{ "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": 785, "ranked": true, "rankOf": 954, "categoryRank": 11, "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": "2026-10-09T16:55:07.207346386Z" }, { "registry": "pypi", "name": "gliclass", "version": "0.1.20", "released": "2026-07-21", "seenAt": "2026-10-09T16:55:07.014721965Z" } ], "githubStars": 556, "pypiWeekly": 12735, "securityTxt": { "url": "https://knowledgator.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-09T15:39:16.87234666Z" }, "updatedAt": "2026-10-09T16:55:07.207346386Z" } }, "answer": "GLiClass scores 49.9 (D) on agent readiness against Microsoft-Decision-1's 39 (E), and leads in 6 of 7 scored categories. Microsoft-Decision-1 leads on security \u0026 auth.", "b": { "slug": "microsoft-decision-1", "name": "Microsoft-Decision-1", "vendor": "Microsoft", "vendorUrl": "https://www.microsoft.com", "kind": "model", "category": "decision-models", "summary": "Microsoft-Decision-1 is a Microsoft model, post-trained from Qwen3.5-9B, that scores fixed answer options with a calibrated probability for each. It is in public preview on Microsoft Foundry and OpenRouter, at $0.042 per million input tokens.", "url": "https://www.anchorterminal.com/tools/microsoft-decision-1", "markdownUrl": "https://www.anchorterminal.com/tools/microsoft-decision-1.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/microsoft-decision-1.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/microsoft-decision-1.json", "license": "Not stated. The announcement and OpenRouter's model page name no licence, and no weights repository was found.", "transports": [ "http" ], "packages": [], "auth": "mixed", "authNotes": "Foundry route: a Microsoft Entra bearer token for https://cognitiveservices.azure.com/.default, against a deployment in a Foundry resource, so an Azure subscription and deployment come first. OpenRouter route: an OpenRouter API key, read from OPENROUTER_API_KEY in OpenRouter's SDK example. Signup and key creation on OpenRouter were not checked.", "pricing": "usage", "pricingNotes": "$0.042 per million input tokens, with output free, on Foundry US and EU Datazone deployments and on OpenRouter (checked 10 October 2026). Microsoft says usage charges apply. No free tier or trial without a card was found.", "priceSummary": "Pay per use", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in Microsoft's announcement, the Tech Community post, the Foundry sample or OpenRouter's model page, checked 10 October 2026.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-10" }, "docsUrl": "https://commandline.microsoft.com/microsoft-decision-1-model-foundry/", "capabilities": [ "inference.decision" ], "tags": [ "hosted", "model", "usage-priced", "status-page", "beta" ], "lastRelease": "2026-10-09", "graded": true, "anchor": { "graded": true, "score": 39, "grade": "E", "agentReady": false, "rank": 921, "ranked": true, "rankOf": 954, "categoryRank": 14, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 50, "maintenance": 40, "payments": 20, "reliability": 30, "schema": 43, "security": 52, "transparency": 32 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-10" }, "negative": 0, "verdict": "Microsoft publishes $0.042 per million input tokens, with output free, and the model is callable through Microsoft Foundry and OpenRouter. It is in public preview. No licence, model-specific retention statement, rate limit or deprecation policy was found, and the Foundry route needs an Azure deployment and an Entra token. Latency and accuracy figures are Microsoft's claims.", "bestFor": "Routing, classification, prioritisation and rubric checks over text, where a fixed set of options and a low price per token matter more than generated text.", "strengths": [ "Price published without a login: $0.042 per million input tokens, with output free, on the US and EU Datazone deployments and on OpenRouter", "Callable today through two routes, Microsoft Foundry and OpenRouter, both linked from Microsoft's 9 October 2026 announcement", "Each answer is a probability for one fixed option, which Microsoft describes as calibrated, so an application can send uncertain results to review", "OpenRouter lists a 32,768-token context window, text input and decisions as output", "OpenRouter's documentation lists a Decisions method in its Python, TypeScript and Go SDKs, marked alpha" ], "weaknesses": [ "Public preview only. Microsoft's post gives no general availability date and states no licence for the hosted model", "No model-specific rate limit, retention statement or deprecation policy was found. Microsoft's Foundry data page covers Models sold by Azure in general", "The Foundry route needs an Azure subscription, a deployment of the model and a Microsoft Entra token, all set up by a person", "Microsoft describes its Xbox Research result as competitive with GPT-5 or GPT-6 Sol on quality, not better, and the two Microsoft posts name different baselines for it", "Azure status history lists a Foundry Models incident on 29 September 2026 in Sweden Central, with intermittent failures and HTTP 5xx for about six hours" ], "agentNotes": [ "Use OpenRouter's Decisions method, not an OpenAI chat-completions SDK. OpenRouter says chat completions SDKs will not work with this model", "On Foundry, send the request to the deployment's /providers/microsoft/v1/systemone path with a Microsoft Entra token for https://cognitiveservices.azure.com/.default, not an API key", "Take the deployment name from the Foundry quickstart before the first call. Microsoft says to confirm the route and authentication header, and the pages reviewed do not give the name", "Keep each request within OpenRouter's 32,768-token context and send only fixed options, since the model is not intended for open-ended generation", "Measure latency and calibration on your own labelled cases before relying on Microsoft's latency and 'nine times out of 10' statements" ], "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": 39 } ], "editorialScores": { "ergonomics": 50, "maintenance": 40, "payments": 20, "reliability": 30, "schema": 43, "security": 52, "transparency": 22 }, "provenanceScore": 41 }, "connect": { "http": "curl -X POST \"$AZURE_ENDPOINT/providers/microsoft/v1/systemone\" \\\n -H \"Authorization: Bearer $ENTRA_TOKEN\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"\u003cdeployment-name\u003e\",\"state\":\"The customer requests a refund for a duplicate charge.\",\"questions\":{\"team\":{\"type\":\"choice\",\"instructions\":\"Which team should handle this request?\",\"criteria\":{\"billing\":\"Charges, invoices, refunds or subscription payments\",\"technical\":\"Software errors or integration failures\"}}}}'" }, "letme": { "capability": "https://letme.dev/inference.decision", "tool": "https://letme.dev/microsoft-decision-1" }, "sameCompany": [ "azure-foundry-fine-tuning", "azure-ai-content-safety", "azure-speech-to-text", "azure-text-to-speech", "microsoft-agent-framework", "microsoft-execution-containers", "microsoft-entra-agent-id", "azure-key-vault", "azure-document-intelligence", "azure-devops-mcp", "microsoft-learn-mcp", "playwright-mcp", "azure-mcp", "azure-maps", "azure-translator", "microsoft-graph-calendar", "azure-blob-storage", "onedrive-sharepoint", "microsoft-teams", "dynamics-365-sales", "power-automate", "foundry-local", "microsoft-advertising-api", "microsoft-excel-graph", "outlook-mail-graph" ], "area": "models", "unitPrices": [ { "item": "Decision input", "unit": "1m-tokens", "usd": 0.042, "note": "US and EU Datazone on Foundry and OpenRouter. Microsoft's post says usage charges apply." }, { "item": "Decision output", "unit": "1m-tokens", "usd": 0, "note": "Free per Microsoft's post and OpenRouter. The Foundry price table shows N/A." } ], "provenance": { "legalEntity": "", "domain": "microsoft.com", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/openai/data-privacy", "statusPage": "https://azure.status.microsoft/en-us/status/history/", "changelog": "", "securityTxt": "expired", "checked": "2026-10-10", "notes": [ "The Foundry endpoint is account-specific, given as AZURE_ENDPOINT in Microsoft's sample, so endpointOnVendorDomain is not set.", "The legal entity name and Microsoft's product terms were not read, so terms is empty.", "Microsoft's security.txt at www.microsoft.com/.well-known/security.txt gives an Expires date of 2026-09-23, which has passed.", "The Azure status history page shows a Foundry Models component and dated incidents. It is shared by all Foundry models, not specific to this one.", "The Foundry model catalogue page at ai.azure.com is rendered by script and returned no model content when read." ], "score": 41 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/microsoft-decision-1.json", "live": { "slug": "microsoft-decision-1", "vendorStatus": { "page": "https://azure.status.microsoft/en-us/status/history", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-10T11:53:10.031474948Z" }, "updatedAt": "2026-10-10T11:53:10.031474948Z" } }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Knowledgator", "b": "Microsoft", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "OAuth or key", "name": "Auth" }, { "a": "Free", "b": "Pay per use", "name": "Pricing" }, { "a": "free", "b": "free", "name": "Price for decision models" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0 (library and the model weights we checked)", "b": "Not stated. The announcement and OpenRouter's model page name no licence, and no weights repository was found.", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-07-21", "b": "2026-10-09", "name": "Last release" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "", "name": "Privacy policy last updated" }, { "a": "", "b": "", "name": "Customer content may train models" }, { "a": "", "b": "", "name": "Terms restrict automated access" }, { "a": "", "b": "", "name": "Terms restrict benchmarking" }, { "a": "", "b": "", "name": "Terms or service can change without notice" }, { "a": "", "b": "", "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 Microsoft-Decision-1's 39 (E), and leads in 6 of 7 scored categories. Microsoft-Decision-1 leads on security \u0026 auth.", "question": "Which is better for AI agents, GLiClass or Microsoft-Decision-1?" }, { "answer": "GLiClass, at free against free for Microsoft-Decision-1. These are the vendors' published prices for the job.", "question": "Which is cheaper for decision models, GLiClass or Microsoft-Decision-1?" }, { "answer": "GLiClass needs no key. Microsoft-Decision-1 takes an API key or an OAuth sign-in.", "question": "Do GLiClass and Microsoft-Decision-1 need an API key?" }, { "answer": "No hosted endpoint is listed for GLiClass. No hosted endpoint is listed for Microsoft-Decision-1.", "question": "Can an agent call GLiClass and Microsoft-Decision-1 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 Microsoft-Decision-1.", "question": "Are GLiClass and Microsoft-Decision-1 open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 43 against 30", "Schema \u0026 documentation, 49 against 43", "Agent ergonomics, 60 against 50", "Payments \u0026 pricing, 60 against 20", "Transparency \u0026 trust, 64 against 32" ], "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": [ "Security \u0026 auth, 52 against 38" ], "also": [ "Cheaper for decision models, $0 against $0 per 1M tokens" ], "goodFor": "Routing, classification, prioritisation and rubric checks over text, where a fixed set of options and a low price per token matter more than generated text.", "slug": "microsoft-decision-1", "watchFor": "Public preview only. Microsoft's post gives no general availability date and states no licence for the hosted model" } ], "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-microsoft-decision-1.json", "title": "Celeris-1 Decision vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-microsoft-decision-1" }, { "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-microsoft-decision-1.json", "title": "Clef vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-microsoft-decision-1" }, { "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-microsoft-decision-1.json", "title": "Laya vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/convai-laya-vs-microsoft-decision-1" }, { "json": "https://www.anchorterminal.com/compare/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-microsoft-decision-1.json", "title": "Decider vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/decider-vs-microsoft-decision-1" }, { "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-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-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-microsoft-decision-1.json", "title": "Kev vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-microsoft-decision-1" }, { "json": "https://www.anchorterminal.com/compare/liquid-d1-vs-microsoft-decision-1.json", "title": "Liquid d1 vs Microsoft-Decision-1", "url": "https://www.anchorterminal.com/compare/liquid-d1-vs-microsoft-decision-1" }, { "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-nace-drex.json", "title": "Microsoft-Decision-1 vs Drex 1.5", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-nace-drex" }, { "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-openai-decisions-api.json", "title": "Microsoft-Decision-1 vs OpenAI Decisions API", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-openai-decisions-api" }, { "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-pplx-decider.json", "title": "Microsoft-Decision-1 vs pplx-decider", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-pplx-decider" }, { "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-strands-decider.json", "title": "Microsoft-Decision-1 vs Strands Decider 2B", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-strands-decider" }, { "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-typesafe-jev.json", "title": "Microsoft-Decision-1 vs Jev", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-typesafe-jev" }, { "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-vela.json", "title": "Microsoft-Decision-1 vs Vela 2.0", "url": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-vela" } ], "scores": [ { "by": 13, "edge": "gliclass", "gliclass": 43, "key": "reliability", "microsoft-decision-1": 30, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 6, "edge": "gliclass", "gliclass": 49, "key": "schema", "microsoft-decision-1": 43, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 10, "edge": "gliclass", "gliclass": 60, "key": "ergonomics", "microsoft-decision-1": 50, "name": "Agent ergonomics", "weight": 13 }, { "by": 14, "edge": "microsoft-decision-1", "gliclass": 38, "key": "security", "microsoft-decision-1": 52, "name": "Security \u0026 auth", "weight": 14 }, { "by": 40, "edge": "gliclass", "gliclass": 60, "key": "payments", "microsoft-decision-1": 20, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 4, "edge": "gliclass", "gliclass": 44, "key": "maintenance", "microsoft-decision-1": 40, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 32, "edge": "gliclass", "gliclass": 64, "key": "transparency", "microsoft-decision-1": 32, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "GLiClass scores 49.9 (D) on agent readiness against Microsoft-Decision-1's 39 (E), and leads in 6 of 7 scored categories. Microsoft-Decision-1 leads on security \u0026 auth. Both do decision models. Microsoft-Decision-1 is cheaper for decision models, $0 against $0 per 1M tokens.", "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.", "microsoft-decision-1": "Microsoft publishes $0.042 per million input tokens, with output free, and the model is callable through Microsoft Foundry and OpenRouter. It is in public preview. No licence, model-specific retention statement, rate limit or deprecation policy was found, and the Foundry route needs an Azure deployment and an Entra token. Latency and accuracy figures are Microsoft's claims." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/gliclass-vs-microsoft-decision-1", "json": "https://www.anchorterminal.com/compare/gliclass-vs-microsoft-decision-1.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/gliclass-vs-microsoft-decision-1.md", "slim": "https://www.anchorterminal.com/compare/gliclass-vs-microsoft-decision-1.min.md" }, "markdown": "GLiClass scores 49.9 (D) on agent readiness against Microsoft-Decision-1's 39 (E), and leads in 6 of 7 scored categories. Microsoft-Decision-1 leads on security \u0026 auth. Both do decision models. Microsoft-Decision-1 is cheaper for decision models, $0 against $0 per 1M tokens.\n\n- GLiClass: grade D, 49.9/100, rank #785 of 954. Markdown https://www.anchorterminal.com/tools/gliclass.md · JSON https://www.anchorterminal.com/api/v1/tools/gliclass.json\n- Microsoft-Decision-1: grade E, 39/100, rank #921 of 954. Markdown https://www.anchorterminal.com/tools/microsoft-decision-1.md · JSON https://www.anchorterminal.com/api/v1/tools/microsoft-decision-1.json\n- Best decision models for AI agents: https://www.anchorterminal.com/best/decision-models/index.md\n- All 91 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- Reliability, 43 against 30\n- Schema \u0026 documentation, 49 against 43\n- Agent ergonomics, 60 against 50\n- Payments \u0026 pricing, 60 against 20\n- Transparency \u0026 trust, 64 against 32\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### Microsoft-Decision-1 (E)\n\nGood for: Routing, classification, prioritisation and rubric checks over text, where a fixed set of options and a low price per token matter more than generated text.\n\nAhead on:\n- Security \u0026 auth, 52 against 38\n\nAlso in its favour:\n- Cheaper for decision models, $0 against $0 per 1M tokens\n\nWatch for: Public preview only. Microsoft's post gives no general availability date and states no licence for the hosted model\n\n\n## Score by category\n\n| Category | Weight | GLiClass | Microsoft-Decision-1 | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 43 | 30 | GLiClass +13 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 49 | 43 | GLiClass +6 |\n| Agent ergonomics | 13% (16.2 this run) | 60 | 50 | GLiClass +10 |\n| Security \u0026 auth | 14% (17.5 this run) | 38 | 52 | Microsoft-Decision-1 +14 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 20 | GLiClass +40 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 44 | 40 | GLiClass +4 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 64 | 32 | GLiClass +32 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **49.9 · D** | **39 · E** | |\n\n## Facts side by side\n\n| Fact | GLiClass | Microsoft-Decision-1 |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Knowledgator | Microsoft |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | None | OAuth or key |\n| Pricing | Free | Pay per use |\n| Price for decision models | free | free |\n| x402 | no | no |\n| Licence | Apache-2.0 (library and the model weights we checked) | Not stated. The announcement and OpenRouter's model page name no licence, and no weights repository was found. |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-07-21 | 2026-10-09 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | |\n| Customer content may train models | | |\n| Terms restrict automated access | | |\n| Terms restrict benchmarking | | |\n| Terms or service can change without notice | | |\n| Arbitration or class-action waiver | | |\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**Microsoft-Decision-1.** Microsoft publishes $0.042 per million input tokens, with output free, and the model is callable through Microsoft Foundry and OpenRouter. It is in public preview. No licence, model-specific retention statement, rate limit or deprecation policy was found, and the Foundry route needs an Azure deployment and an Entra token. Latency and accuracy figures are Microsoft's claims.\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### Microsoft-Decision-1\n\n1. Use OpenRouter's Decisions method, not an OpenAI chat-completions SDK. OpenRouter says chat completions SDKs will not work with this model\n2. On Foundry, send the request to the deployment's /providers/microsoft/v1/systemone path with a Microsoft Entra token for https://cognitiveservices.azure.com/.default, not an API key\n3. Take the deployment name from the Foundry quickstart before the first call. Microsoft says to confirm the route and authentication header, and the pages reviewed do not give the name\n4. Keep each request within OpenRouter's 32,768-token context and send only fixed options, since the model is not intended for open-ended generation\n5. Measure latency and calibration on your own labelled cases before relying on Microsoft's latency and 'nine times out of 10' statements\n\n## Questions\n\n### Which is better for AI agents, GLiClass or Microsoft-Decision-1?\n\nGLiClass scores 49.9 (D) on agent readiness against Microsoft-Decision-1's 39 (E), and leads in 6 of 7 scored categories. Microsoft-Decision-1 leads on security \u0026 auth.\n\n### Which is cheaper for decision models, GLiClass or Microsoft-Decision-1?\n\nGLiClass, at free against free for Microsoft-Decision-1. These are the vendors' published prices for the job.\n\n### Do GLiClass and Microsoft-Decision-1 need an API key?\n\nGLiClass needs no key. Microsoft-Decision-1 takes an API key or an OAuth sign-in.\n\n### Can an agent call GLiClass and Microsoft-Decision-1 without installing anything?\n\nNo hosted endpoint is listed for GLiClass. No hosted endpoint is listed for Microsoft-Decision-1.\n\n### Are GLiClass and Microsoft-Decision-1 open source?\n\nGLiClass is open source (Apache-2.0 (library and the model weights we checked)). No open-source release is listed for Microsoft-Decision-1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/gliclass-vs-microsoft-decision-1.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gliclass-vs-microsoft-decision-1.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gliclass\", \"b\": \"microsoft-decision-1\"}`. From a terminal: `anchor compare gliclass microsoft-decision-1`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gliclass.json and https://www.anchorterminal.com/api/v1/tools/microsoft-decision-1.json\n\n## Other comparisons with GLiClass or Microsoft-Decision-1\n\n- [Celeris-1 Decision vs GLiClass](https://www.anchorterminal.com/compare/celeris-1-decision-vs-gliclass.md)\n- [Celeris-1 Decision vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/celeris-1-decision-vs-microsoft-decision-1.md)\n- [Clef vs GLiClass](https://www.anchorterminal.com/compare/cloudflare-clef-vs-gliclass.md)\n- [Clef vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/cloudflare-clef-vs-microsoft-decision-1.md)\n- [Laya vs GLiClass](https://www.anchorterminal.com/compare/convai-laya-vs-gliclass.md)\n- [Laya vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/convai-laya-vs-microsoft-decision-1.md)\n- [Decider vs GLiClass](https://www.anchorterminal.com/compare/decider-vs-gliclass.md)\n- [Decider vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/decider-vs-microsoft-decision-1.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 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 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 Microsoft-Decision-1](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-microsoft-decision-1.md)\n- [Liquid d1 vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/liquid-d1-vs-microsoft-decision-1.md)\n- [Microsoft-Decision-1 vs Drex 1.5](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-nace-drex.md)\n- [Microsoft-Decision-1 vs OpenAI Decisions API](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-openai-decisions-api.md)\n- [Microsoft-Decision-1 vs pplx-decider](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-pplx-decider.md)\n- [Microsoft-Decision-1 vs Strands Decider 2B](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-strands-decider.md)\n- [Microsoft-Decision-1 vs Jev](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-typesafe-jev.md)\n- [Microsoft-Decision-1 vs Vela 2.0](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-vela.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-10", "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 Microsoft-Decision-1", "url": "" } ], "description": "GLiClass scores 49.9 (D) to Microsoft-Decision-1's 39 (E) for decision models. Microsoft-Decision-1 is cheaper for decision models, $0 against $0 per 1M tokens. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "GLiClass D 49.9", "Microsoft-Decision-1 E 39", "scores" ], "h1": "GLiClass vs Microsoft-Decision-1", "image": "https://www.anchorterminal.com/assets/og/compare-gliclass-vs-microsoft-decision-1.png", "path": "/compare/gliclass-vs-microsoft-decision-1", "published": "2026-10-01", "section": "tools", "title": "GLiClass vs Microsoft-Decision-1 for AI agents (2026)", "toc": null, "updated": "2026-10-10", "url": "https://www.anchorterminal.com/compare/gliclass-vs-microsoft-decision-1" }, "tokens": { "markdown": 2750, "slim": 630 }, "version": 1 }