{ "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": 697, "ranked": true, "rankOf": 842, "categoryRank": 9, "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" }, "answer": "GLiClass scores 49.9 (D) on agent readiness against Liquid d1's 43.5 (E), and leads in 4 of 7 scored categories. Liquid d1 leads on schema \u0026 documentation and maintenance \u0026 community.", "b": { "slug": "liquid-d1", "name": "Liquid d1", "vendor": "Liquid AI", "vendorUrl": "https://www.liquid.ai", "kind": "model", "category": "decision-models", "summary": "d1 is Liquid AI's decision model family. It answers typed yes or no, choice and score questions about text and images with probabilities, through a hosted API and the open-weight d1-3B and d1-omni-600M models.", "url": "https://www.anchorterminal.com/tools/liquid-d1", "markdownUrl": "https://www.anchorterminal.com/tools/liquid-d1.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/liquid-d1.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/liquid-d1.json", "repo": "https://huggingface.co/LiquidAI/d1-3B", "license": "The hosted d1 model is proprietary under Liquid AI's terms of service. The d1-3B and d1-omni-600M weights and model code are under the LFM Open Licence v1.0, which is based on Apache-2.0 and conditions commercial use on annual revenue under $10 million. Training code and data aren't published", "transports": [ "http" ], "remoteUrl": "https://api.liquid.ai/decisions/v1/systemone", "packages": [], "auth": "api-key", "authNotes": "A key created at console.liquid.ai under Dashboard, API Keys, after registering and joining an organisation, sent as a Bearer header. Keys start with `liquid_`. No scopes, expiry or rotation were found in the reviewed documentation. The weights download from Hugging Face without an account.", "pricing": "freemium", "pricingNotes": "The hosted `d1` model costs $0.04 per million input tokens and bills no output tokens, per the launch post of 5 October 2026 (https://www.liquid.ai/blog/d1-decision-model). Each question is billed as its own prompt, and an image counts 1.5 tokens per 32 by 32 pixel patch. A text-only `d1:free` model exists, with no published limits. Liquid's pricing page covers model licensing only. The open weights are free to run, and commercial use is free below $10 million in annual revenue.", "priceSummary": "Freemium", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the d1 docs, the launch posts or the terms of service (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-08" }, "docsUrl": "https://docs.liquid.ai/lfm/models/decision-models", "llmsTxt": "https://docs.liquid.ai/llms.txt", "capabilities": [ "inference.decision" ], "tags": [ "hosted", "model", "open-weights", "source-available", "self-hosted", "llms-txt", "free-tier", "usage-priced" ], "lastRelease": "2026-10-07", "graded": true, "anchor": { "graded": true, "score": 43.5, "grade": "E", "agentReady": false, "rank": 784, "ranked": true, "rankOf": 842, "categoryRank": 11, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 63, "maintenance": 60, "payments": 27, "reliability": 21, "schema": 59, "security": 35, "transparency": 54 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "The hosted API costs $0.04 per million input tokens and takes TypeSafe's System One request, and the d1-3B weights run locally through Transformers or llama.cpp. Liquid's terms allow it to train on API content, and no status page, rate limits or error reference were found. The family launched between 22 September and 7 October 2026.", "bestFor": "Classification, routing, yes or no gates and rubric scoring over text and images at a low per-token price, or on your own hardware with d1-3B where data can't leave.", "strengths": [ "$0.04 per million input tokens with no output tokens billed, per the launch post, and a text-only `d1:free` model", "d1-3B (3.12B parameters, 32,768-token context) and d1-omni-600M are ungated on Hugging Face, with GGUF builds", "llama.cpp's server README documents `/v1/systemone` for d1, so the same request runs locally", "The hosted `d1` model accepts up to 8 images a request as Base64 data", "Docs are served as Markdown with an llms.txt index, and say when to use a language model instead" ], "weaknesses": [ "The terms of 30 September 2026 allow Liquid to train on API content, with no opt-out or zero-retention option found", "No status page, rate limits, SLA or error reference found for the hosted API", "The LFM Open Licence v1.0 ends free commercial use at $10 million in annual revenue, so the weights aren't open source", "No OpenAPI file, API changelog or versioned model IDs. The hosted models are `d1` and `d1:free`", "No SDK of its own. TypeSafe's SDKs are the documented clients and don't send images" ], "agentNotes": [ "POST to https://api.liquid.ai/decisions/v1/systemone with a `liquid_` key as a Bearer header. This is not a chat-completions endpoint", "Use `d1` for images. `d1:free` is text-only and answers that it does not accept images", "Send images as Base64 data URLs in `images`, at most 8, with the whole JSON body under 4.5 MB. Remote image URLs are refused", "Budget tokens per question. Each question is billed as its own prompt, with its text and every image counted again", "Don't send confidential content to the hosted API, since the terms allow training on it. Run d1-3B locally for that data" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "E", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 43.5 } ], "editorialScores": { "ergonomics": 63, "maintenance": 60, "payments": 27, "reliability": 21, "schema": 59, "security": 35, "transparency": 46 }, "provenanceScore": 62 }, "connect": { "install": "pip install typesafe-sdk # or: npm install @typesafe-ai/sdk", "http": "curl -s https://api.liquid.ai/decisions/v1/systemone \\\n -H \"Authorization: Bearer $LIQUID_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"d1\",\"state\":\"I have been waiting over three weeks for my order and nobody has responded to my emails.\",\"questions\":{\"is_complaint\":{\"type\":\"noul\",\"instructions\":\"Is this message a complaint from the customer?\"}}}'" }, "letme": { "capability": "https://letme.dev/inference.decision", "tool": "https://letme.dev/liquid-d1" }, "area": "models", "unitPrices": [ { "item": "d1 input", "unit": "1m-tokens", "usd": 0.04, "note": "No output tokens. Each question is billed as its own prompt, images at 1.5 tokens per 32 by 32 pixel patch" } ], "provenance": { "legalEntity": "Liquid AI, Inc.", "domain": "liquid.ai", "domainRegistered": "2017-12-16", "endpointOnVendorDomain": true, "terms": "https://www.liquid.ai/terms-conditions", "privacy": "https://www.liquid.ai/privacy-policy", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-08", "notes": [ "The terms of service (updated 30 September 2026) name Liquid AI, Inc., a Delaware corporation, and Massachusetts law. The privacy policy carries the same date.", "RDAP gives liquid.ai a registration date of 16 December 2017 and a transfer on 20 April 2023. The site footer says the company was established in 2023.", "The hosted endpoint is on api.liquid.ai. The weights sit on huggingface.co under the LiquidAI organisation.", "/.well-known/security.txt returned 404 on www.liquid.ai, liquid.ai and api.liquid.ai.", "No status page is linked from the site, the docs or the launch posts, and status.liquid.ai did not answer our reader. No changelog for the API or the docs was found. docs.liquid.ai/changelog returned 404.", "A trust centre at trust.liquid.ai is hosted by Vanta and renders only with JavaScript, so its contents are unread." ], "score": 62 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/liquid-d1.json", "live": { "slug": "liquid-d1", "probe": { "target": "https://api.liquid.ai/decisions/v1/systemone", "method": "get", "lastAt": "2026-10-09T11:46:32.681112093Z", "lastOk": true, "lastStatus": 404, "lastMs": 221, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 152, "p95ms24h": 287, "samples24h": 218, "samples30d": 218, "days": [ { "date": "2026-10-08", "probes": 93, "ok": 93 }, { "date": "2026-10-09", "probes": 125, "ok": 125 } ] }, "securityTxt": { "url": "https://liquid.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-08T15:39:08.129742302Z" }, "pages": [ { "url": "https://www.liquid.ai/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-08T18:28:45.318974429Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "42d9e4ba3a39" }, { "url": "https://www.liquid.ai/terms-conditions", "kind": "terms", "status": 200, "checkedAt": "2026-10-08T18:28:47.564454912Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "8fd8f3573ffc" } ], "updatedAt": "2026-10-09T11:46:32.681112093Z" } }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Knowledgator", "b": "Liquid AI", "name": "Vendor" }, { "a": "no (local only)", "b": "https://api.liquid.ai/decisions/v1/systemone", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "API key", "name": "Auth" }, { "a": "Free", "b": "Freemium", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0 (library and the model weights we checked)", "b": "The hosted d1 model is proprietary under Liquid AI's terms of service. The d1-3B and d1-omni-600M weights and model code are under the LFM Open Licence v1.0, which is based on Apache-2.0 and conditions commercial use on annual revenue under $10 million. Training code and data aren't published", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-07-21", "b": "2026-10-07", "name": "Last release" }, { "a": "no document linked", "b": "2026-09-30", "name": "Terms last updated" }, { "a": "no document linked", "b": "2026-09-30", "name": "Privacy policy last updated" }, { "a": "", "b": "yes", "name": "Customer content may train models" }, { "a": "", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "555 stars, 13k PyPI/wk", "b": "none", "name": "Popularity" } ], "faq": [ { "answer": "GLiClass scores 49.9 (D) on agent readiness against Liquid d1's 43.5 (E), and leads in 4 of 7 scored categories. Liquid d1 leads on schema \u0026 documentation and maintenance \u0026 community.", "question": "Which is better for AI agents, GLiClass or Liquid d1?" }, { "answer": "GLiClass needs no key. Liquid d1 needs an API key.", "question": "Do GLiClass and Liquid d1 need an API key?" }, { "answer": "No hosted endpoint is listed for GLiClass. Liquid d1 has a hosted endpoint at https://api.liquid.ai/decisions/v1/systemone.", "question": "Can an agent call GLiClass and Liquid d1 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 Liquid d1.", "question": "Are GLiClass and Liquid d1 open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 43 against 21", "Payments \u0026 pricing, 60 against 27", "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, 59 against 49", "Maintenance \u0026 community, 60 against 44" ], "also": [ "A hosted endpoint, with nothing to install" ], "goodFor": "Classification, routing, yes or no gates and rubric scoring over text and images at a low per-token price, or on your own hardware with d1-3B where data can't leave.", "slug": "liquid-d1", "watchFor": "The terms of 30 September 2026 allow Liquid to train on API content, with no opt-out or zero-retention option found" } ], "job": { "capability": "inference.decision", "name": "Inference decision" }, "others": [ { "json": "https://www.anchorterminal.com/compare/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-liquid-d1.json", "title": "Celeris-1 Decision vs Liquid d1", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-liquid-d1" }, { "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-liquid-d1.json", "title": "Clef vs Liquid d1", "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-liquid-d1" }, { "json": "https://www.anchorterminal.com/compare/convai-laya-vs-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-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/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-liquid-d1.json", "title": "Decider vs Liquid d1", "url": "https://www.anchorterminal.com/compare/decider-vs-liquid-d1" }, { "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-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-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-liquid-d1.json", "title": "Kev vs Liquid d1", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-liquid-d1" }, { "json": "https://www.anchorterminal.com/compare/liquid-d1-vs-openai-decisions-api.json", "title": "Liquid d1 vs OpenAI Decisions API", "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-openai-decisions-api" }, { "json": "https://www.anchorterminal.com/compare/liquid-d1-vs-strands-decider.json", "title": "Liquid d1 vs Strands Decider 2B", "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-strands-decider" }, { "json": "https://www.anchorterminal.com/compare/liquid-d1-vs-typesafe-jev.json", "title": "Liquid d1 vs Jev", "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-typesafe-jev" }, { "json": "https://www.anchorterminal.com/compare/liquid-d1-vs-vela.json", "title": "Liquid d1 vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-vela" } ], "scores": [ { "by": 22, "edge": "gliclass", "gliclass": 43, "key": "reliability", "liquid-d1": 21, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 10, "edge": "liquid-d1", "gliclass": 49, "key": "schema", "liquid-d1": 59, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 3, "edge": "liquid-d1", "gliclass": 60, "key": "ergonomics", "liquid-d1": 63, "name": "Agent ergonomics", "weight": 13 }, { "by": 3, "edge": "gliclass", "gliclass": 38, "key": "security", "liquid-d1": 35, "name": "Security \u0026 auth", "weight": 14 }, { "by": 33, "edge": "gliclass", "gliclass": 60, "key": "payments", "liquid-d1": 27, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 16, "edge": "liquid-d1", "gliclass": 44, "key": "maintenance", "liquid-d1": 60, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 10, "edge": "gliclass", "gliclass": 64, "key": "transparency", "liquid-d1": 54, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "GLiClass scores 49.9 (D) on agent readiness against Liquid d1's 43.5 (E), and leads in 4 of 7 scored categories. Liquid d1 leads on schema \u0026 documentation and maintenance \u0026 community. Both do inference decision.", "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.", "liquid-d1": "The hosted API costs $0.04 per million input tokens and takes TypeSafe's System One request, and the d1-3B weights run locally through Transformers or llama.cpp. Liquid's terms allow it to train on API content, and no status page, rate limits or error reference were found. The family launched between 22 September and 7 October 2026." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/gliclass-vs-liquid-d1", "json": "https://www.anchorterminal.com/compare/gliclass-vs-liquid-d1.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/gliclass-vs-liquid-d1.md", "slim": "https://www.anchorterminal.com/compare/gliclass-vs-liquid-d1.min.md" }, "markdown": "GLiClass scores 49.9 (D) on agent readiness against Liquid d1's 43.5 (E), and leads in 4 of 7 scored categories. Liquid d1 leads on schema \u0026 documentation and maintenance \u0026 community. Both do inference decision.\n\n- GLiClass: grade D, 49.9/100, rank #697 of 842. Markdown https://www.anchorterminal.com/tools/gliclass.md · JSON https://www.anchorterminal.com/api/v1/tools/gliclass.json\n- Liquid d1: grade E, 43.5/100, rank #784 of 842. Markdown https://www.anchorterminal.com/tools/liquid-d1.md · JSON https://www.anchorterminal.com/api/v1/tools/liquid-d1.json\n\n## Which one, for what\n\n### 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- Reliability, 43 against 21\n- Payments \u0026 pricing, 60 against 27\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### Liquid d1 (E)\n\nGood for: Classification, routing, yes or no gates and rubric scoring over text and images at a low per-token price, or on your own hardware with d1-3B where data can't leave.\n\nAhead on:\n- Schema \u0026 documentation, 59 against 49\n- Maintenance \u0026 community, 60 against 44\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: The terms of 30 September 2026 allow Liquid to train on API content, with no opt-out or zero-retention option found\n\n\n## Score by category\n\n| Category | Weight | GLiClass | Liquid d1 | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 43 | 21 | GLiClass +22 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 49 | 59 | Liquid d1 +10 |\n| Agent ergonomics | 13% (16.2 this run) | 60 | 63 | Liquid d1 +3 |\n| Security \u0026 auth | 14% (17.5 this run) | 38 | 35 | GLiClass +3 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 27 | GLiClass +33 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 44 | 60 | Liquid d1 +16 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 64 | 54 | GLiClass +10 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **49.9 · D** | **43.5 · E** | |\n\n## Facts side by side\n\n| Fact | GLiClass | Liquid d1 |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Knowledgator | Liquid AI |\n| Hosted endpoint | no (local only) | `https://api.liquid.ai/decisions/v1/systemone` |\n| Transports | HTTP | HTTP |\n| Auth | None | API key |\n| Pricing | Free | Freemium |\n| x402 | no | no |\n| Licence | Apache-2.0 (library and the model weights we checked) | The hosted d1 model is proprietary under Liquid AI's terms of service. The d1-3B and d1-omni-600M weights and model code are under the LFM Open Licence v1.0, which is based on Apache-2.0 and conditions commercial use on annual revenue under $10 million. Training code and data aren't published |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-07-21 | 2026-10-07 |\n| Terms last updated | no document linked | 2026-09-30 |\n| Privacy policy last updated | no document linked | 2026-09-30 |\n| Customer content may train models | | yes |\n| Terms restrict automated access | | not found in the text |\n| Terms restrict benchmarking | | not found in the text |\n| Terms or service can change without notice | | not found in the text |\n| Arbitration or class-action waiver | | not found in the text |\n| Popularity | 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**Liquid d1.** The hosted API costs $0.04 per million input tokens and takes TypeSafe's System One request, and the d1-3B weights run locally through Transformers or llama.cpp. Liquid's terms allow it to train on API content, and no status page, rate limits or error reference were found. The family launched between 22 September and 7 October 2026.\n\n## Before you call either\n\n### 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### Liquid d1\n\n1. POST to https://api.liquid.ai/decisions/v1/systemone with a `liquid_` key as a Bearer header. This is not a chat-completions endpoint\n2. Use `d1` for images. `d1:free` is text-only and answers that it does not accept images\n3. Send images as Base64 data URLs in `images`, at most 8, with the whole JSON body under 4.5 MB. Remote image URLs are refused\n4. Budget tokens per question. Each question is billed as its own prompt, with its text and every image counted again\n5. Don't send confidential content to the hosted API, since the terms allow training on it. Run d1-3B locally for that data\n\n## Questions\n\n### Which is better for AI agents, GLiClass or Liquid d1?\n\nGLiClass scores 49.9 (D) on agent readiness against Liquid d1's 43.5 (E), and leads in 4 of 7 scored categories. Liquid d1 leads on schema \u0026 documentation and maintenance \u0026 community.\n\n### Do GLiClass and Liquid d1 need an API key?\n\nGLiClass needs no key. Liquid d1 needs an API key.\n\n### Can an agent call GLiClass and Liquid d1 without installing anything?\n\nNo hosted endpoint is listed for GLiClass. Liquid d1 has a hosted endpoint at https://api.liquid.ai/decisions/v1/systemone.\n\n### Are GLiClass and Liquid d1 open source?\n\nGLiClass is open source (Apache-2.0 (library and the model weights we checked)). No open-source release is listed for Liquid d1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/gliclass-vs-liquid-d1.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gliclass-vs-liquid-d1.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gliclass\", \"b\": \"liquid-d1\"}`. From a terminal: `anchor compare gliclass liquid-d1`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gliclass.json and https://www.anchorterminal.com/api/v1/tools/liquid-d1.json\n\n## Other comparisons with GLiClass or Liquid d1\n\n- [Celeris-1 Decision vs GLiClass](https://www.anchorterminal.com/compare/celeris-1-decision-vs-gliclass.md)\n- [Celeris-1 Decision vs Liquid d1](https://www.anchorterminal.com/compare/celeris-1-decision-vs-liquid-d1.md)\n- [Clef vs GLiClass](https://www.anchorterminal.com/compare/cloudflare-clef-vs-gliclass.md)\n- [Clef vs Liquid d1](https://www.anchorterminal.com/compare/cloudflare-clef-vs-liquid-d1.md)\n- [Laya vs GLiClass](https://www.anchorterminal.com/compare/convai-laya-vs-gliclass.md)\n- [Laya vs Liquid d1](https://www.anchorterminal.com/compare/convai-laya-vs-liquid-d1.md)\n- [Decider vs GLiClass](https://www.anchorterminal.com/compare/decider-vs-gliclass.md)\n- [Decider vs Liquid d1](https://www.anchorterminal.com/compare/decider-vs-liquid-d1.md)\n- [GLiClass vs Kev](https://www.anchorterminal.com/compare/gliclass-vs-jaredpalmer-kev.md)\n- [GLiClass vs OpenAI Decisions API](https://www.anchorterminal.com/compare/gliclass-vs-openai-decisions-api.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 Liquid d1](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-liquid-d1.md)\n- [Liquid d1 vs OpenAI Decisions API](https://www.anchorterminal.com/compare/liquid-d1-vs-openai-decisions-api.md)\n- [Liquid d1 vs Strands Decider 2B](https://www.anchorterminal.com/compare/liquid-d1-vs-strands-decider.md)\n- [Liquid d1 vs Jev](https://www.anchorterminal.com/compare/liquid-d1-vs-typesafe-jev.md)\n- [Liquid d1 vs Vela 2.0](https://www.anchorterminal.com/compare/liquid-d1-vs-vela.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-09", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "GLiClass vs Liquid d1", "url": "" } ], "description": "GLiClass scores 49.9 (D) on agent readiness against Liquid d1's 43.5 (E), and leads in 4 of 7 scored categories. Liquid d1 leads on schema \u0026 documentation and maintenance \u0026 community. Both do inference decision. Category scores, facts, verdicts and agent notes side by side.", "facts": [ "GLiClass D 49.9", "Liquid d1 E 43.5", "scores" ], "h1": "GLiClass vs Liquid d1", "image": "https://www.anchorterminal.com/assets/og/compare-gliclass-vs-liquid-d1.png", "path": "/compare/gliclass-vs-liquid-d1", "published": "2026-10-01", "section": "tools", "title": "GLiClass vs Liquid d1 for AI agents, D 49.9 vs E 43.5", "toc": null, "updated": "2026-10-09", "url": "https://www.anchorterminal.com/compare/gliclass-vs-liquid-d1" }, "tokens": { "markdown": 2350, "slim": 780 }, "version": 1 }