{ "data": { "a": { "slug": "celeris-1-decision", "name": "Celeris-1 Decision", "vendor": "Celeris (Marqo Inc)", "vendorUrl": "https://celeris.ai", "kind": "model", "category": "decision-models", "summary": "Celeris-1 Decision is a hosted multimodal diffusion model from Celeris, a Marqo Inc research lab. Its HTTP API answers typed questions about text, structured data and images with probabilities and optional explanations.", "url": "https://www.anchorterminal.com/tools/celeris-1-decision", "markdownUrl": "https://www.anchorterminal.com/tools/celeris-1-decision.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/celeris-1-decision.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/celeris-1-decision.json", "license": "Proprietary hosted model under Celeris terms of service", "transports": [ "http" ], "remoteUrl": "https://inference.celeris.ai/celeris-1-decision/v1/systemone", "packages": [], "auth": "api-key", "authNotes": "Bearer ck_ API key from an activated workspace. Signup, a payment method and prepaid credit are required. Keys can be created, rotated and revoked in the console; changes can take one minute. Keys share workspace credit, with no per-key limits. Activation is usually immediate but can queue when capacity is full.", "pricing": "usage", "pricingNotes": "$0.04 per million input tokens, including cached input, with output tokens free. Images and request overhead count as input. Card-funded purchases start at $5 and credit expires after 30 days. No card-free tier was found. Requests still processing after disconnection may be charged. Executed order forms can override self-service terms.", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 interface found in the reviewed pricing and API documentation on 9 October 2026. HTTP 402 means exhausted prepaid credit.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-09" }, "docsUrl": "https://docs.celeris.ai/decisions", "llmsTxt": "https://docs.celeris.ai/llms.txt", "capabilities": [ "inference.decision" ], "tags": [ "hosted", "model", "closed-source", "multimodal", "llms-txt", "usage-priced", "status-page", "beta" ], "lastRelease": "2026-10-08", "graded": true, "anchor": { "graded": true, "score": 49.3, "grade": "D", "agentReady": false, "rank": 708, "ranked": true, "rankOf": 842, "categoryRank": 10, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 80, "maintenance": 40, "payments": 20, "reliability": 40, "schema": 60, "security": 45, "transparency": 53 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-09" }, "negative": 0, "verdict": "Typed probabilities, image inputs and optional explanations suit routing and classification inside an agent. Both System One and OpenAI Decisions request formats are documented. The service remains early access under its terms, activation can queue, and prepaid credit expires after 30 days. The published accuracy and latency figures are Celeris measurements, not Anchor Terminal tests.", "bestFor": "Multimodal classification, routing and bounded decisions with probabilities and optional explanations", "strengths": [ "Typed binary, choice and score answers, with multiple questions about one state per request", "Text, JSON and images through System One, with optional explanations", "Decision inputs cost $0.04 per million tokens and outputs are free", "Markdown documentation, error recovery guidance and revocable workspace keys" ], "weaknesses": [ "Early-access terms and capacity-dependent workspace activation", "Prepaid credit expires after 30 days, with a $5 minimum card purchase", "No numeric request-rate guarantee or decision-model context window found", "No explicit API training exclusion or prompt-retention period found in the reviewed policies", "Closed weights and no fine-tuning in this release" ], "agentNotes": [ "Use the decision model path and matching model field. This model has no chat, Responses or models endpoint.", "Use at most 512 questions per request, or 64 with explanations. Both endpoints reject streaming.", "Preserve x_celeris in a custom Jev SDK response model when reading explanations. The default response type drops it.", "Retry 429 with Retry-After and backoff. Stop on 402 until workspace credit is replenished.", "Read usage.input_tokens for cost, including images and request overhead. Track credit expiry separately from token consumption." ], "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": 49.3 } ], "editorialScores": { "ergonomics": 80, "maintenance": 40, "payments": 20, "reliability": 40, "schema": 60, "security": 45, "transparency": 45 }, "provenanceScore": 61 }, "connect": { "http": "curl https://inference.celeris.ai/celeris-1-decision/v1/systemone \\\n -H \"Authorization: Bearer $CELERIS_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"celeris-1-decision\",\"state\":\"The customer requests a refund for a duplicate charge.\",\"questions\":{\"refund\":{\"type\":\"noul\",\"instructions\":\"The customer is asking for a refund.\"}},\"x_celeris\":{\"explain\":true}}'" }, "letme": { "capability": "https://letme.dev/inference.decision", "tool": "https://letme.dev/celeris-1-decision" }, "area": "models", "unitPrices": [ { "item": "Decision input", "unit": "1m-tokens", "usd": 0.04, "note": "Includes cached input and image tokens. Prepaid credit expires after 30 days." }, { "item": "Decision output", "unit": "1m-tokens", "usd": 0, "note": "Includes optional explanations." } ], "provenance": { "legalEntity": "Marqo Inc", "domain": "celeris.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://celeris.ai/terms", "privacy": "https://celeris.ai/privacy", "statusPage": "https://status.celeris.ai/", "changelog": "", "securityTxt": "none", "checked": "2026-10-09", "notes": [ "Terms dated 8 September 2026 and privacy notice dated 23 July 2026 name Marqo Inc operating as Celeris.", "No dedicated decision-model changelog or dated deprecation policy found.", "The public status history records an 11-hour-20-minute outage for the separate Celeris-1 model on 19 August 2026. It predates this decision model and is not counted as its outage.", "The standard well-known security.txt and docs OpenAPI JSON addresses returned HTTP 404. Domain registration was not checked." ], "score": 61 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/celeris-1-decision.json", "live": { "slug": "celeris-1-decision", "probe": { "target": "https://inference.celeris.ai/celeris-1-decision/v1/systemone", "method": "get", "lastAt": "2026-10-09T11:46:25.06310241Z", "lastOk": true, "lastStatus": 404, "lastMs": 341, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 343, "p95ms24h": 515, "samples24h": 24, "samples30d": 24, "days": [ { "date": "2026-10-09", "probes": 24, "ok": 24 } ] }, "vendorStatus": { "page": "https://status.celeris.ai", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-09T09:35:43.34493788Z" }, "updatedAt": "2026-10-09T11:46:25.06310241Z" } }, "answer": "GLiClass and Celeris-1 Decision score within a point of each other on agent readiness, 49.9 (D) and 49.3 (D). Celeris-1 Decision leads on schema \u0026 documentation, agent ergonomics and security \u0026 auth.", "b": { "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" }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Celeris (Marqo Inc)", "b": "Knowledgator", "name": "Vendor" }, { "a": "https://inference.celeris.ai/celeris-1-decision/v1/systemone", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "None", "name": "Auth" }, { "a": "Pay per use", "b": "Free", "name": "Pricing" }, { "a": "free", "b": "free", "name": "Price for inference decision" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary hosted model under Celeris terms of service", "b": "Apache-2.0 (library and the model weights we checked)", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "no", "name": "llms.txt" }, { "a": "2026-10-08", "b": "2026-07-21", "name": "Last release" }, { "a": "2026-09-08", "b": "no document linked", "name": "Terms last updated" }, { "a": "2026-07-23", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "", "name": "Terms restrict automated access" }, { "a": "yes", "b": "", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "555 stars, 13k PyPI/wk", "name": "Popularity" } ], "faq": [ { "answer": "GLiClass and Celeris-1 Decision score within a point of each other on agent readiness, 49.9 (D) and 49.3 (D). Celeris-1 Decision leads on schema \u0026 documentation, agent ergonomics and security \u0026 auth.", "question": "Which is better for AI agents, Celeris-1 Decision or GLiClass?" }, { "answer": "Celeris-1 Decision, at free against free for GLiClass. These are the vendors' published prices for the job.", "question": "Which is cheaper for inference decision, Celeris-1 Decision or GLiClass?" }, { "answer": "Celeris-1 Decision needs an API key. GLiClass needs no key.", "question": "Do Celeris-1 Decision and GLiClass need an API key?" }, { "answer": "Celeris-1 Decision has a hosted endpoint at https://inference.celeris.ai/celeris-1-decision/v1/systemone. No hosted endpoint is listed for GLiClass.", "question": "Can an agent call Celeris-1 Decision and GLiClass without installing anything?" }, { "answer": "No open-source release is listed for Celeris-1 Decision. GLiClass is open source (Apache-2.0 (library and the model weights we checked)).", "question": "Are Celeris-1 Decision and GLiClass open source?" } ], "goodFor": [ { "aheadOn": [ "Schema \u0026 documentation, 60 against 49", "Agent ergonomics, 80 against 60", "Security \u0026 auth, 45 against 38" ], "also": [ "Cheaper for inference decision, $0 against $0 per 1M tokens", "A hosted endpoint, with nothing to install" ], "goodFor": "Multimodal classification, routing and bounded decisions with probabilities and optional explanations", "slug": "celeris-1-decision", "watchFor": "Early-access terms and capacity-dependent workspace activation" }, { "aheadOn": [ "Payments \u0026 pricing, 60 against 20", "Transparency \u0026 trust, 64 against 53" ], "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" } ], "job": { "capability": "inference.decision", "name": "Inference decision" }, "others": [ { "json": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-cloudflare-clef.json", "title": "Celeris-1 Decision vs Clef", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-cloudflare-clef" }, { "json": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-convai-laya.json", "title": "Celeris-1 Decision vs Laya", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-convai-laya" }, { "json": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-decider.json", "title": "Celeris-1 Decision vs Decider", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-decider" }, { "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-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/celeris-1-decision-vs-openai-decisions-api.json", "title": "Celeris-1 Decision vs OpenAI Decisions API", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-openai-decisions-api" }, { "json": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-strands-decider.json", "title": "Celeris-1 Decision vs Strands Decider 2B", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-strands-decider" }, { "json": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-typesafe-jev.json", "title": "Celeris-1 Decision vs Jev", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-typesafe-jev" }, { "json": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-vela.json", "title": "Celeris-1 Decision vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-vela" }, { "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/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/decider-vs-gliclass.json", "title": "Decider vs GLiClass", "url": "https://www.anchorterminal.com/compare/decider-vs-gliclass" }, { "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-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" } ], "scores": [ { "by": 3, "celeris-1-decision": 40, "edge": "gliclass", "gliclass": 43, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 11, "celeris-1-decision": 60, "edge": "celeris-1-decision", "gliclass": 49, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 20, "celeris-1-decision": 80, "edge": "celeris-1-decision", "gliclass": 60, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "by": 7, "celeris-1-decision": 45, "edge": "celeris-1-decision", "gliclass": 38, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "by": 40, "celeris-1-decision": 20, "edge": "gliclass", "gliclass": 60, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 4, "celeris-1-decision": 40, "edge": "gliclass", "gliclass": 44, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 11, "celeris-1-decision": 53, "edge": "gliclass", "gliclass": 64, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "GLiClass and Celeris-1 Decision score within a point of each other on agent readiness, 49.9 (D) and 49.3 (D). Celeris-1 Decision leads on schema \u0026 documentation, agent ergonomics and security \u0026 auth. Both do inference decision. Celeris-1 Decision is cheaper for inference decision, $0 against $0 per 1M tokens.", "verdicts": { "celeris-1-decision": "Typed probabilities, image inputs and optional explanations suit routing and classification inside an agent. Both System One and OpenAI Decisions request formats are documented. The service remains early access under its terms, activation can queue, and prepaid credit expires after 30 days. The published accuracy and latency figures are Celeris measurements, not Anchor Terminal tests.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-gliclass", "json": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-gliclass.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-gliclass.md", "slim": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-gliclass.min.md" }, "markdown": "GLiClass and Celeris-1 Decision score within a point of each other on agent readiness, 49.9 (D) and 49.3 (D). Celeris-1 Decision leads on schema \u0026 documentation, agent ergonomics and security \u0026 auth. Both do inference decision. Celeris-1 Decision is cheaper for inference decision, $0 against $0 per 1M tokens.\n\n- Celeris-1 Decision: grade D, 49.3/100, rank #708 of 842. Markdown https://www.anchorterminal.com/tools/celeris-1-decision.md · JSON https://www.anchorterminal.com/api/v1/tools/celeris-1-decision.json\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\n## Which one, for what\n\n### Celeris-1 Decision (D)\n\nGood for: Multimodal classification, routing and bounded decisions with probabilities and optional explanations\n\nAhead on:\n- Schema \u0026 documentation, 60 against 49\n- Agent ergonomics, 80 against 60\n- Security \u0026 auth, 45 against 38\n\nAlso in its favour:\n- Cheaper for inference decision, $0 against $0 per 1M tokens\n- A hosted endpoint, with nothing to install\n\nWatch for: Early-access terms and capacity-dependent workspace activation\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- Payments \u0026 pricing, 60 against 20\n- Transparency \u0026 trust, 64 against 53\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\n## Score by category\n\n| Category | Weight | Celeris-1 Decision | GLiClass | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 40 | 43 | GLiClass +3 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 60 | 49 | Celeris-1 Decision +11 |\n| Agent ergonomics | 13% (16.2 this run) | 80 | 60 | Celeris-1 Decision +20 |\n| Security \u0026 auth | 14% (17.5 this run) | 45 | 38 | Celeris-1 Decision +7 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 60 | GLiClass +40 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 40 | 44 | GLiClass +4 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 53 | 64 | GLiClass +11 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **49.3 · D** | **49.9 · D** | |\n\n## Facts side by side\n\n| Fact | Celeris-1 Decision | GLiClass |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Celeris (Marqo Inc) | Knowledgator |\n| Hosted endpoint | `https://inference.celeris.ai/celeris-1-decision/v1/systemone` | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | API key | None |\n| Pricing | Pay per use | Free |\n| Price for inference decision | free | free |\n| x402 | no | no |\n| Licence | Proprietary hosted model under Celeris terms of service | Apache-2.0 (library and the model weights we checked) |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| Last release | 2026-10-08 | 2026-07-21 |\n| Terms last updated | 2026-09-08 | no document linked |\n| Privacy policy last updated | 2026-07-23 | no document linked |\n| Customer content may train models | not found in the text | |\n| Terms restrict automated access | not found in the text | |\n| Terms restrict benchmarking | yes | |\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 | none | 555 stars, 13k PyPI/wk |\n\n## Verdicts\n\n**Celeris-1 Decision.** Typed probabilities, image inputs and optional explanations suit routing and classification inside an agent. Both System One and OpenAI Decisions request formats are documented. The service remains early access under its terms, activation can queue, and prepaid credit expires after 30 days. The published accuracy and latency figures are Celeris measurements, not Anchor Terminal tests.\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## Before you call either\n\n### Celeris-1 Decision\n\n1. Use the decision model path and matching model field. This model has no chat, Responses or models endpoint.\n2. Use at most 512 questions per request, or 64 with explanations. Both endpoints reject streaming.\n3. Preserve x_celeris in a custom Jev SDK response model when reading explanations. The default response type drops it.\n4. Retry 429 with Retry-After and backoff. Stop on 402 until workspace credit is replenished.\n5. Read usage.input_tokens for cost, including images and request overhead. Track credit expiry separately from token consumption.\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## Questions\n\n### Which is better for AI agents, Celeris-1 Decision or GLiClass?\n\nGLiClass and Celeris-1 Decision score within a point of each other on agent readiness, 49.9 (D) and 49.3 (D). Celeris-1 Decision leads on schema \u0026 documentation, agent ergonomics and security \u0026 auth.\n\n### Which is cheaper for inference decision, Celeris-1 Decision or GLiClass?\n\nCeleris-1 Decision, at free against free for GLiClass. These are the vendors' published prices for the job.\n\n### Do Celeris-1 Decision and GLiClass need an API key?\n\nCeleris-1 Decision needs an API key. GLiClass needs no key.\n\n### Can an agent call Celeris-1 Decision and GLiClass without installing anything?\n\nCeleris-1 Decision has a hosted endpoint at https://inference.celeris.ai/celeris-1-decision/v1/systemone. No hosted endpoint is listed for GLiClass.\n\n### Are Celeris-1 Decision and GLiClass open source?\n\nNo open-source release is listed for Celeris-1 Decision. GLiClass is open source (Apache-2.0 (library and the model weights we checked)).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/celeris-1-decision-vs-gliclass.json, and with the fewest tokens: https://www.anchorterminal.com/compare/celeris-1-decision-vs-gliclass.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"celeris-1-decision\", \"b\": \"gliclass\"}`. From a terminal: `anchor compare celeris-1-decision gliclass`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/celeris-1-decision.json and https://www.anchorterminal.com/api/v1/tools/gliclass.json\n\n## Other comparisons with Celeris-1 Decision or GLiClass\n\n- [Celeris-1 Decision vs Clef](https://www.anchorterminal.com/compare/celeris-1-decision-vs-cloudflare-clef.md)\n- [Celeris-1 Decision vs Laya](https://www.anchorterminal.com/compare/celeris-1-decision-vs-convai-laya.md)\n- [Celeris-1 Decision vs Decider](https://www.anchorterminal.com/compare/celeris-1-decision-vs-decider.md)\n- [Celeris-1 Decision vs Kev](https://www.anchorterminal.com/compare/celeris-1-decision-vs-jaredpalmer-kev.md)\n- [Celeris-1 Decision vs Liquid d1](https://www.anchorterminal.com/compare/celeris-1-decision-vs-liquid-d1.md)\n- [Celeris-1 Decision vs OpenAI Decisions API](https://www.anchorterminal.com/compare/celeris-1-decision-vs-openai-decisions-api.md)\n- [Celeris-1 Decision vs Strands Decider 2B](https://www.anchorterminal.com/compare/celeris-1-decision-vs-strands-decider.md)\n- [Celeris-1 Decision vs Jev](https://www.anchorterminal.com/compare/celeris-1-decision-vs-typesafe-jev.md)\n- [Celeris-1 Decision vs Vela 2.0](https://www.anchorterminal.com/compare/celeris-1-decision-vs-vela.md)\n- [Clef vs GLiClass](https://www.anchorterminal.com/compare/cloudflare-clef-vs-gliclass.md)\n- [Laya vs GLiClass](https://www.anchorterminal.com/compare/convai-laya-vs-gliclass.md)\n- [Decider vs GLiClass](https://www.anchorterminal.com/compare/decider-vs-gliclass.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 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", "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": "Celeris-1 Decision vs GLiClass", "url": "" } ], "description": "GLiClass and Celeris-1 Decision score within a point of each other on agent readiness, 49.9 (D) and 49.3 (D). Celeris-1 Decision leads on schema \u0026 documentation, agent ergonomics and security \u0026 auth. Both do inference decision. Celeris-1 Decision is cheaper for inference…", "facts": [ "Celeris-1 Decision D 49.3", "GLiClass D 49.9", "scores" ], "h1": "Celeris-1 Decision vs GLiClass", "image": "https://www.anchorterminal.com/assets/og/compare-celeris-1-decision-vs-gliclass.png", "path": "/compare/celeris-1-decision-vs-gliclass", "published": "2026-10-01", "section": "tools", "title": "Celeris-1 Decision vs GLiClass for AI agents, D 49.3 vs D 49.9", "toc": null, "updated": "2026-10-09", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-gliclass" }, "tokens": { "markdown": 2450, "slim": 730 }, "version": 1 }