{
  "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": "2026-10-09T11:46:30.653783864Z",
          "lastOk": true,
          "lastStatus": 200,
          "lastMs": 257,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 255,
          "p95ms24h": 300,
          "samples24h": 44,
          "samples30d": 44,
          "days": [
            {
              "date": "2026-10-09",
              "probes": 44,
              "ok": 44
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.huggingface.co",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-09T07:58:03.654181492Z"
        },
        "updatedAt": "2026-10-09T11:46:30.653783864Z"
      }
    },
    "answer": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Verda's 62.3 (B), and leads in 1 of 7 scored categories. Verda leads on schema \u0026 documentation and transparency \u0026 trust.",
    "b": {
      "slug": "verda",
      "name": "Verda",
      "vendor": "Verda",
      "vendorUrl": "https://verda.com",
      "kind": "http-api",
      "category": "gpu-compute",
      "summary": "Verda, formerly DataCrunch, is a Finnish GPU cloud renting GPU and CPU instances, clusters, serverless containers and storage. Agents use its REST API, Python and Go SDKs, or a CLI with a built-in MCP server in beta.",
      "url": "https://www.anchorterminal.com/tools/verda",
      "markdownUrl": "https://www.anchorterminal.com/tools/verda.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/verda.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/verda.json",
      "repo": "https://github.com/verda-cloud/verda-cli",
      "license": "Proprietary service under Verda's Terms of Service. The CLI, the Python SDK and the Go SDK on GitHub are Apache-2.0",
      "transports": [
        "http",
        "stdio"
      ],
      "remoteUrl": "https://api.verda.com/v1",
      "packages": [
        {
          "registry": "pypi",
          "name": "verda"
        },
        {
          "registry": "go",
          "name": "github.com/verda-cloud/verdacloud-sdk-go"
        }
      ],
      "auth": "oauth",
      "authNotes": "Self-serve. A signed-in user creates a Client ID and Client Secret on the console's Credentials page, and the secret is shown once. `POST /v1/oauth2/token` with the client credentials grant returns an access token valid for 3,600 seconds and a refresh token, both with the scope `cloud-api-v1`. Credentials belong to the member who created them and are deleted when that member leaves the project. The CLI and its MCP server read the same pair from `~/.verda/credentials` after `verda auth login`. A few catalogue endpoints such as `GET /v1/instance-types` need no token.",
      "pricing": "usage",
      "pricingNotes": "No free tier or trial. Accounts are prepaid by card or bank transfer, and Pay As You Go is charged in prepaid 10-minute increments with the unused part refunded. On-demand prices per GPU an hour on 8 October 2026 include H100 80 GB at $3.89, H200 at $5.07, B200 at $7.34 and A100 80 GB at $1.87, with spot at about half. Reserved terms take 2 to 25 per cent off. Serverless containers bill per minute of replica use. Free credits are granted only for approved blog posts or videos (https://verda.com/pricing).",
      "priceSummary": "Pay per use",
      "where": "both",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the docs corpus, the OpenAPI document or the pricing page (checked 2026-10-08).",
        "endpoints": []
      },
      "toolCount": 18,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": 10461,
        "asOf": "2026-10-08"
      },
      "docsUrl": "https://docs.verda.com",
      "llmsTxt": "https://docs.verda.com/llms.txt",
      "openapi": "https://api.verda.com/v1/openapi.json",
      "capabilities": [
        "compute.gpu",
        "compute.serverless",
        "compute.endpoints",
        "compute.batch",
        "compute.containers"
      ],
      "tags": [
        "hosted",
        "usage-priced",
        "openapi",
        "llms-txt",
        "mcp",
        "cli",
        "oauth",
        "python",
        "go",
        "terraform",
        "status-page",
        "soc2",
        "europe"
      ],
      "lastRelease": "2026-10-07",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 62.3,
        "grade": "B",
        "agentReady": false,
        "rank": 396,
        "ranked": true,
        "rankOf": 842,
        "categoryRank": 7,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 63,
          "maintenance": 83,
          "payments": 20,
          "reliability": 67,
          "schema": 82,
          "security": 68,
          "transparency": 76
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-08"
        },
        "negative": -3,
        "negativeNotes": [
          "2026-03-19, making `location_code` required on `POST /v1/instances`, `POST /v1/clusters` and `POST /v1/volumes`. Requests that had defaulted to FIN-01 began returning 400. The API changelog dates the change 19 March and the docs 23 March, and neither records advance notice. Documented, so 3 points (https://docs.verda.com/welcome-to-verda/release-notes/verda-api-changes/index.md)."
        ],
        "verdict": "The REST API has a public OpenAPI 3.1 document, a dated changelog, published rate limits with `Retry-After`, and an audit log endpoint. The CLI's MCP server refuses billed or destructive calls without `confirm: true`. Access needs a browser signup and a prepaid balance, credentials carry one scope, and instance creation has no idempotency key.",
        "bestFor": "Agents that rent whole GPU machines or clusters in Finland for training or batch work, or deploy scale-to-zero container endpoints, and that can run a local CLI for MCP.",
        "strengths": [
          "OpenAPI 3.1 document with 112 operations and 156 schemas, plus `llms.txt` files on three hosts and the whole docs corpus as Markdown",
          "Rate limits of 500 requests a minute per project and 60 per endpoint, with `RateLimit` headers and `Retry-After` on 429",
          "API changelog with 11 dated entries between 11 September and 7 October 2026",
          "Audit log endpoint in CloudEvents 1.0 format covering 90 days, with the caller's IP address and origin on resource events",
          "The 18-tool MCP server refuses `create_vm`, `create_volume` and destructive `vm_action` calls unless `confirm: true` is passed"
        ],
        "weaknesses": [
          "No free tier. Accounts are prepaid, and instances are discontinued and volumes deleted when the balance reaches zero",
          "Cloud API credentials carry one scope, `cloud-api-v1`, with no read-only credential found in the reviewed documentation",
          "`POST /v1/instances` has no idempotency key, so a retried launch can start a second billed instance",
          "The MCP server is marked beta and its tools carry no read-only or destructive annotations",
          "On 30 December 2025 a storage migration overwrote part of a shared filesystem in FIN-03, and Verda reported irreversible data loss for some customers",
          "No SLA was found, and the terms give no warranty of uninterrupted availability"
        ],
        "agentNotes": [
          "Exchange the client ID and secret at `POST /v1/oauth2/token`, then send the access token as a Bearer header. It expires after 3,600 seconds, so refresh it.",
          "Send `location_code` on every create call. Requests without it have returned 400 since March 2026.",
          "Call `GET /v1/instance-availability` before launching. `POST /v1/instances` returns 503 `service_unavailable` when the location has no capacity.",
          "List instances before retrying a failed launch, because create has no idempotency key.",
          "Use the `delete` action to stop charges. `shutdown` keeps billing, and deleted volumes stay recoverable for 96 hours unless `delete_permanently` is set."
        ],
        "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": 62.3
          }
        ],
        "editorialScores": {
          "ergonomics": 63,
          "maintenance": 83,
          "payments": 20,
          "reliability": 67,
          "schema": 82,
          "security": 68,
          "transparency": 57
        },
        "provenanceScore": 95
      },
      "connect": {
        "install": "brew install verda-cloud/tap/verda-cli",
        "http": "curl -X POST https://api.verda.com/v1/oauth2/token -H \"Content-Type: application/json\" -d '{\"grant_type\":\"client_credentials\",\"client_id\":\"\u003cYOUR_CLIENT_ID\u003e\",\"client_secret\":\"\u003cYOUR_CLIENT_SECRET\u003e\"}'",
        "config": {
          "mcpServers": {
            "verda": {
              "args": [
                "mcp",
                "serve"
              ],
              "command": "verda"
            }
          }
        }
      },
      "letme": {
        "capability": "https://letme.dev/compute.gpu",
        "tool": "https://letme.dev/verda"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "H100 SXM5 80 GB, on-demand",
          "unit": "gpu-hour",
          "usd": 3.89,
          "note": "Spot $1.95. Billed in prepaid 10-minute increments"
        },
        {
          "item": "H200 SXM5 141 GB, on-demand",
          "unit": "gpu-hour",
          "usd": 5.07,
          "note": "Spot $2.54"
        },
        {
          "item": "B200 SXM6 180 GB, on-demand",
          "unit": "gpu-hour",
          "usd": 7.34,
          "note": "Spot $3.67"
        },
        {
          "item": "B300 SXM6 268 GB, on-demand",
          "unit": "gpu-hour",
          "usd": 9.24,
          "note": "Spot $4.62"
        },
        {
          "item": "A100 SXM4 80 GB, on-demand",
          "unit": "gpu-hour",
          "usd": 1.87,
          "note": "Spot $0.935"
        },
        {
          "item": "L40S 48 GB, on-demand",
          "unit": "gpu-hour",
          "usd": 1.61,
          "note": "Spot $0.803"
        },
        {
          "item": "H100 SXM5 80 GB, serverless container",
          "unit": "gpu-hour",
          "usd": 4.28,
          "note": "Spot $2.14. Billed per minute of replica use"
        },
        {
          "item": "NVMe block volume or shared filesystem",
          "unit": "gb-month",
          "usd": 0.2,
          "note": "Per GiB"
        }
      ],
      "provenance": {
        "legalEntity": "DataCrunch Oy",
        "domain": "verda.com",
        "domainRegistered": "1998-05-22",
        "endpointOnVendorDomain": true,
        "terms": "https://verda.com/terms-and-conditions",
        "privacy": "https://verda.com/privacy-policy",
        "statusPage": "https://status.verda.com",
        "changelog": "https://docs.verda.com/welcome-to-verda/release-notes/verda-api-changes/",
        "securityTxt": "valid",
        "checked": "2026-10-08",
        "notes": [
          "The Terms of Service, last updated 30 September 2025, name the supplier as Verda (DataCrunch Oy), apply Finnish law and set arbitration in Helsinki. They include the data processing terms.",
          "The CLI source carries the copyright of Verda Cloud Oy.",
          "The API answers at api.verda.com, a subdomain of the vendor domain.",
          "security.txt expires on 31 December 2026, lists security@verda.com and a policy at https://vdp.verda.com.",
          "RDAP for verda.com gives a registration date of 1998-05-22. The company took the Verda name later, and verda.com/llms.txt says it was previously known as DataCrunch.",
          "The privacy policy covers the website and the services and shows no readable date."
        ],
        "score": 95
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/verda.json",
      "live": {
        "slug": "verda",
        "probe": {
          "target": "https://api.verda.com/v1",
          "method": "get",
          "lastAt": "2026-10-09T11:46:44.806118011Z",
          "lastOk": true,
          "lastStatus": 401,
          "lastMs": 106,
          "lastNote": "asks for credentials",
          "authRequired": true,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 91,
          "p95ms24h": 177,
          "samples24h": 44,
          "samples30d": 44,
          "days": [
            {
              "date": "2026-10-09",
              "probes": 44,
              "ok": 44
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.verda.com",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-09T07:58:39.142949931Z"
        },
        "updatedAt": "2026-10-09T11:46:44.806118011Z"
      }
    },
    "facts": [
      {
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        "question": "Which is better for AI agents, Hugging Face Inference Endpoints or Verda?"
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      {
        "answer": "Hugging Face Inference Endpoints takes an API key or an OAuth sign-in. Verda uses an OAuth sign-in.",
        "question": "Do Hugging Face Inference Endpoints and Verda need an API key?"
      },
      {
        "answer": "Yes. Hugging Face Inference Endpoints has a hosted endpoint at https://api.endpoints.huggingface.cloud and Verda at https://api.verda.com/v1.",
        "question": "Can an agent call Hugging Face Inference Endpoints and Verda without installing anything?"
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        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-hyperbolic.json",
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        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-thunder-compute"
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        "key": "reliability",
        "name": "Reliability",
        "verda": 67,
        "weight": 16
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        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 9,
        "edge": "verda",
        "hugging-face-inference-endpoints": 73,
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "verda": 82,
        "weight": 13
      },
      {
        "by": 1,
        "edge": "verda",
        "hugging-face-inference-endpoints": 62,
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "verda": 63,
        "weight": 13
      },
      {
        "by": 15,
        "edge": "hugging-face-inference-endpoints",
        "hugging-face-inference-endpoints": 83,
        "key": "security",
        "name": "Security \u0026 auth",
        "verda": 68,
        "weight": 14
      },
      {
        "by": 0,
        "edge": "",
        "hugging-face-inference-endpoints": 20,
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "verda": 20,
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 3,
        "edge": "verda",
        "hugging-face-inference-endpoints": 80,
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "verda": 83,
        "weight": 7
      },
      {
        "by": 8,
        "edge": "verda",
        "hugging-face-inference-endpoints": 68,
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "verda": 76,
        "weight": 7
      }
    ],
    "summary": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Verda's 62.3 (B), and leads in 1 of 7 scored categories. Verda leads on schema \u0026 documentation and transparency \u0026 trust. Both do compute gpu.",
    "verdicts": {
      "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.",
      "verda": "The REST API has a public OpenAPI 3.1 document, a dated changelog, published rate limits with `Retry-After`, and an audit log endpoint. The CLI's MCP server refuses billed or destructive calls without `confirm: true`. Access needs a browser signup and a prepaid balance, credentials carry one scope, and instance creation has no idempotency key."
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  "markdown": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Verda's 62.3 (B), and leads in 1 of 7 scored categories. Verda leads on schema \u0026 documentation and transparency \u0026 trust. 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- Verda: grade B, 62.3/100, rank #396 of 842. Markdown https://www.anchorterminal.com/tools/verda.md · JSON https://www.anchorterminal.com/api/v1/tools/verda.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- Security \u0026 auth, 83 against 68\n\nAlso in its favour:\n- No incidents deducted, where Verda loses 3 points for them\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### Verda (B)\n\nGood for: Agents that rent whole GPU machines or clusters in Finland for training or batch work, or deploy scale-to-zero container endpoints, and that can run a local CLI for MCP.\n\nAhead on:\n- Schema \u0026 documentation, 82 against 73\n- Transparency \u0026 trust, 76 against 68\n\nAlso in its favour:\n- Runs on your own machine\n\nWatch for: No free tier. Accounts are prepaid, and instances are discontinued and volumes deleted when the balance reaches zero\n\n\n## Score by category\n\n| Category | Weight | Hugging Face Inference Endpoints | Verda | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 63 | 67 | Verda +4 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 73 | 82 | Verda +9 |\n| Agent ergonomics | 13% (16.2 this run) | 62 | 63 | Verda +1 |\n| Security \u0026 auth | 14% (17.5 this run) | 83 | 68 | Hugging Face Inference Endpoints +15 |\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 | 83 | Verda +3 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 68 | 76 | Verda +8 |\n| Negative events | ≤15 | 0 | -3 | |\n| **Total** | | **64.5 · B** | **62.3 · B** | |\n\n## Facts side by side\n\n| Fact | Hugging Face Inference Endpoints | Verda |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Hugging Face, Inc. | Verda |\n| Hosted endpoint | `https://api.endpoints.huggingface.cloud` | `https://api.verda.com/v1` |\n| Transports | HTTP | HTTP, stdio |\n| Auth | OAuth or key | OAuth |\n| Pricing | Pay per use | Pay per use |\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 | Proprietary service under Verda's Terms of Service. The CLI, the Python SDK and the Go SDK on GitHub are Apache-2.0 |\n| Tools exposed | 19 | 18 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-08 | 2026-10-07 |\n| Terms last updated | 2022-09-15 | 2025-09-30 |\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 | not found in the text |\n| Terms restrict benchmarking | not found in the text | yes |\n| Terms or service can change without notice | yes | not found in the text |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | 60M PyPI/wk | 10k PyPI/wk |\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**Verda.** The REST API has a public OpenAPI 3.1 document, a dated changelog, published rate limits with `Retry-After`, and an audit log endpoint. The CLI's MCP server refuses billed or destructive calls without `confirm: true`. Access needs a browser signup and a prepaid balance, credentials carry one scope, and instance creation has no idempotency key.\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### Verda\n\n1. Exchange the client ID and secret at `POST /v1/oauth2/token`, then send the access token as a Bearer header. It expires after 3,600 seconds, so refresh it.\n2. Send `location_code` on every create call. Requests without it have returned 400 since March 2026.\n3. Call `GET /v1/instance-availability` before launching. `POST /v1/instances` returns 503 `service_unavailable` when the location has no capacity.\n4. List instances before retrying a failed launch, because create has no idempotency key.\n5. Use the `delete` action to stop charges. `shutdown` keeps billing, and deleted volumes stay recoverable for 96 hours unless `delete_permanently` is set.\n\n## Questions\n\n### Which is better for AI agents, Hugging Face Inference Endpoints or Verda?\n\nHugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Verda's 62.3 (B), and leads in 1 of 7 scored categories. Verda leads on schema \u0026 documentation and transparency \u0026 trust.\n\n### Do Hugging Face Inference Endpoints and Verda need an API key?\n\nHugging Face Inference Endpoints takes an API key or an OAuth sign-in. Verda uses an OAuth sign-in.\n\n### Can an agent call Hugging Face Inference Endpoints and Verda without installing anything?\n\nYes. Hugging Face Inference Endpoints has a hosted endpoint at https://api.endpoints.huggingface.cloud and Verda at https://api.verda.com/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-verda.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-verda.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"hugging-face-inference-endpoints\", \"b\": \"verda\"}`. From a terminal: `anchor compare hugging-face-inference-endpoints verda`\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/verda.json\n\n## Other comparisons with Hugging Face Inference Endpoints or Verda\n\n- [Baseten vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/baseten-vs-hugging-face-inference-endpoints.md)\n- [Baseten vs Verda](https://www.anchorterminal.com/compare/baseten-vs-verda.md)\n- [Beam vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/beam-vs-hugging-face-inference-endpoints.md)\n- [Beam vs Verda](https://www.anchorterminal.com/compare/beam-vs-verda.md)\n- [Cerebrium vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/cerebrium-vs-hugging-face-inference-endpoints.md)\n- [Cerebrium vs Verda](https://www.anchorterminal.com/compare/cerebrium-vs-verda.md)\n- [CoreWeave vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/coreweave-vs-hugging-face-inference-endpoints.md)\n- [CoreWeave vs Verda](https://www.anchorterminal.com/compare/coreweave-vs-verda.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 Koyeb](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-koyeb.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- [Hyperbolic vs Verda](https://www.anchorterminal.com/compare/hyperbolic-vs-verda.md)\n- [Koyeb vs Verda](https://www.anchorterminal.com/compare/koyeb-vs-verda.md)\n- [Lambda Cloud vs Verda](https://www.anchorterminal.com/compare/lambda-vs-verda.md)\n- [Modal vs Verda](https://www.anchorterminal.com/compare/modal-vs-verda.md)\n- [Nebius AI Cloud vs Verda](https://www.anchorterminal.com/compare/nebius-ai-cloud-vs-verda.md)\n- [Northflank vs Verda](https://www.anchorterminal.com/compare/northflank-vs-verda.md)\n- [Replicate Deployments vs Verda](https://www.anchorterminal.com/compare/replicate-deploy-vs-verda.md)\n- [Runpod vs Verda](https://www.anchorterminal.com/compare/runpod-vs-verda.md)\n- [Thunder Compute vs Verda](https://www.anchorterminal.com/compare/thunder-compute-vs-verda.md)\n- [Vast.ai vs Verda](https://www.anchorterminal.com/compare/vast-ai-vs-verda.md)\n",
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    "description": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Verda's 62.3 (B), and leads in 1 of 7 scored categories. Verda leads on schema \u0026 documentation and transparency \u0026 trust. Both do compute gpu. Category scores, facts, verdicts and agent notes side by side.",
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