{
  "data": {
    "a": {
      "slug": "hugging-face-inference-endpoints",
      "name": "Hugging Face Inference Endpoints",
      "vendor": "Hugging Face, Inc.",
      "vendorUrl": "https://huggingface.co",
      "kind": "http-api",
      "category": "gpu-compute",
      "summary": "Managed Hugging Face service that deploys a Hub model as a dedicated, autoscaling HTTPS endpoint on AWS, Azure or Google Cloud, using vLLM, TGI, SGLang, llama.cpp, TEI or a custom container. Managed by REST API, Python client, CLI or MCP.",
      "url": "https://www.anchorterminal.com/tools/hugging-face-inference-endpoints",
      "markdownUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-endpoints.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-endpoints.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-endpoints.json",
      "repo": "https://github.com/huggingface/hf-endpoints-documentation",
      "license": "Proprietary service under the Hugging Face Terms of Service. The `huggingface_hub` Python client and CLI are Apache-2.0",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://api.endpoints.huggingface.cloud",
      "packages": [
        {
          "registry": "pypi",
          "name": "huggingface_hub"
        }
      ],
      "auth": "mixed",
      "authNotes": "Hugging Face access token sent as `Authorization: Bearer $HF_TOKEN` to the management API and to each endpoint. Tokens are created in the account settings in a browser and can be fine-grained, read or write. The MCP server uses OAuth through huggingface.co (authorisation code with PKCE, device code, dynamic client registration) with `read-endpoints` and `write-endpoints` scopes. `GET /v2/provider` and the catalogue list need no token. Access is self-serve, with quota requests for larger instances.",
      "pricing": "usage",
      "pricingNotes": "Usage priced by instance hour, billed per minute while a replica is initialising or running. GPUs run from $0.50 an hour (T4) to $10 (H100 on GCP), CPUs from $0.033. No free tier or trial was found. The docs require a payment method and credits before deploying, and the pricing page says an active subscription. Paused endpoints and endpoints at zero replicas aren't billed for compute (https://huggingface.co/docs/inference-endpoints/support/pricing).",
      "priceSummary": "$0.033 / vCPU-hr",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the Inference Endpoints docs, the two OpenAPI documents or the pricing page (checked 2026-10-08).",
        "endpoints": []
      },
      "toolCount": 19,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": 60014944,
        "asOf": "2026-10-08"
      },
      "docsUrl": "https://huggingface.co/docs/inference-endpoints/index",
      "llmsTxt": "https://huggingface.co/docs/inference-endpoints/llms.txt",
      "openapi": "https://api.endpoints.huggingface.cloud/openapi.json",
      "capabilities": [
        "compute.gpu",
        "compute.endpoints",
        "compute.containers"
      ],
      "tags": [
        "hosted",
        "usage-priced",
        "python",
        "cli",
        "mcp",
        "oauth",
        "openapi",
        "llms-txt",
        "status-page",
        "soc2",
        "enterprise"
      ],
      "lastRelease": "2026-10-08",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 64.5,
        "grade": "B",
        "agentReady": false,
        "rank": 314,
        "ranked": true,
        "rankOf": 842,
        "categoryRank": 3,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 62,
          "maintenance": 80,
          "payments": 20,
          "reliability": 63,
          "schema": 73,
          "security": 83,
          "transparency": 68
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-08"
        },
        "negative": 0,
        "verdict": "OAuth scopes separate reading endpoints from writing them, both OpenAPI documents are public, and the unauthenticated `/v2/provider` route lists every instance with its hourly price. An account needs a payment method and credits before the first deployment, no rate limits or SLA were found for the management API, and the docs price table disagrees with the live list in places.",
        "bestFor": "Teams whose models already live on the Hugging Face Hub and who want a dedicated endpoint on a named cloud and region with standard open-source engines.",
        "strengths": [
          "Public OpenAPI 3.1 documents for the management API (46 operations) and the catalogue API (3), plus llms.txt and a Markdown twin of every docs page",
          "The MCP server at endpoints.huggingface.co/mcp uses OAuth with `read-endpoints` and `write-endpoints` scopes, PKCE and dynamic client registration",
          "`GET /v2/provider` needs no token and returns each instance type by cloud and region with status and price per hour",
          "The MCP `delete_endpoint` tool returns a preview and deletes only on a second call with `confirm: true`",
          "The Inference Endpoints API component on status.huggingface.co shows 100 per cent uptime over the 90 days to 8 October 2026"
        ],
        "weaknesses": [
          "No free tier. The docs require a payment method and credits, and replicas are billed while initialising as well as running",
          "No rate limits, SLA or idempotency keys were found for the management API, and its OpenAPI document lists only 200 responses on 43 of 46 operations",
          "The docs price table and the live provider list disagree. Inferentia2 x1 is $0.75 in the docs and $1.95 in the API, and AWS H200 is listed in the docs and marked deprecated in the API",
          "A start from zero replicas takes minutes by the docs' own account, and the proxy answers 503 until a replica is ready",
          "The Hub outage of 16 July 2026 took the Inference Endpoints UI down for 1 hour 37 minutes"
        ],
        "agentNotes": [
          "Call `GET https://api.endpoints.huggingface.cloud/v2/provider` first and pick an instance whose `status` is `available`. The docs table lists types the API marks deprecated or not available",
          "Send `X-Scale-Up-Timeout: 600` on requests to an endpoint that scales to zero, or handle 503 while the first replica starts",
          "Set `scaleToZeroTimeout` yourself. The docs give a default of 1 hour and the OpenAPI document says 15 minutes",
          "Pause or delete an endpoint when the job is done. Billing covers every minute a replica is initialising or running",
          "Give the agent a fine-grained token or the `read-endpoints` scope unless it must deploy. Endpoints are private by default and take the same Hugging Face token as a bearer"
        ],
        "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": 64.5
          }
        ],
        "editorialScores": {
          "ergonomics": 62,
          "maintenance": 80,
          "payments": 20,
          "reliability": 63,
          "schema": 73,
          "security": 83,
          "transparency": 68
        },
        "provenanceScore": 67
      },
      "connect": {
        "install": "pip install huggingface_hub",
        "http": "curl \"https://api.endpoints.huggingface.cloud/v2/endpoint/$NAMESPACE\" \\\n  -H \"Authorization: Bearer $HF_TOKEN\""
      },
      "letme": {
        "capability": "https://letme.dev/compute.gpu",
        "tool": "https://letme.dev/hugging-face-inference-endpoints"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "NVIDIA T4 16 GB x1 (AWS, GCP)",
          "unit": "gpu-hour",
          "usd": 0.5,
          "note": "Billed per minute while initialising or running"
        },
        {
          "item": "NVIDIA L4 24 GB x1 (AWS)",
          "unit": "gpu-hour",
          "usd": 0.8,
          "note": "$0.70 on GCP us-east4"
        },
        {
          "item": "NVIDIA A10G 24 GB x1 (AWS)",
          "unit": "gpu-hour",
          "usd": 1,
          "note": "us-east-1 and eu-west-1"
        },
        {
          "item": "NVIDIA L40S 48 GB x1 (AWS)",
          "unit": "gpu-hour",
          "usd": 1.8,
          "note": "us-east-1"
        },
        {
          "item": "NVIDIA A100 80 GB x1 (AWS)",
          "unit": "gpu-hour",
          "usd": 2.5,
          "note": "$3.60 on GCP us-east4"
        },
        {
          "item": "NVIDIA RTX PRO 6000 Blackwell 96 GB x1 (AWS)",
          "unit": "gpu-hour",
          "usd": 2.75,
          "note": "us-east-2, in the live provider list and absent from the docs table"
        },
        {
          "item": "NVIDIA H200 141 GB x1 (GCP)",
          "unit": "gpu-hour",
          "usd": 5,
          "note": "us-south1. The AWS H200 in us-west-2 is marked deprecated in the API"
        },
        {
          "item": "NVIDIA H100 80 GB x1 (GCP)",
          "unit": "gpu-hour",
          "usd": 10,
          "note": "us-east4. The AWS H100 at $4.50 is deprecated from December 2025"
        },
        {
          "item": "Intel Sapphire Rapids x1, 1 vCPU and 2 GB (AWS)",
          "unit": "vcpu-hour",
          "usd": 0.033,
          "note": "$0.050 on GCP and $0.060 on Azure Intel Xeon"
        }
      ],
      "provenance": {
        "legalEntity": "Hugging Face, Inc.",
        "domain": "huggingface.co",
        "domainRegistered": "",
        "endpointOnVendorDomain": false,
        "terms": "https://huggingface.co/terms-of-service",
        "privacy": "https://huggingface.co/privacy",
        "statusPage": "https://status.huggingface.co",
        "changelog": "https://huggingface.co/changelog",
        "securityTxt": "valid",
        "checked": "2026-10-08",
        "notes": [
          "The Terms of Service (effective 15 September 2022) name Hugging Face, Inc., a Delaware corporation, list Inference Endpoints among the services they cover and are governed by New York law. They link Supplemental Terms (effective 28 April 2025) as a PDF, of which our reader extracted only the first page.",
          "The privacy policy (effective 28 March 2023) names Hugging Face, Inc. and its EU establishment Hugging Face, SAS, 9 rue des Colonnes, 75002 Paris, and lists 11 subprocessors with countries. The Inference Endpoints security page points to it.",
          "The management API answers at api.endpoints.huggingface.cloud and deployed endpoints at subdomains of endpoints.huggingface.cloud, a second domain of the vendor's. The catalogue API and the MCP server are on endpoints.huggingface.co.",
          "huggingface.co/.well-known/security.txt gives security@huggingface.co and expires on 1 July 2030. endpoints.huggingface.co/.well-known/security.txt returns 404.",
          "status.huggingface.co is a Better Stack page with separate components for the Inference Endpoints UI and API.",
          "The changelog at huggingface.co/changelog covers the whole Hub. Inference Endpoints has no changelog of its own. Dated changes are in the docs repository's commit history.",
          "rdap.org returned 404 for huggingface.co, so the registration date is unrecorded."
        ],
        "score": 67
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-endpoints.json",
      "live": {
        "slug": "hugging-face-inference-endpoints",
        "probe": {
          "target": "https://api.endpoints.huggingface.cloud",
          "method": "get",
          "lastAt": "2026-10-09T10:42:45.525175216Z",
          "lastOk": true,
          "lastStatus": 200,
          "lastMs": 266,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 255,
          "p95ms24h": 295,
          "samples24h": 33,
          "samples30d": 33,
          "days": [
            {
              "date": "2026-10-09",
              "probes": 33,
              "ok": 33
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.huggingface.co",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-09T07:58:03.654181492Z"
        },
        "updatedAt": "2026-10-09T10:42:45.525175216Z"
      }
    },
    "answer": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Koyeb's 46.5 (D), and leads in 6 of 7 scored categories.",
    "b": {
      "slug": "koyeb",
      "name": "Koyeb",
      "vendor": "Koyeb",
      "vendorUrl": "https://www.koyeb.com",
      "kind": "platform",
      "category": "gpu-compute",
      "summary": "Serverless platform for deploying applications and containers on CPU or GPU instances, with autoscaling and an API.",
      "url": "https://www.anchorterminal.com/tools/koyeb",
      "markdownUrl": "https://www.anchorterminal.com/tools/koyeb.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/koyeb.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/koyeb.json",
      "repo": "https://github.com/koyeb/koyeb-cli",
      "license": "Apache-2.0",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://app.koyeb.com/v1",
      "packages": [],
      "auth": "pat",
      "authNotes": "Personal access token created in the control panel (app.koyeb.com/user/settings/api) and sent as `Authorization: Bearer` to app.koyeb.com/v1. The CLI stores it from `koyeb login` and hides it in debug output. Organisation-scoped tokens can be created for teams.",
      "pricing": "freemium",
      "pricingNotes": "Pro is $29 a month with $10 of usage included, Scale $299 with $100, Enterprise custom. The Starter plan closed to new sign-ups after the Mistral AI agreement. Everything bills per second. GPUs an hour are RTX 4000 SFF Ada $0.50, L4 $0.70, RTX A6000 $0.75, L40S $1.20, A100 $1.60, A100 SXM $2.15, RTX PRO 6000 $2.20, H100 $2.50, H200 $3.00, 2x A100 $3.20, 2x H100 $5.00, 4x A100 $6.40, 8x H100 $20.00, 8x H200 $24.00. CPU services start at $0.000006 a second (https://www.koyeb.com/pricing, https://www.koyeb.com/blog/koyeb-is-joining-mistral-ai-to-build-the-future-of-ai-infrastructure).",
      "priceSummary": "$29 / mo",
      "where": "hosted",
      "x402": {
        "level": "no",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 72,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-09-30"
      },
      "docsUrl": "https://www.koyeb.com/docs",
      "capabilities": [
        "compute.gpu",
        "compute.serverless",
        "compute.endpoints",
        "compute.containers"
      ],
      "tags": [
        "hosted",
        "freemium",
        "eu",
        "enterprise"
      ],
      "lastRelease": "2026-05-12",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 46.5,
        "grade": "D",
        "agentReady": false,
        "rank": 755,
        "ranked": true,
        "rankOf": 842,
        "categoryRank": 16,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 56,
          "maintenance": 23,
          "payments": 20,
          "reliability": 60,
          "schema": 41,
          "security": 50,
          "transparency": 63
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-01"
        },
        "negative": 0,
        "verdict": "H100 at $2.50 and H200 at $3.00 an hour, billed per second. Changelog silent since 27 February 2026 and no CLI release since 12 May 2026.",
        "bestFor": "Teams that want cheap H100 or H200 containers with scale to zero and an SLA, deployed from Git or an image without a vendor SDK.",
        "strengths": [
          "H100 at $2.50 and H200 at $3.00 an hour, billed per second",
          "Scale to zero after 5 idle minutes by default, configurable up to 12 hours on higher plans",
          "99.9 per cent uptime SLA published from the Pro plan",
          "List endpoints filter by name, type, status and region with `limit` and `offset`, and create and update take `dry_run`",
          "French company under French law with a published DPA"
        ],
        "weaknesses": [
          "Changelog silent since 27 February 2026 and no CLI release since 12 May 2026",
          "No free compute tier; Starter closed after the Mistral AI agreement",
          "No llms.txt, no downloadable OpenAPI file, no documented rate limits or error codes",
          "Audit logs and RBAC only on Enterprise, and tokens have no scopes",
          "Platform due to fold into Mistral Compute with no dated migration plan"
        ],
        "agentNotes": [
          "Pass `dry_run` on service create or update to validate the definition before anything deploys",
          "Page service lists with `limit` and `offset` and filter by `statuses` instead of fetching everything",
          "Expect the first request after deep sleep to take 1 to 5 seconds and retry once with a timeout",
          "Set `--min-scale 0` on GPU services so idle instances stop billing",
          "Re-check the Mistral transition before building anything long-lived on it"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 3.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "D",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 46.5
          }
        ],
        "editorialScores": {
          "ergonomics": 56,
          "maintenance": 23,
          "payments": 20,
          "reliability": 60,
          "schema": 41,
          "security": 50,
          "transparency": 50
        },
        "provenanceScore": 75
      },
      "connect": {
        "install": "brew install koyeb/tap/koyeb \u0026\u0026 koyeb login  # or go install github.com/koyeb/koyeb-cli/cmd/koyeb",
        "http": "curl \"https://app.koyeb.com/v1/services\" -H \"Authorization: Bearer $KOYEB_TOKEN\""
      },
      "letme": {
        "capability": "https://letme.dev/compute.gpu",
        "tool": "https://letme.dev/koyeb"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "H100 80 GB",
          "unit": "gpu-hour",
          "usd": 2.5
        },
        {
          "item": "H200 141 GB",
          "unit": "gpu-hour",
          "usd": 3
        },
        {
          "item": "A100 80 GB",
          "unit": "gpu-hour",
          "usd": 1.6
        },
        {
          "item": "RTX PRO 6000",
          "unit": "gpu-hour",
          "usd": 2.2
        },
        {
          "item": "L40S 48 GB",
          "unit": "gpu-hour",
          "usd": 1.2
        },
        {
          "item": "L4 24 GB",
          "unit": "gpu-hour",
          "usd": 0.7
        },
        {
          "item": "Pro plan",
          "unit": "month",
          "usd": 29,
          "note": "$10 of usage included"
        },
        {
          "item": "Scale plan",
          "unit": "month",
          "usd": 299,
          "note": "$100 of usage included"
        }
      ],
      "provenance": {
        "legalEntity": "Koyeb SAS",
        "domain": "koyeb.com",
        "domainRegistered": "2019-03-11",
        "endpointOnVendorDomain": true,
        "terms": "https://www.koyeb.com/docs/legal/terms",
        "privacy": "https://www.koyeb.com/docs/legal/data-processing-agreement",
        "statusPage": "https://status.koyeb.com",
        "changelog": "https://www.koyeb.com/changelog",
        "securityTxt": "none",
        "checked": "2026-09-30",
        "notes": [
          "The Master Services Agreement of 28 June 2024 names Koyeb, a simplified joint-stock company registered in Nanterre under 850 183 948, at 9 rue des Longs Prés, Boulogne-Billancourt, under French law.",
          "The site footer's privacy link points at the data processing agreement rather than a separate privacy policy.",
          "www.koyeb.com/.well-known/security.txt returns 404 and there's no llms.txt at www.koyeb.com or under /docs.",
          "Koyeb announced on 17 February 2026 that it is joining Mistral AI."
        ],
        "score": 75
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/koyeb.json",
      "live": {
        "slug": "koyeb",
        "probe": {
          "target": "https://app.koyeb.com/v1",
          "method": "get",
          "lastAt": "2026-10-09T10:42:46.700822838Z",
          "lastOk": true,
          "lastStatus": 200,
          "lastMs": 75,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 68,
          "p95ms24h": 118,
          "samples24h": 260,
          "samples30d": 2098,
          "days": [
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              "date": "2026-10-01",
              "probes": 109,
              "ok": 109
            },
            {
              "date": "2026-10-02",
              "probes": 248,
              "ok": 248
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            {
              "date": "2026-10-03",
              "probes": 271,
              "ok": 271
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            {
              "date": "2026-10-04",
              "probes": 272,
              "ok": 272
            },
            {
              "date": "2026-10-05",
              "probes": 272,
              "ok": 272
            },
            {
              "date": "2026-10-06",
              "probes": 272,
              "ok": 272
            },
            {
              "date": "2026-10-07",
              "probes": 272,
              "ok": 272
            },
            {
              "date": "2026-10-08",
              "probes": 268,
              "ok": 268
            },
            {
              "date": "2026-10-09",
              "probes": 114,
              "ok": 114
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.koyeb.com",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-09T07:58:06.915098843Z"
        },
        "versions": [
          {
            "registry": "github",
            "name": "koyeb/koyeb-cli",
            "version": "v5.12.0",
            "released": "2026-09-16",
            "seenAt": "2026-10-08T16:18:01.679616884Z"
          }
        ],
        "githubStars": 75,
        "securityTxt": {
          "url": "https://koyeb.com/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-08T15:38:33.165001961Z"
        },
        "domain": {
          "domain": "koyeb.com",
          "registered": "2019-03-11",
          "source": "https://rdap.verisign.com/com/v1/domain/koyeb.com",
          "checkedAt": "2026-10-04T13:09:21.713025238Z"
        },
        "pages": [
          {
            "url": "https://www.koyeb.com/changelog",
            "kind": "changelog",
            "status": 304,
            "checkedAt": "2026-10-08T18:28:38.583332732Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "7e4e89b36b63"
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          {
            "url": "https://www.koyeb.com/pricing",
            "kind": "pricing",
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            "checkedAt": "2026-10-08T18:28:44.671933232Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "9d7cf517fa78"
          },
          {
            "url": "https://www.koyeb.com/docs/legal/data-processing-agreement",
            "kind": "privacy",
            "status": 304,
            "checkedAt": "2026-10-08T18:28:40.700270182Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "6e08cc6e8919"
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          {
            "url": "https://www.koyeb.com/docs/legal/terms",
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        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-vast-ai"
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        "url": "https://www.anchorterminal.com/compare/koyeb-vs-thunder-compute"
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        "json": "https://www.anchorterminal.com/compare/koyeb-vs-vast-ai.json",
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        "hugging-face-inference-endpoints": 63,
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        "koyeb": 60,
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        "weight": 16
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      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
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      {
        "by": 32,
        "edge": "hugging-face-inference-endpoints",
        "hugging-face-inference-endpoints": 73,
        "key": "schema",
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        "name": "Schema \u0026 documentation",
        "weight": 13
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        "edge": "hugging-face-inference-endpoints",
        "hugging-face-inference-endpoints": 62,
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        "name": "Agent ergonomics",
        "weight": 13
      },
      {
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        "edge": "hugging-face-inference-endpoints",
        "hugging-face-inference-endpoints": 83,
        "key": "security",
        "koyeb": 50,
        "name": "Security \u0026 auth",
        "weight": 14
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        "hugging-face-inference-endpoints": 20,
        "key": "payments",
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        "weight": 10
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        "name": "Task success",
        "pending": true,
        "weight": 10
      },
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        "by": 57,
        "edge": "hugging-face-inference-endpoints",
        "hugging-face-inference-endpoints": 80,
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        "koyeb": 23,
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        "weight": 7
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        "edge": "hugging-face-inference-endpoints",
        "hugging-face-inference-endpoints": 68,
        "key": "transparency",
        "koyeb": 63,
        "name": "Transparency \u0026 trust",
        "weight": 7
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    "summary": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Koyeb's 46.5 (D), and leads in 6 of 7 scored categories. Both do compute gpu.",
    "verdicts": {
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      "koyeb": "H100 at $2.50 and H200 at $3.00 an hour, billed per second. Changelog silent since 27 February 2026 and no CLI release since 12 May 2026."
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  "markdown": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Koyeb's 46.5 (D), and leads in 6 of 7 scored categories. Both do compute gpu.\n\n- Hugging Face Inference Endpoints: grade B, 64.5/100, rank #314 of 842. Markdown https://www.anchorterminal.com/tools/hugging-face-inference-endpoints.md · JSON https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-endpoints.json\n- Koyeb: grade D, 46.5/100, rank #755 of 842. Markdown https://www.anchorterminal.com/tools/koyeb.md · JSON https://www.anchorterminal.com/api/v1/tools/koyeb.json\n\n## Which one, for what\n\n### Hugging Face Inference Endpoints (B)\n\nGood for: Teams whose models already live on the Hugging Face Hub and who want a dedicated endpoint on a named cloud and region with standard open-source engines.\n\nAhead on:\n- Schema \u0026 documentation, 73 against 41\n- Agent ergonomics, 62 against 56\n- Security \u0026 auth, 83 against 50\n- Maintenance \u0026 community, 80 against 23\n- Transparency \u0026 trust, 68 against 63\n\nWatch for: No free tier. The docs require a payment method and credits, and replicas are billed while initialising as well as running\n\n### Koyeb (D)\n\nGood for: Teams that want cheap H100 or H200 containers with scale to zero and an SLA, deployed from Git or an image without a vendor SDK.\n\nWatch for: Changelog silent since 27 February 2026 and no CLI release since 12 May 2026\n\n\n## Score by category\n\n| Category | Weight | Hugging Face Inference Endpoints | Koyeb | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 63 | 60 | Hugging Face Inference Endpoints +3 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 73 | 41 | Hugging Face Inference Endpoints +32 |\n| Agent ergonomics | 13% (16.2 this run) | 62 | 56 | Hugging Face Inference Endpoints +6 |\n| Security \u0026 auth | 14% (17.5 this run) | 83 | 50 | Hugging Face Inference Endpoints +33 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 20 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 80 | 23 | Hugging Face Inference Endpoints +57 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 68 | 63 | Hugging Face Inference Endpoints +5 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **64.5 · B** | **46.5 · D** | |\n\n## Facts side by side\n\n| Fact | Hugging Face Inference Endpoints | Koyeb |\n| --- | --- | --- |\n| Kind | HTTP API | Model platform |\n| Vendor | Hugging Face, Inc. | Koyeb |\n| Hosted endpoint | `https://api.endpoints.huggingface.cloud` | `https://app.koyeb.com/v1` |\n| Transports | HTTP | HTTP |\n| Auth | OAuth or key | Token |\n| Pricing | Pay per use | Freemium |\n| x402 | no | no |\n| Licence | Proprietary service under the Hugging Face Terms of Service. The `huggingface_hub` Python client and CLI are Apache-2.0 | Apache-2.0 |\n| Tools exposed | 19 | none |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| Last release | 2026-10-08 | 2026-05-12 |\n| Terms last updated | 2022-09-15 | no date given |\n| Privacy policy last updated | 2023-03-28 | no date given |\n| Customer content may train models | not found in the text | not found in the text |\n| Terms restrict automated access | not found in the text | yes |\n| Terms restrict benchmarking | not found in the text | not found in the text |\n| Terms or service can change without notice | yes | yes |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Popularity | 60M PyPI/wk | 72 stars |\n| Agent reviews | none | 3.5/5 (2) |\n\n## Verdicts\n\n**Hugging Face Inference Endpoints.** OAuth scopes separate reading endpoints from writing them, both OpenAPI documents are public, and the unauthenticated `/v2/provider` route lists every instance with its hourly price. An account needs a payment method and credits before the first deployment, no rate limits or SLA were found for the management API, and the docs price table disagrees with the live list in places.\n\n**Koyeb.** H100 at $2.50 and H200 at $3.00 an hour, billed per second. Changelog silent since 27 February 2026 and no CLI release since 12 May 2026.\n\n## Before you call either\n\n### Hugging Face Inference Endpoints\n\n1. Call `GET https://api.endpoints.huggingface.cloud/v2/provider` first and pick an instance whose `status` is `available`. The docs table lists types the API marks deprecated or not available\n2. Send `X-Scale-Up-Timeout: 600` on requests to an endpoint that scales to zero, or handle 503 while the first replica starts\n3. Set `scaleToZeroTimeout` yourself. The docs give a default of 1 hour and the OpenAPI document says 15 minutes\n4. Pause or delete an endpoint when the job is done. Billing covers every minute a replica is initialising or running\n5. Give the agent a fine-grained token or the `read-endpoints` scope unless it must deploy. Endpoints are private by default and take the same Hugging Face token as a bearer\n\n### Koyeb\n\n1. Pass `dry_run` on service create or update to validate the definition before anything deploys\n2. Page service lists with `limit` and `offset` and filter by `statuses` instead of fetching everything\n3. Expect the first request after deep sleep to take 1 to 5 seconds and retry once with a timeout\n4. Set `--min-scale 0` on GPU services so idle instances stop billing\n5. Re-check the Mistral transition before building anything long-lived on it\n\n## Questions\n\n### Which is better for AI agents, Hugging Face Inference Endpoints or Koyeb?\n\nHugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Koyeb's 46.5 (D), and leads in 6 of 7 scored categories.\n\n### Can an agent call Hugging Face Inference Endpoints and Koyeb without installing anything?\n\nYes. Hugging Face Inference Endpoints has a hosted endpoint at https://api.endpoints.huggingface.cloud and Koyeb at https://app.koyeb.com/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-koyeb.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-koyeb.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"hugging-face-inference-endpoints\", \"b\": \"koyeb\"}`. From a terminal: `anchor compare hugging-face-inference-endpoints koyeb`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-endpoints.json and https://www.anchorterminal.com/api/v1/tools/koyeb.json\n\n## Other comparisons with Hugging Face Inference Endpoints or Koyeb\n\n- [Baseten vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/baseten-vs-hugging-face-inference-endpoints.md)\n- [Baseten vs Koyeb](https://www.anchorterminal.com/compare/baseten-vs-koyeb.md)\n- [Beam vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/beam-vs-hugging-face-inference-endpoints.md)\n- [Beam vs Koyeb](https://www.anchorterminal.com/compare/beam-vs-koyeb.md)\n- [Cerebrium vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/cerebrium-vs-hugging-face-inference-endpoints.md)\n- [Cerebrium vs Koyeb](https://www.anchorterminal.com/compare/cerebrium-vs-koyeb.md)\n- [CoreWeave vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/coreweave-vs-hugging-face-inference-endpoints.md)\n- [CoreWeave vs Koyeb](https://www.anchorterminal.com/compare/coreweave-vs-koyeb.md)\n- [Hugging Face Inference Endpoints vs Hyperbolic](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-hyperbolic.md)\n- [Hugging Face Inference Endpoints vs Lambda Cloud](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-lambda.md)\n- [Hugging Face Inference Endpoints vs Modal](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-modal.md)\n- [Hugging Face Inference Endpoints vs Nebius AI Cloud](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-nebius-ai-cloud.md)\n- [Hugging Face Inference Endpoints vs Northflank](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-northflank.md)\n- [Hugging Face Inference Endpoints vs Replicate Deployments](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-replicate-deploy.md)\n- [Hugging Face Inference Endpoints vs Runpod](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-runpod.md)\n- [Hugging Face Inference Endpoints vs Thunder Compute](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-thunder-compute.md)\n- [Hugging Face Inference Endpoints vs Vast.ai](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-vast-ai.md)\n- [Hugging Face Inference Endpoints vs Verda](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-verda.md)\n- [Hyperbolic vs Koyeb](https://www.anchorterminal.com/compare/hyperbolic-vs-koyeb.md)\n- [Koyeb vs Lambda Cloud](https://www.anchorterminal.com/compare/koyeb-vs-lambda.md)\n- [Koyeb vs Modal](https://www.anchorterminal.com/compare/koyeb-vs-modal.md)\n- [Koyeb vs Nebius AI Cloud](https://www.anchorterminal.com/compare/koyeb-vs-nebius-ai-cloud.md)\n- [Koyeb vs Northflank](https://www.anchorterminal.com/compare/koyeb-vs-northflank.md)\n- [Koyeb vs Replicate Deployments](https://www.anchorterminal.com/compare/koyeb-vs-replicate-deploy.md)\n- [Koyeb vs Runpod](https://www.anchorterminal.com/compare/koyeb-vs-runpod.md)\n- [Koyeb vs Thunder Compute](https://www.anchorterminal.com/compare/koyeb-vs-thunder-compute.md)\n- [Koyeb vs Vast.ai](https://www.anchorterminal.com/compare/koyeb-vs-vast-ai.md)\n- [Koyeb vs Verda](https://www.anchorterminal.com/compare/koyeb-vs-verda.md)\n",
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      {
        "name": "Hugging Face Inference Endpoints vs Koyeb",
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    "description": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Koyeb's 46.5 (D), and leads in 6 of 7 scored categories. Both do compute gpu. Category scores, facts, verdicts and agent notes side by side.",
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    "title": "Hugging Face Inference Endpoints vs Koyeb for AI agents",
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