{
  "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": "Drex 1.5 scores 69.7 (B) on agent readiness against GLiClass's 49.9 (D), and leads in 5 of 7 scored categories. GLiClass leads on payments \u0026 pricing.",
    "b": {
      "slug": "nace-drex",
      "name": "Drex 1.5",
      "vendor": "Nace AI, Inc. (Nace.AI)",
      "vendorUrl": "https://www.nace.ai",
      "kind": "model",
      "category": "decision-models",
      "summary": "Drex 1.5 is Nace.AI's decision model. It returns a probability for each option in typed yes or no, choice and score questions. Hosted at console.nace.ai, with open weights under the Nace AI Open RAIL-M licence.",
      "url": "https://www.anchorterminal.com/tools/nace-drex",
      "markdownUrl": "https://www.anchorterminal.com/tools/nace-drex.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/nace-drex.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/nace-drex.json",
      "repo": "https://huggingface.co/nace-ai/drex-v1.5",
      "license": "Hosted API under the Nace AI Terms of Service, last updated 5 May 2026. Weights under the Nace AI Open RAIL-M licence (modified, version 1.0, October 2026), which is not an open-source licence. Businesses above $1 million in revenue or funding need a separate commercial licence, and competing products are excluded. The bundled code/kev package, derived from Jared Palmer's Kev (https://github.com/jaredpalmer/kev), and the GitHub repository are Apache-2.0, and the agent skill is MIT.",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://console.nace.ai/v1/systemone",
      "packages": [
        {
          "registry": "pypi",
          "name": "nace-sdk"
        },
        {
          "registry": "npm",
          "name": "nace-sdk"
        },
        {
          "registry": "pypi",
          "name": "nace-mcp"
        }
      ],
      "auth": "api-key",
      "authNotes": "A key starting nace_sk_, created in the Console dashboard after an emailed-code sign-in and sent as a Bearer header. The key is shown once. An account can hold three active keys, which share its credit and rate limits. Keys can be revoked and rotated, and no scopes are documented. An agent cannot create its own account, because sign-in needs an emailed code.",
      "pricing": "freemium",
      "pricingNotes": "drex-v1.5 costs $0.05 per million input tokens, and output tokens are not billed. The price is on the public pricing reference without a login. New accounts get $25 of signup credit, which expires three months after sign-up, and a $5 monthly credit. Each mailbox gets the signup credit once, and disposable domains get none. Without a saved card, requests stop at zero credit with 402 insufficient_credit. A saved card turns on pay-as-you-go, billed every 14 days.",
      "priceSummary": "Freemium",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the pricing reference, the API reference or the OpenAPI document (checked 10 October 2026).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": 318,
        "pypiWeekly": 156,
        "asOf": "2026-10-10"
      },
      "docsUrl": "https://console.nace.ai/docs/drex",
      "llmsTxt": "https://drex.nace.ai/llms.txt",
      "openapi": "https://console.nace.ai/openapi.json",
      "capabilities": [
        "inference.decision"
      ],
      "tags": [
        "hosted",
        "model",
        "open-weights",
        "llms-txt",
        "openapi",
        "python",
        "typescript",
        "mcp",
        "free-tier",
        "usage-priced",
        "status-page"
      ],
      "lastRelease": "2026-09-28",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 69.7,
        "grade": "B",
        "agentReady": false,
        "rank": 172,
        "ranked": true,
        "rankOf": 954,
        "categoryRank": 2,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 85,
          "maintenance": 65,
          "payments": 40,
          "reliability": 80,
          "schema": 88,
          "security": 65,
          "transparency": 63
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-10"
        },
        "negative": -2,
        "negativeNotes": [
          "10 October 2026, read against the public board generated 28 September 2026. The site at www.nace.ai/drex states a Decision Index 0.2.1 score of 58.28 and says Drex 1.5 leads all 71 entries under 10B parameters. The 0.2.1 board has 70 entries, none of them Drex, and its top score is Surogate Rune 26B-A4B v3 at 57.44 (https://huggingface.co/spaces/multimodalart/jev-decision-index/resolve/main/data/index-v0.2.1.json). The Hugging Face card does say the Drex figure is Nace's own run, but the site does not. Deducted 2 as a misleading claim."
        ],
        "verdict": "The hosted endpoint has a public OpenAPI document, published limits and pinned model versions, at $0.05 per million input tokens with no output charge. The #1 under 10B claim rests on Nace's own run, since Drex is absent from both public boards. Weights carry Open RAIL-M, which requires a commercial licence above $1 million in revenue or funding.",
        "bestFor": "Routing, triage and yes or no gates inside an agent, where the caller supplies the options and acts on the probabilities. Suited to hosted use at a low per-token price, or to open weights where the licence fits.",
        "strengths": [
          "Public OpenAPI 3.1 document for POST /v1/systemone, plus llms.txt. Request limits are 512 questions, a 1,048,576-byte body and a 131,072-token state.",
          "Price per input token on the pricing reference, readable without a login. drex-v1.5 costs $0.05 per million, and output tokens are not billed.",
          "Rate limits with numbers for the free tier (120 requests a minute) and the paid tier (600), and Retry-After on 429 and 529 responses.",
          "Pinned model ids (drex-v1.0, drex-v1.5) that stay on their version, with a dated record of the drex-latest alias moves.",
          "Official Python and TypeScript SDKs (nace-sdk), an MCP server (nace-mcp) with 21 tools, and the weights on Hugging Face."
        ],
        "weaknesses": [
          "The rank 1 claim comes from Nace's own run on Decision Index 0.3.1, and Drex is not on the public board for 0.3 or 0.2.1.",
          "The weights are under Open RAIL-M, which restricts commercial use above $1 million in revenue or funding and excludes competing products.",
          "The data statements conflict. The developer page says no training on your data, while the privacy notice allows input and output to improve the Services.",
          "No SLA, changelog or readable incident list for the model. Drex has been public for 12 days.",
          "Sign-up needs an emailed code and a browser step. The $25 signup credit is granted once per mailbox and expires after three months."
        ],
        "agentNotes": [
          "Call https://console.nace.ai/v1/systemone with Authorization: Bearer nace_sk_..., and pin model drex-v1.5 rather than drex-latest in production.",
          "Stop on 402 insufficient_credit or 402 payment_required until credit is topped up or the unpaid invoice is paid.",
          "Retry 429 and 529 after retry-after-ms. On a 422 for an unknown model, use one of the ids the error message lists.",
          "Keep state below 131,072 tokens and the body below 1,048,576 bytes, and send at most 512 questions per request.",
          "Keep the key on a server. A key in browser code is exposed, and the /v1 routes send no Access-Control-Allow-Origin header.",
          "Check usage.input_tokens and the usage CSV after retries, since /v1/systemone documents no idempotency key."
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "B",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 69.7
          }
        ],
        "editorialScores": {
          "ergonomics": 85,
          "maintenance": 65,
          "payments": 40,
          "reliability": 80,
          "schema": 88,
          "security": 65,
          "transparency": 50
        },
        "provenanceScore": 75
      },
      "connect": {
        "install": "pip install nace-sdk   # or: npm install nace-sdk",
        "http": "curl https://console.nace.ai/v1/systemone \\\n  -H \"Authorization: Bearer $NACE_API_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"model\":\"drex-v1.5\",\"state\":\"I was charged twice for order A-104.\",\"questions\":{\"refund\":{\"type\":\"noul\",\"instructions\":\"Does the customer ask for a refund?\"}}}'",
        "claudeCode": "uvx nace-mcp login\nclaude mcp add nace -- uvx nace-mcp"
      },
      "letme": {
        "capability": "https://letme.dev/inference.decision",
        "tool": "https://letme.dev/nace-drex"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "Drex 1.5 input",
          "unit": "1m-tokens",
          "usd": 0.05,
          "note": "Per input token, as reported in usage.input_tokens. The pinned drex-v1.0 costs $0.04."
        },
        {
          "item": "Drex 1.5 output",
          "unit": "1m-tokens",
          "usd": 0,
          "note": "Reported in usage.output_tokens and not billed."
        }
      ],
      "provenance": {
        "legalEntity": "Nace AI, Inc.",
        "domain": "nace.ai",
        "domainRegistered": "",
        "endpointOnVendorDomain": true,
        "terms": "https://www.nace.ai/policies/terms-of-service",
        "privacy": "https://www.nace.ai/policies/privacy-policy",
        "statusPage": "https://status.nace.ai/",
        "changelog": "",
        "securityTxt": "valid",
        "checked": "2026-10-10",
        "notes": [
          "The Terms were last updated 5 May 2026, before Drex was released, and no Drex-specific service terms were found.",
          "The security.txt expires on 9 October 2027. The console changelog URL returned 500 and nace.ai/changelog returned 404.",
          "The Hugging Face cardData field marks the repository as private, while the Hub API returns it as public and the files download without an account."
        ],
        "score": 75
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/nace-drex.json",
      "live": {
        "slug": "nace-drex",
        "probe": {
          "target": "https://console.nace.ai/v1/systemone",
          "method": "get",
          "lastAt": "2026-10-10T13:02:21.179574177Z",
          "lastOk": true,
          "lastStatus": 405,
          "lastMs": 294,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 208,
          "p95ms24h": 294,
          "samples24h": 21,
          "samples30d": 21,
          "days": [
            {
              "date": "2026-10-10",
              "probes": 21,
              "ok": 21
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.nace.ai",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-10T11:53:13.006193955Z"
        },
        "updatedAt": "2026-10-10T13:02:21.179574177Z"
      }
    },
    "facts": [
      {
        "a": "Model API",
        "b": "Model API",
        "name": "Kind"
      },
      {
        "a": "Knowledgator",
        "b": "Nace AI, Inc. (Nace.AI)",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "https://console.nace.ai/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": "Hosted API under the Nace AI Terms of Service, last updated 5 May 2026. Weights under the Nace AI Open RAIL-M licence (modified, version 1.0, October 2026), which is not an open-source licence. Businesses above $1 million in revenue or funding need a separate commercial licence, and competing products are excluded. The bundled code/kev package, derived from Jared Palmer's Kev (https://github.com/jaredpalmer/kev), and the GitHub repository are Apache-2.0, and the agent skill is MIT.",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-07-21",
        "b": "2026-09-28",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "",
        "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": "318 npm/wk, 156 PyPI/wk",
        "name": "Popularity"
      }
    ],
    "faq": [
      {
        "answer": "Drex 1.5 scores 69.7 (B) on agent readiness against GLiClass's 49.9 (D), and leads in 5 of 7 scored categories. GLiClass leads on payments \u0026 pricing.",
        "question": "Which is better for AI agents, GLiClass or Drex 1.5?"
      },
      {
        "answer": "GLiClass needs no key. Drex 1.5 needs an API key.",
        "question": "Do GLiClass and Drex 1.5 need an API key?"
      },
      {
        "answer": "No hosted endpoint is listed for GLiClass. Drex 1.5 has a hosted endpoint at https://console.nace.ai/v1/systemone.",
        "question": "Can an agent call GLiClass and Drex 1.5 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 Drex 1.5.",
        "question": "Are GLiClass and Drex 1.5 open source?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Payments \u0026 pricing, 60 against 40"
        ],
        "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": [
          "Reliability, 80 against 43",
          "Schema \u0026 documentation, 88 against 49",
          "Agent ergonomics, 85 against 60",
          "Security \u0026 auth, 65 against 38",
          "Maintenance \u0026 community, 65 against 44"
        ],
        "also": [
          "A hosted endpoint, with nothing to install"
        ],
        "goodFor": "Routing, triage and yes or no gates inside an agent, where the caller supplies the options and acts on the probabilities. Suited to hosted use at a low per-token price, or to open weights where the licence fits.",
        "slug": "nace-drex",
        "watchFor": "The rank 1 claim comes from Nace's own run on Decision Index 0.3.1, and Drex is not on the public board for 0.3 or 0.2.1."
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      {
        "json": "https://www.anchorterminal.com/compare/celeris-1-decision-vs-nace-drex.json",
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        "json": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-gliclass.json",
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        "url": "https://www.anchorterminal.com/compare/cloudflare-clef-vs-nace-drex"
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      {
        "json": "https://www.anchorterminal.com/compare/convai-laya-vs-gliclass.json",
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      {
        "json": "https://www.anchorterminal.com/compare/convai-laya-vs-nace-drex.json",
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        "url": "https://www.anchorterminal.com/compare/convai-laya-vs-nace-drex"
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        "json": "https://www.anchorterminal.com/compare/decider-vs-gliclass.json",
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        "json": "https://www.anchorterminal.com/compare/decider-vs-nace-drex.json",
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        "url": "https://www.anchorterminal.com/compare/gliclass-vs-jaredpalmer-kev"
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        "json": "https://www.anchorterminal.com/compare/gliclass-vs-liquid-d1.json",
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        "url": "https://www.anchorterminal.com/compare/gliclass-vs-vela"
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        "json": "https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-nace-drex.json",
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        "json": "https://www.anchorterminal.com/compare/microsoft-decision-1-vs-nace-drex.json",
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      {
        "by": 37,
        "edge": "nace-drex",
        "gliclass": 43,
        "key": "reliability",
        "nace-drex": 80,
        "name": "Reliability",
        "weight": 16
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      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
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      {
        "by": 39,
        "edge": "nace-drex",
        "gliclass": 49,
        "key": "schema",
        "nace-drex": 88,
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "by": 25,
        "edge": "nace-drex",
        "gliclass": 60,
        "key": "ergonomics",
        "nace-drex": 85,
        "name": "Agent ergonomics",
        "weight": 13
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      {
        "by": 27,
        "edge": "nace-drex",
        "gliclass": 38,
        "key": "security",
        "nace-drex": 65,
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "by": 20,
        "edge": "gliclass",
        "gliclass": 60,
        "key": "payments",
        "nace-drex": 40,
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 21,
        "edge": "nace-drex",
        "gliclass": 44,
        "key": "maintenance",
        "nace-drex": 65,
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "by": 1,
        "edge": "gliclass",
        "gliclass": 64,
        "key": "transparency",
        "nace-drex": 63,
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
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    "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.",
      "nace-drex": "The hosted endpoint has a public OpenAPI document, published limits and pinned model versions, at $0.05 per million input tokens with no output charge. The #1 under 10B claim rests on Nace's own run, since Drex is absent from both public boards. Weights carry Open RAIL-M, which requires a commercial licence above $1 million in revenue or funding."
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  "markdown": "Drex 1.5 scores 69.7 (B) on agent readiness against GLiClass's 49.9 (D), and leads in 5 of 7 scored categories. GLiClass leads on payments \u0026 pricing. Both do decision models.\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- Drex 1.5: grade B, 69.7/100, rank #172 of 954. Markdown https://www.anchorterminal.com/tools/nace-drex.md · JSON https://www.anchorterminal.com/api/v1/tools/nace-drex.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- Payments \u0026 pricing, 60 against 40\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### Drex 1.5 (B)\n\nGood for: Routing, triage and yes or no gates inside an agent, where the caller supplies the options and acts on the probabilities. Suited to hosted use at a low per-token price, or to open weights where the licence fits.\n\nAhead on:\n- Reliability, 80 against 43\n- Schema \u0026 documentation, 88 against 49\n- Agent ergonomics, 85 against 60\n- Security \u0026 auth, 65 against 38\n- Maintenance \u0026 community, 65 against 44\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: The rank 1 claim comes from Nace's own run on Decision Index 0.3.1, and Drex is not on the public board for 0.3 or 0.2.1.\n\n\n## Score by category\n\n| Category | Weight | GLiClass | Drex 1.5 | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 43 | 80 | Drex 1.5 +37 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 49 | 88 | Drex 1.5 +39 |\n| Agent ergonomics | 13% (16.2 this run) | 60 | 85 | Drex 1.5 +25 |\n| Security \u0026 auth | 14% (17.5 this run) | 38 | 65 | Drex 1.5 +27 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 40 | GLiClass +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 44 | 65 | Drex 1.5 +21 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 64 | 63 | GLiClass +1 |\n| Negative events | ≤15 | 0 | -2 | |\n| **Total** | | **49.9 · D** | **69.7 · B** | |\n\n## Facts side by side\n\n| Fact | GLiClass | Drex 1.5 |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Knowledgator | Nace AI, Inc. (Nace.AI) |\n| Hosted endpoint | no (local only) | `https://console.nace.ai/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) | Hosted API under the Nace AI Terms of Service, last updated 5 May 2026. Weights under the Nace AI Open RAIL-M licence (modified, version 1.0, October 2026), which is not an open-source licence. Businesses above $1 million in revenue or funding need a separate commercial licence, and competing products are excluded. The bundled code/kev package, derived from Jared Palmer's Kev (https://github.com/jaredpalmer/kev), and the GitHub repository are Apache-2.0, and the agent skill is MIT. |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-07-21 | 2026-09-28 |\n| Terms last updated | 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 | 318 npm/wk, 156 PyPI/wk |\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**Drex 1.5.** The hosted endpoint has a public OpenAPI document, published limits and pinned model versions, at $0.05 per million input tokens with no output charge. The #1 under 10B claim rests on Nace's own run, since Drex is absent from both public boards. Weights carry Open RAIL-M, which requires a commercial licence above $1 million in revenue or funding.\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### Drex 1.5\n\n1. Call https://console.nace.ai/v1/systemone with Authorization: Bearer nace_sk_..., and pin model drex-v1.5 rather than drex-latest in production.\n2. Stop on 402 insufficient_credit or 402 payment_required until credit is topped up or the unpaid invoice is paid.\n3. Retry 429 and 529 after retry-after-ms. On a 422 for an unknown model, use one of the ids the error message lists.\n4. Keep state below 131,072 tokens and the body below 1,048,576 bytes, and send at most 512 questions per request.\n5. Keep the key on a server. A key in browser code is exposed, and the /v1 routes send no Access-Control-Allow-Origin header.\n6. Check usage.input_tokens and the usage CSV after retries, since /v1/systemone documents no idempotency key.\n\n## Questions\n\n### Which is better for AI agents, GLiClass or Drex 1.5?\n\nDrex 1.5 scores 69.7 (B) on agent readiness against GLiClass's 49.9 (D), and leads in 5 of 7 scored categories. GLiClass leads on payments \u0026 pricing.\n\n### Do GLiClass and Drex 1.5 need an API key?\n\nGLiClass needs no key. Drex 1.5 needs an API key.\n\n### Can an agent call GLiClass and Drex 1.5 without installing anything?\n\nNo hosted endpoint is listed for GLiClass. Drex 1.5 has a hosted endpoint at https://console.nace.ai/v1/systemone.\n\n### Are GLiClass and Drex 1.5 open source?\n\nGLiClass is open source (Apache-2.0 (library and the model weights we checked)). No open-source release is listed for Drex 1.5.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/gliclass-vs-nace-drex.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gliclass-vs-nace-drex.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gliclass\", \"b\": \"nace-drex\"}`. From a terminal: `anchor compare gliclass nace-drex`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gliclass.json and https://www.anchorterminal.com/api/v1/tools/nace-drex.json\n\n## Other comparisons with GLiClass or Drex 1.5\n\n- [Celeris-1 Decision vs GLiClass](https://www.anchorterminal.com/compare/celeris-1-decision-vs-gliclass.md)\n- [Celeris-1 Decision vs Drex 1.5](https://www.anchorterminal.com/compare/celeris-1-decision-vs-nace-drex.md)\n- [Clef vs GLiClass](https://www.anchorterminal.com/compare/cloudflare-clef-vs-gliclass.md)\n- [Clef vs Drex 1.5](https://www.anchorterminal.com/compare/cloudflare-clef-vs-nace-drex.md)\n- [Laya vs GLiClass](https://www.anchorterminal.com/compare/convai-laya-vs-gliclass.md)\n- [Laya vs Drex 1.5](https://www.anchorterminal.com/compare/convai-laya-vs-nace-drex.md)\n- [Decider vs GLiClass](https://www.anchorterminal.com/compare/decider-vs-gliclass.md)\n- [Decider vs Drex 1.5](https://www.anchorterminal.com/compare/decider-vs-nace-drex.md)\n- [GLiClass vs Kev](https://www.anchorterminal.com/compare/gliclass-vs-jaredpalmer-kev.md)\n- [GLiClass vs Liquid d1](https://www.anchorterminal.com/compare/gliclass-vs-liquid-d1.md)\n- [GLiClass vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/gliclass-vs-microsoft-decision-1.md)\n- [GLiClass vs 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 Drex 1.5](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-nace-drex.md)\n- [Liquid d1 vs Drex 1.5](https://www.anchorterminal.com/compare/liquid-d1-vs-nace-drex.md)\n- [Microsoft-Decision-1 vs Drex 1.5](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-nace-drex.md)\n- [Drex 1.5 vs OpenAI Decisions API](https://www.anchorterminal.com/compare/nace-drex-vs-openai-decisions-api.md)\n- [Drex 1.5 vs pplx-decider](https://www.anchorterminal.com/compare/nace-drex-vs-pplx-decider.md)\n- [Drex 1.5 vs Strands Decider 2B](https://www.anchorterminal.com/compare/nace-drex-vs-strands-decider.md)\n- [Drex 1.5 vs Jev](https://www.anchorterminal.com/compare/nace-drex-vs-typesafe-jev.md)\n- [Drex 1.5 vs Vela 2.0](https://www.anchorterminal.com/compare/nace-drex-vs-vela.md)\n",
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