), and leads in 4 of 7 scored categories. GLiClass leads on security \u0026 auth, payments \u0026 pricing and 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": "Knowledgator", "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 (library and the model weights we checked)", "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": "2026-07-21", "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": "555 stars, 13k PyPI/wk", "b": "none", "name": "Popularity" } ], "faq": [ { "answer": "SPEV scores 51.1 (D) on agent readiness against GLiClass's 49.9 (D), and leads in 4 of 7 scored categories. GLiClass leads on security \u0026 auth, payments \u0026 pricing and transparency \u0026 trust.", "question": "Which is better for AI agents, GLiClass or SPEV?" }, { "answer": "GLiClass needs no key. SPEV needs an API key.", "question": "Do GLiClass and SPEV need an API key?" }, { "answer": "No hosted endpoint is listed for GLiClass. SPEV has a hosted endpoint at https://api.sprag.ai/v1/decisions.", "question": "Can an agent call GLiClass and SPEV without installing anything?" }, { "answer": "GLiClass is open source (Apache-2.0 (library and the model weights we checked)). No open-source release is listed for SPEV.", "question": "Are GLiClass and SPEV open source?" } ], "goodFor": [ { "aheadOn": [ "Security \u0026 auth, 38 against 33", "Payments \u0026 pricing, 60 against 30", "Transparency \u0026 trust, 64 against 54" ], "also": [ "No key needed to call it", "Open source" ], "goodFor": "Topic, intent and sentiment routing over a known label set on the owner's own CPU or GPU, where many labels must be scored at once.", "slug": "gliclass", "watchFor": "No calibration evidence. The cards report F1 only, and the docs tell users to calibrate thresholds on their own traffic" }, { "aheadOn": [ "Schema \u0026 documentation, 81 against 49", "Agent ergonomics, 76 against 60", "Maintenance \u0026 community, 49 against 44" ], "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-gliclass.json", "title": "Celeris-1 Decision vs GLiClass", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-gliclass" }, { "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-gliclass.json", "title": "Clef vs GLiClass", "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-gliclass" }, { "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-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-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-gliclass.json", "title": "Decider vs GLiClass", "url": "https://www.anchorterminal.com/compare/decider-vs-gliclass" }, { "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-gliclass.json", "title": "Decision 3.0 vs GLiClass", "url": "https://www.anchorterminal.com/compare/decision-3-vs-gliclass" }, { "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-liquid-d1.json", "title": "GLiClass vs Liquid d1", "url": "https://www.anchorterminal.com/compare/gliclass-vs-liquid-d1" }, { "json": "https://www.anchorterminal.com/compare/gliclass-vs-microsoft-decision-1.json", "title": "GLiClass vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/gliclass-vs-microsoft-decision-1" }, { "json": "https://www.anchorterminal.com/compare/gliclass-vs-nace-drex.json", "title": "GLiClass vs Drex 1.5", "url": "https://www.anchorterminal.com/compare/gliclass-vs-nace-drex" }, { "json": "https://www.anchorterminal.com/compare/gliclass-vs-openai-decisions-api.json", "title": "GLiClass vs OpenAI Decisions API", "url": "https://www.anchorterminal.com/compare/gliclass-vs-openai-decisions-api" }, { "json": "https://www.anchorterminal.com/compare/gliclass-vs-pplx-decider.json", "title": "GLiClass vs pplx-decider", "url": "https://www.anchorterminal.com/compare/gliclass-vs-pplx-decider" }, { "json": "https://www.anchorterminal.com/compare/gliclass-vs-scaledown.json", "title": "GLiClass vs ScaleDown", "url": "https://www.anchorterminal.com/compare/gliclass-vs-scaledown" }, { "json": "https://www.anchorterminal.com/compare/gliclass-vs-strands-decider.json", "title": "GLiClass vs Strands Decider 2B", "url": "https://www.anchorterminal.com/compare/gliclass-vs-strands-decider" }, { "json": "https://www.anchorterminal.com/compare/gliclass-vs-typesafe-jev.json", "title": "GLiClass vs Jev", "url": "https://www.anchorterminal.com/compare/gliclass-vs-typesafe-jev" }, { "json": "https://www.anchorterminal.com/compare/gliclass-vs-vela.json", "title": "GLiClass vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/gliclass-vs-vela" }, { "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": 2, "edge": "sprag-spev", "gliclass": 43, "key": "reliability", "name": "Reliability", "sprag-spev": 45, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 32, "edge": "sprag-spev", "gliclass": 49, "key": "schema", "name": "Schema \u0026 documentation", "sprag-spev": 81, "weight": 13 }, { "by": 16, "edge": "sprag-spev", "gliclass": 60, "key": "ergonomics", "name": "Agent ergonomics", "sprag-spev": 76, "weight": 13 }, { "by": 5, "edge": "gliclass", "gliclass": 38, "key": "security", "name": "Security \u0026 auth", "sprag-spev": 33, "weight": 14 }, { "by": 30, "edge": "gliclass", "gliclass": 60, "key": "payments", "name": "Payments \u0026 pricing", "sprag-spev": 30, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 5, "edge": "sprag-spev", "gliclass": 44, "key": "maintenance", "name": "Maintenance \u0026 community", "sprag-spev": 49, "weight": 7 }, { "by": 10, "edge": "gliclass", "gliclass": 64, "key": "transparency", "name": "Transparency \u0026 trust", "sprag-spev": 54, "weight": 7 } ], "summary": "SPEV scores 51.1 (D) on agent readiness against GLiClass's 49.9 (D), and leads in 4 of 7 scored categories. GLiClass leads on security \u0026 auth, payments \u0026 pricing and transparency \u0026 trust. Both do decision models.", "verdicts": { "gliclass": "An Apache-2.0 classifier that scores a whole label set in one encoder pass on the owner's hardware, with single-label, multi-label, hierarchical and few-shot modes. It returns label scores with no calibration claim, the bundled server has no authentication, and the last three test runs on the main branch, on 24 September 2026, failed.", "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/gliclass-vs-sprag-spev", "json": "https://www.anchorterminal.com/compare/gliclass-vs-sprag-spev.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/gliclass-vs-sprag-spev.md", "slim": "https://www.anchorterminal.com/compare/gliclass-vs-sprag-spev.min.md" }, "markdown": "SPEV scores 51.1 (D) on agent readiness against GLiClass's 49.9 (D), and leads in 4 of 7 scored categories. GLiClass leads on security \u0026 auth, payments \u0026 pricing and transparency \u0026 trust. Both do decision models.\n\n- GLiClass: grade D, 49.9/100, rank #848 of 1094. Markdown https://www.anchorterminal.com/tools/gliclass.md · JSON https://www.anchorterminal.com/api/v1/tools/gliclass.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### GLiClass (D)\n\nGood for: Topic, intent and sentiment routing over a known label set on the owner's own CPU or GPU, where many labels must be scored at once.\n\nAhead on:\n- Security \u0026 auth, 38 against 33\n- Payments \u0026 pricing, 60 against 30\n- Transparency \u0026 trust, 64 against 54\n\nAlso in its favour:\n- No key needed to call it\n- Open source\n\nWatch for: No calibration evidence. The cards report F1 only, and the docs tell users to calibrate thresholds on their own traffic\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- Schema \u0026 documentation, 81 against 49\n- Agent ergonomics, 76 against 60\n- Maintenance \u0026 community, 49 against 44\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 | GLiClass | SPEV | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 43 | 45 | SPEV +2 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 49 | 81 | SPEV +32 |\n| Agent ergonomics | 13% (16.2 this run) | 60 | 76 | SPEV +16 |\n| Security \u0026 auth | 14% (17.5 this run) | 38 | 33 | GLiClass +5 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 30 | GLiClass +30 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 44 | 49 | SPEV +5 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 64 | 54 | GLiClass +10 |\n| Negative events | ≤15 | 0 | -2 | |\n| **Total** | | **49.9 · D** | **51.1 · D** | |\n\n## Facts side by side\n\n| Fact | GLiClass | SPEV |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Knowledgator | 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 (library and the model weights we checked) | 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 | 2026-07-21 | 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 | 555 stars, 13k PyPI/wk | none |\n\n## Verdicts\n\n**GLiClass.** An Apache-2.0 classifier that scores a whole label set in one encoder pass on the owner's hardware, with single-label, multi-label, hierarchical and few-shot modes. It returns label scores with no calibration claim, the bundled server has no authentication, and the last three test runs on the main branch, on 24 September 2026, failed.\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### GLiClass\n\n1. Pass `--host 127.0.0.1` to `python -m gliclass.serve`, or put the port behind your own gateway. The server checks no credential\n2. On a machine without a GPU add `--device cpu --dtype float32 --num-gpus-per-replica 0`. The default configuration expects CUDA\n3. Send one text a request to `POST /gliclass`. An array in `texts` is cut to its first item without an error\n4. Set `multi_label` to false for one label from a set. The default scores each label independently, so scores do not sum to 1\n5. Keep text plus labels under the pipeline's 1,024-token `max_length`, or use `ZeroShotClassificationWithChunkingPipeline`. Longer input is truncated silently\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, GLiClass or SPEV?\n\nSPEV scores 51.1 (D) on agent readiness against GLiClass's 49.9 (D), and leads in 4 of 7 scored categories. GLiClass leads on security \u0026 auth, payments \u0026 pricing and transparency \u0026 trust.\n\n### Do GLiClass and SPEV need an API key?\n\nGLiClass needs no key. SPEV needs an API key.\n\n### Can an agent call GLiClass and SPEV without installing anything?\n\nNo hosted endpoint is listed for GLiClass. SPEV has a hosted endpoint at https://api.sprag.ai/v1/decisions.\n\n### Are GLiClass and SPEV open source?\n\nGLiClass is open source (Apache-2.0 (library and the model weights we checked)). No open-source release is listed for SPEV.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/gliclass-vs-sprag-spev.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gliclass-vs-sprag-spev.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gliclass\", \"b\": \"sprag-spev\"}`. From a terminal: `anchor compare gliclass sprag-spev`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gliclass.json and https://www.anchorterminal.com/api/v1/tools/sprag-spev.json\n\n## Other comparisons with GLiClass or SPEV\n\n- [Celeris-1 Decision vs GLiClass](https://www.anchorterminal.com/compare/celeris-1-decision-vs-gliclass.md)\n- [Celeris-1 Decision vs SPEV](https://www.anchorterminal.com/compare/celeris-1-decision-vs-sprag-spev.md)\n- [Clef vs GLiClass](https://www.anchorterminal.com/compare/cloudflare-clef-vs-gliclass.md)\n- [Clef vs SPEV](https://www.anchorterminal.com/compare/cloudflare-clef-vs-sprag-spev.md)\n- [Laya vs GLiClass](https://www.anchorterminal.com/compare/convai-laya-vs-gliclass.md)\n- [Laya vs SPEV](https://www.anchorterminal.com/compare/convai-laya-vs-sprag-spev.md)\n- [Decider vs GLiClass](https://www.anchorterminal.com/compare/decider-vs-gliclass.md)\n- [Decider vs SPEV](https://www.anchorterminal.com/compare/decider-vs-sprag-spev.md)\n- [Decision 3.0 vs GLiClass](https://www.anchorterminal.com/compare/decision-3-vs-gliclass.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 Liquid d1](https://www.anchorterminal.com/compare/gliclass-vs-liquid-d1.md)\n- [GLiClass vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/gliclass-vs-microsoft-decision-1.md)\n- [GLiClass vs Drex 1.5](https://www.anchorterminal.com/compare/gliclass-vs-nace-drex.md)\n- [GLiClass vs OpenAI Decisions API](https://www.anchorterminal.com/compare/gliclass-vs-openai-decisions-api.md)\n- [GLiClass vs pplx-decider](https://www.anchorterminal.com/compare/gliclass-vs-pplx-decider.md)\n- [GLiClass vs ScaleDown](https://www.anchorterminal.com/compare/gliclass-vs-scaledown.md)\n- [GLiClass vs Strands Decider 2B](https://www.anchorterminal.com/compare/gliclass-vs-strands-decider.md)\n- [GLiClass vs Jev](https://www.anchorterminal.com/compare/gliclass-vs-typesafe-jev.md)\n- [GLiClass vs Vela 2.0](https://www.anchorterminal.com/compare/gliclass-vs-vela.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": "GLiClass vs SPEV", "url": "" } ], "description": "SPEV scores 51.1 (D) to GLiClass's 49.9 (D) for decision models. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "GLiClass D 49.9", "SPEV D 51.1", "scores" ], "h1": "GLiClass vs SPEV", "image": "https://www.anchorterminal.com/assets/og/compare-gliclass-vs-sprag-spev.png", "path": "/compare/gliclass-vs-sprag-spev", "published": "2026-10-01", "section": "tools", "title": "GLiClass vs SPEV for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-15", "url": "https://www.anchorterminal.com/compare/gliclass-vs-sprag-spev" }, "tokens": { "markdown": 2600, "slim": 730 }, "version": 1 }