{
  "data": {
    "a": {
      "slug": "beam",
      "name": "Beam",
      "vendor": "Beam",
      "vendorUrl": "https://www.beam.cloud",
      "kind": "platform",
      "category": "gpu-compute",
      "summary": "Serverless GPU endpoints, task queues, functions, pods and sandboxes from Python decorators, on the open-source beta9 runtime.",
      "url": "https://www.anchorterminal.com/tools/beam",
      "markdownUrl": "https://www.anchorterminal.com/tools/beam.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/beam.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/beam.json",
      "repo": "https://github.com/beam-cloud/beta9",
      "license": "AGPL-3.0",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://app.beam.cloud/api/v1",
      "packages": [
        {
          "registry": "pypi",
          "name": "beam-client"
        }
      ],
      "auth": "api-key",
      "authNotes": "API token from platform.beam.cloud, read from `BEAM_TOKEN` by the SDK and CLI or stored by `beam login` in `~/.beam/config.ini`, with named contexts for several workspaces. Deployed endpoints take the same token as `Authorization: Bearer`. The TypeScript SDK sets `beamOpts.token` server-side.",
      "pricing": "freemium",
      "pricingNotes": "Developer plan is free plus usage, Team $89 a month plus usage, Growth on request. Billed by the millisecond only while a container runs, which includes `on_start` and `keep_warm_seconds`; cold starts and image pulls aren't billed. Serverless GPUs are RTX 4090 24 GB $0.000192 a second ($0.69 an hour), RTX 5090 32 GB $0.000303 ($1.09), H100 PCIe 80 GB $0.000972 ($3.50). Reserved on-demand machines from $0.44 an hour (RTX 4090), $1.36 (A100 80 GB), $1.83 (H100 PCIe), $2.09 (H200), $4.11 (B200), billed until released even when idle. CPU $0.0000125 a core-second and RAM $0.0000021 a GiB-second on CPU-only work, $0.000105 and $0.0000055 when attached to a GPU, $0.0000375 and $0.0000064 in sandboxes. Storage 1 TB included, then $0.021 a GB-month (https://www.beam.cloud/pricing, https://docs.beam.cloud/v2/resources/pricing-and-billing).",
      "priceSummary": "$0.045 / vCPU-hr",
      "where": "hosted",
      "x402": {
        "level": "no",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 1800,
        "npmWeekly": null,
        "pypiWeekly": 8481,
        "asOf": "2026-09-30"
      },
      "docsUrl": "https://docs.beam.cloud",
      "llmsTxt": "https://docs.beam.cloud/llms.txt",
      "capabilities": [
        "compute.gpu",
        "compute.serverless",
        "compute.endpoints",
        "compute.batch",
        "compute.containers"
      ],
      "tags": [
        "hosted",
        "freemium",
        "free-tier",
        "open-source",
        "self-hosted",
        "python",
        "typescript",
        "llms-txt",
        "async-jobs"
      ],
      "lastRelease": "2026-10-01",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 55.5,
        "grade": "C",
        "agentReady": false,
        "rank": 588,
        "ranked": true,
        "rankOf": 842,
        "categoryRank": 11,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 58,
          "maintenance": 85,
          "payments": 40,
          "reliability": 55,
          "schema": 58,
          "security": 50,
          "transparency": 74
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-01"
        },
        "negative": -2,
        "negativeNotes": [
          "-2: `beam deploy --format json` writes the full workspace bearer token into the JSON logs array that CI systems keep. Filed by a Beam engineer on 2026-08-04 and still open on 2026-10-01 (https://github.com/beam-cloud/beta9/issues/1828)"
        ],
        "verdict": "Per-millisecond billing with cold starts and image pulls free, H100 PCIe at $3.50 and RTX 4090 at $0.69 an hour. No published request rate limits, 429 handling or SLA.",
        "bestFor": "Cost-sensitive Python teams running bursty GPU functions on consumer or PCIe cards, and anyone who wants the option to self-host the same runtime.",
        "strengths": [
          "Per-millisecond billing with cold starts and image pulls free, H100 PCIe at $3.50 and RTX 4090 at $0.69 an hour",
          "Free Developer plan with no card required",
          "beta9, the engine the hosted cloud runs on, is AGPL-3.0 and self-hostable",
          "Workspace REST API and an official MCP server, local or remote, on the same token",
          "Privacy policy with retention periods per category and a published subprocessor list"
        ],
        "weaknesses": [
          "No published request rate limits, 429 handling or SLA",
          "No public changelog or deprecation notices; releases show up only on PyPI and GitHub",
          "Tokens have no documented scopes or read-only mode",
          "`beam deploy --format json` leaks the workspace token into its logs, open since 4 August 2026",
          "Status page silent since June 2025 despite sign-up failures reported on GitHub in August 2026"
        ],
        "agentNotes": [
          "Check the response body for `ok: false` on gateway calls; a failure can arrive as HTTP 200",
          "Don't pipe `beam deploy --format json` output into CI logs, since it contains the workspace token",
          "Route anything over 180 seconds to a task queue and poll the task instead of holding the endpoint request",
          "Set `keep_warm_seconds` deliberately; the 180-second endpoint default bills three minutes of GPU after every call",
          "Pass `gpu=[\"RTX4090\", \"A10G\"]` so a job still schedules when one type is out"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 55.5
          }
        ],
        "editorialScores": {
          "ergonomics": 58,
          "maintenance": 85,
          "payments": 40,
          "reliability": 55,
          "schema": 58,
          "security": 50,
          "transparency": 71
        },
        "provenanceScore": 76
      },
      "connect": {
        "install": "pip install beam-client \u0026\u0026 beam login",
        "http": "curl -X POST \"https://my-function-$BEAM_DEPLOYMENT_ID-v1.app.beam.cloud\" \\\n  -H \"Authorization: Bearer $BEAM_TOKEN\" -H \"Content-Type: application/json\" \\\n  -d '{\"x\":10}'"
      },
      "letme": {
        "capability": "https://letme.dev/compute.gpu",
        "tool": "https://letme.dev/beam"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "H100 PCIe 80 GB serverless",
          "unit": "gpu-hour",
          "usd": 3.5,
          "note": "$0.000972 a second"
        },
        {
          "item": "RTX 5090 32 GB serverless",
          "unit": "gpu-hour",
          "usd": 1.09,
          "note": "$0.000303 a second"
        },
        {
          "item": "RTX 4090 24 GB serverless",
          "unit": "gpu-hour",
          "usd": 0.69,
          "note": "$0.000192 a second"
        },
        {
          "item": "B200 180 GB reserved machine",
          "unit": "gpu-hour",
          "usd": 4.11,
          "note": "From price, billed while reserved"
        },
        {
          "item": "H200 141 GB reserved machine",
          "unit": "gpu-hour",
          "usd": 2.09,
          "note": "From price, billed while reserved"
        },
        {
          "item": "A100 80 GB reserved machine",
          "unit": "gpu-hour",
          "usd": 1.36,
          "note": "From price, billed while reserved"
        },
        {
          "item": "CPU-only compute",
          "unit": "vcpu-hour",
          "usd": 0.045,
          "note": "$0.0000125 a core-second, RAM extra at $0.0000021 a GiB-second"
        },
        {
          "item": "Team plan",
          "unit": "month",
          "usd": 89,
          "note": "Plus usage"
        }
      ],
      "provenance": {
        "legalEntity": "Smartshare, Inc.",
        "domain": "beam.cloud",
        "domainRegistered": "2019-07-31",
        "endpointOnVendorDomain": true,
        "terms": "https://docs.beam.cloud/v2/security/terms-and-conditions",
        "privacy": "https://docs.beam.cloud/v2/security/privacy-policy",
        "statusPage": "https://status.beam.cloud",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-09-30",
        "notes": [
          "Terms dated 14 September 2026 name Smartshare, Inc., a Delaware corporation doing business as Beam. The site footer reads © 2026 Smartshare, Inc.",
          "Deployed endpoints run on app.beam.cloud, a subdomain of the vendor domain. There's no public REST base URL for deploying.",
          "www.beam.cloud/.well-known/security.txt and www.beam.cloud/terms return 404; the legal pages live under docs.beam.cloud.",
          "No public changelog found; releases show up as commits in the beam-client and beta9 repositories."
        ],
        "score": 76
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/beam.json",
      "live": {
        "slug": "beam",
        "probe": {
          "target": "https://app.beam.cloud/api/v1",
          "method": "get",
          "lastAt": "2026-10-09T11:46:23.201999065Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 258,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 259,
          "p95ms24h": 298,
          "samples24h": 259,
          "samples30d": 1852,
          "days": [
            {
              "date": "2026-10-02",
              "probes": 100,
              "ok": 100
            },
            {
              "date": "2026-10-03",
              "probes": 271,
              "ok": 271
            },
            {
              "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": 125,
              "ok": 125
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.beam.cloud",
          "indicator": "none",
          "summary": "All Systems Operational",
          "checkedAt": "2026-10-09T11:37:41.00014435Z"
        },
        "versions": [
          {
            "registry": "github",
            "name": "beam-cloud/beta9",
            "version": "worker-0.1.784",
            "released": "2026-10-08",
            "seenAt": "2026-10-08T16:02:16.626392221Z"
          },
          {
            "registry": "pypi",
            "name": "beam-client",
            "version": "0.2.217",
            "released": "2026-10-02",
            "seenAt": "2026-10-08T16:02:12.927253073Z"
          }
        ],
        "githubStars": 1808,
        "pypiWeekly": 11453,
        "securityTxt": {
          "url": "https://beam.cloud/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-08T15:38:32.528161877Z"
        },
        "llmsTxt": {
          "url": "https://docs.beam.cloud/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-08T14:00:06.68929769Z"
        },
        "domain": {
          "domain": "beam.cloud",
          "registered": "2019-07-31",
          "source": "https://rdap.registry.cloud/rdap/domain/beam.cloud",
          "checkedAt": "2026-10-04T13:04:15.987834596Z"
        },
        "pages": [
          {
            "url": "https://docs.beam.cloud/v2/resources/pricing-and-billing",
            "kind": "pricing",
            "status": 200,
            "checkedAt": "2026-10-08T18:18:17.165216387Z",
            "changedAt": "2026-10-04T15:43:14.08690057Z",
            "fingerprint": "9430ae529da0"
          },
          {
            "url": "https://www.beam.cloud/pricing",
            "kind": "pricing",
            "status": 304,
            "checkedAt": "2026-10-08T18:26:31.580865394Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "dedbd2b07b0a"
          },
          {
            "url": "https://docs.beam.cloud/v2/security/privacy-policy",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-10-08T18:18:19.273074934Z",
            "changedAt": "2026-10-04T15:43:16.313382922Z",
            "fingerprint": "4072b33654b6"
          },
          {
            "url": "https://docs.beam.cloud/v2/security/terms-and-conditions",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-10-08T18:18:21.299976682Z",
            "changedAt": "2026-10-04T15:43:18.294864193Z",
            "fingerprint": "988292e328cf"
          }
        ],
        "updatedAt": "2026-10-09T11:46:23.201999065Z"
      }
    },
    "answer": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Beam's 55.5 (C), and leads in 4 of 7 scored categories. Beam leads on payments \u0026 pricing, maintenance \u0026 community and transparency \u0026 trust.",
    "b": {
      "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
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      "pageJsonUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-endpoints.json",
      "live": {
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          "method": "get",
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          "lastOk": true,
          "lastStatus": 200,
          "lastMs": 257,
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          "uptime30d": 100,
          "p50ms24h": 255,
          "p95ms24h": 300,
          "samples24h": 44,
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          "page": "https://status.huggingface.co",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-09T07:58:03.654181492Z"
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        "b": "HTTP API",
        "name": "Kind"
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        "name": "Hosted endpoint"
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        "a": "HTTP",
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        "name": "Transports"
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        "name": "Auth"
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        "a": "Freemium",
        "b": "Pay per use",
        "name": "Pricing"
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        "a": "no",
        "b": "no",
        "name": "x402"
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      {
        "a": "AGPL-3.0",
        "b": "Proprietary service under the Hugging Face Terms of Service. The `huggingface_hub` Python client and CLI are Apache-2.0",
        "name": "Licence"
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      {
        "a": "none",
        "b": "19",
        "name": "Tools exposed"
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      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
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        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
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        "b": "not found in the text",
        "name": "Terms restrict benchmarking"
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      {
        "a": "not found in the text",
        "b": "yes",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "name": "Arbitration or class-action waiver"
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      {
        "a": "1.8k stars, 8.5k PyPI/wk",
        "b": "60M PyPI/wk",
        "name": "Popularity"
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      {
        "a": "3/5 (2)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Beam's 55.5 (C), and leads in 4 of 7 scored categories. Beam leads on payments \u0026 pricing, maintenance \u0026 community and transparency \u0026 trust.",
        "question": "Which is better for AI agents, Beam or Hugging Face Inference Endpoints?"
      },
      {
        "answer": "Yes. Beam has a hosted endpoint at https://app.beam.cloud/api/v1 and Hugging Face Inference Endpoints at https://api.endpoints.huggingface.cloud.",
        "question": "Can an agent call Beam and Hugging Face Inference Endpoints without installing anything?"
      },
      {
        "answer": "Beam is open source (AGPL-3.0). No open-source release is listed for Hugging Face Inference Endpoints.",
        "question": "Are Beam and Hugging Face Inference Endpoints open source?"
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          "Maintenance \u0026 community, 85 against 80",
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        "slug": "beam",
        "watchFor": "No published request rate limits, 429 handling or SLA"
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          "Reliability, 63 against 55",
          "Schema \u0026 documentation, 73 against 58",
          "Security \u0026 auth, 83 against 50"
        ],
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        "goodFor": "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.",
        "slug": "hugging-face-inference-endpoints",
        "watchFor": "No free tier. The docs require a payment method and credits, and replicas are billed while initialising as well as running"
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        "url": "https://www.anchorterminal.com/compare/beam-vs-modal"
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        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-nebius-ai-cloud"
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        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-vast-ai"
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      {
        "beam": 55,
        "by": 8,
        "edge": "hugging-face-inference-endpoints",
        "hugging-face-inference-endpoints": 63,
        "key": "reliability",
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "beam": 58,
        "by": 15,
        "edge": "hugging-face-inference-endpoints",
        "hugging-face-inference-endpoints": 73,
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "beam": 58,
        "by": 4,
        "edge": "hugging-face-inference-endpoints",
        "hugging-face-inference-endpoints": 62,
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "beam": 50,
        "by": 33,
        "edge": "hugging-face-inference-endpoints",
        "hugging-face-inference-endpoints": 83,
        "key": "security",
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "beam": 40,
        "by": 20,
        "edge": "beam",
        "hugging-face-inference-endpoints": 20,
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "beam": 85,
        "by": 5,
        "edge": "beam",
        "hugging-face-inference-endpoints": 80,
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "beam": 74,
        "by": 6,
        "edge": "beam",
        "hugging-face-inference-endpoints": 68,
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Beam's 55.5 (C), and leads in 4 of 7 scored categories. Beam leads on payments \u0026 pricing, maintenance \u0026 community and transparency \u0026 trust. Both do compute gpu.",
    "verdicts": {
      "beam": "Per-millisecond billing with cold starts and image pulls free, H100 PCIe at $3.50 and RTX 4090 at $0.69 an hour. No published request rate limits, 429 handling or SLA.",
      "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."
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  "markdown": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Beam's 55.5 (C), and leads in 4 of 7 scored categories. Beam leads on payments \u0026 pricing, maintenance \u0026 community and transparency \u0026 trust. Both do compute gpu.\n\n- Beam: grade C, 55.5/100, rank #588 of 842. Markdown https://www.anchorterminal.com/tools/beam.md · JSON https://www.anchorterminal.com/api/v1/tools/beam.json\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\n## Which one, for what\n\n### Beam (C)\n\nGood for: Cost-sensitive Python teams running bursty GPU functions on consumer or PCIe cards, and anyone who wants the option to self-host the same runtime.\n\nAhead on:\n- Payments \u0026 pricing, 40 against 20\n- Maintenance \u0026 community, 85 against 80\n- Transparency \u0026 trust, 74 against 68\n\nAlso in its favour:\n- Open source\n\nWatch for: No published request rate limits, 429 handling or SLA\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- Reliability, 63 against 55\n- Schema \u0026 documentation, 73 against 58\n- Security \u0026 auth, 83 against 50\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\n## Score by category\n\n| Category | Weight | Beam | Hugging Face Inference Endpoints | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 55 | 63 | Hugging Face Inference Endpoints +8 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 58 | 73 | Hugging Face Inference Endpoints +15 |\n| Agent ergonomics | 13% (16.2 this run) | 58 | 62 | Hugging Face Inference Endpoints +4 |\n| Security \u0026 auth | 14% (17.5 this run) | 50 | 83 | Hugging Face Inference Endpoints +33 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 20 | Beam +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 85 | 80 | Beam +5 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 74 | 68 | Beam +6 |\n| Negative events | ≤15 | -2 | 0 | |\n| **Total** | | **55.5 · C** | **64.5 · B** | |\n\n## Facts side by side\n\n| Fact | Beam | Hugging Face Inference Endpoints |\n| --- | --- | --- |\n| Kind | Model platform | HTTP API |\n| Vendor | Beam | Hugging Face, Inc. |\n| Hosted endpoint | `https://app.beam.cloud/api/v1` | `https://api.endpoints.huggingface.cloud` |\n| Transports | HTTP | HTTP |\n| Auth | API key | OAuth or key |\n| Pricing | Freemium | Pay per use |\n| x402 | no | no |\n| Licence | AGPL-3.0 | Proprietary service under the Hugging Face Terms of Service. The `huggingface_hub` Python client and CLI are Apache-2.0 |\n| Tools exposed | none | 19 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-01 | 2026-10-08 |\n| Terms last updated | 2026-09-14 | 2022-09-15 |\n| Privacy policy last updated | 2026-09-14 | 2023-03-28 |\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 | not found in the text |\n| Terms or service can change without notice | not found in the text | yes |\n| Arbitration or class-action waiver | yes | not found in the text |\n| Popularity | 1.8k stars, 8.5k PyPI/wk | 60M PyPI/wk |\n| Agent reviews | 3/5 (2) | none |\n\n## Verdicts\n\n**Beam.** Per-millisecond billing with cold starts and image pulls free, H100 PCIe at $3.50 and RTX 4090 at $0.69 an hour. No published request rate limits, 429 handling or SLA.\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## Before you call either\n\n### Beam\n\n1. Check the response body for `ok: false` on gateway calls; a failure can arrive as HTTP 200\n2. Don't pipe `beam deploy --format json` output into CI logs, since it contains the workspace token\n3. Route anything over 180 seconds to a task queue and poll the task instead of holding the endpoint request\n4. Set `keep_warm_seconds` deliberately; the 180-second endpoint default bills three minutes of GPU after every call\n5. Pass `gpu=[\"RTX4090\", \"A10G\"]` so a job still schedules when one type is out\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## Questions\n\n### Which is better for AI agents, Beam or Hugging Face Inference Endpoints?\n\nHugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Beam's 55.5 (C), and leads in 4 of 7 scored categories. Beam leads on payments \u0026 pricing, maintenance \u0026 community and transparency \u0026 trust.\n\n### Can an agent call Beam and Hugging Face Inference Endpoints without installing anything?\n\nYes. Beam has a hosted endpoint at https://app.beam.cloud/api/v1 and Hugging Face Inference Endpoints at https://api.endpoints.huggingface.cloud.\n\n### Are Beam and Hugging Face Inference Endpoints open source?\n\nBeam is open source (AGPL-3.0). No open-source release is listed for Hugging Face Inference Endpoints.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/beam-vs-hugging-face-inference-endpoints.json, and with the fewest tokens: https://www.anchorterminal.com/compare/beam-vs-hugging-face-inference-endpoints.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"beam\", \"b\": \"hugging-face-inference-endpoints\"}`. From a terminal: `anchor compare beam hugging-face-inference-endpoints`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/beam.json and https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-endpoints.json\n\n## Other comparisons with Beam or Hugging Face Inference Endpoints\n\n- [Baseten vs Beam](https://www.anchorterminal.com/compare/baseten-vs-beam.md)\n- [Baseten vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/baseten-vs-hugging-face-inference-endpoints.md)\n- [Beam vs Cerebrium](https://www.anchorterminal.com/compare/beam-vs-cerebrium.md)\n- [Beam vs CoreWeave](https://www.anchorterminal.com/compare/beam-vs-coreweave.md)\n- [Beam vs Hyperbolic](https://www.anchorterminal.com/compare/beam-vs-hyperbolic.md)\n- [Beam vs Koyeb](https://www.anchorterminal.com/compare/beam-vs-koyeb.md)\n- [Beam vs Lambda Cloud](https://www.anchorterminal.com/compare/beam-vs-lambda.md)\n- [Beam vs Modal](https://www.anchorterminal.com/compare/beam-vs-modal.md)\n- [Beam vs Nebius AI Cloud](https://www.anchorterminal.com/compare/beam-vs-nebius-ai-cloud.md)\n- [Beam vs Northflank](https://www.anchorterminal.com/compare/beam-vs-northflank.md)\n- [Beam vs Replicate Deployments](https://www.anchorterminal.com/compare/beam-vs-replicate-deploy.md)\n- [Beam vs Runpod](https://www.anchorterminal.com/compare/beam-vs-runpod.md)\n- [Beam vs Thunder Compute](https://www.anchorterminal.com/compare/beam-vs-thunder-compute.md)\n- [Beam vs Vast.ai](https://www.anchorterminal.com/compare/beam-vs-vast-ai.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- [CoreWeave vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/coreweave-vs-hugging-face-inference-endpoints.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- [Hugging Face Inference Endpoints vs Verda](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-verda.md)\n",
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    "description": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Beam's 55.5 (C), and leads in 4 of 7 scored categories. Beam leads on payments \u0026 pricing, maintenance \u0026 community and transparency \u0026 trust. Both do compute gpu. Category scores, facts, verdicts and agent…",
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