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    "answer": "GroqCloud scores 74.5 (BB) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 6 of 7 scored categories. Hugging Face Inference Providers leads on maintenance \u0026 community.",
    "b": {
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      "name": "Hugging Face Inference Providers",
      "vendor": "Hugging Face, Inc.",
      "vendorUrl": "https://huggingface.co",
      "kind": "router",
      "category": "inference",
      "summary": "Hugging Face's serverless router that sends model calls to partner inference providers such as Groq, Cerebras, Together and Fireworks through one Hugging Face token, with an OpenAI-compatible API at router.huggingface.co/v1 and Python and JavaScript clients.",
      "url": "https://www.anchorterminal.com/tools/hugging-face-inference-providers",
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      "repo": "https://github.com/huggingface/huggingface_hub",
      "license": "Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT",
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        {
          "registry": "npm",
          "name": "@huggingface/inference"
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      ],
      "auth": "api-key",
      "authNotes": "Hugging Face user access token sent as `Authorization: Bearer $HF_TOKEN`. The docs recommend a fine-grained token with only the `Make calls to Inference Providers` permission. Tokens are made in account settings in a browser, can be rotated and revoked, and a leaked token can be revoked by anyone through `POST /api/credentials/revoke`. A provider's own key can be stored in settings instead, and Hugging Face swaps it in when routing.",
      "pricing": "usage",
      "pricingNotes": "Pay as you go at each provider's own per-token rates with no Hugging Face markup, drawn from prepaid credits on the Hugging Face account. Free users get no included credits since 7 October 2026 and must buy credits. PRO users and Team or Enterprise seats get $2.00 a month of compute credits. Requests with a custom provider key are billed by the provider (https://huggingface.co/docs/inference-providers/pricing, checked 2026-11-06).",
      "priceSummary": "$2 / mo",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the Inference Providers docs, llms.txt or the router's model list. Calls draw on prepaid Hugging Face credits bought in the account's billing settings (checked 2026-11-06).",
        "endpoints": []
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      "capabilities": [
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      "tags": [
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          "security": 79,
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        "assessment": {
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        "verdict": "One Hugging Face token reaches open models on 18 partner providers at the providers' own prices, with a public model list that shows each provider's price, context and tool support. Router rate limits, error responses and its own status component were not found in the reviewed documentation, and free accounts have had no included credits since 7 October 2026.",
        "bestFor": "Agents and developers who want open-weight models from several hosts on one token and one bill, with a public price and capability list per provider.",
        "strengths": [
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          "Provider choice by suffix (`:fastest`, `:cheapest`, `:preferred` or a provider name) on an OpenAI-compatible endpoint",
          "Fine-grained tokens can be limited to the `Make calls to Inference Providers` permission and revoked at once",
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          "Official clients in Python (`huggingface_hub` 2.4.0, 29 October 2026) and JavaScript (`@huggingface/inference` 4.13.32)"
        ],
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          "status.huggingface.co has no component for Inference Providers or the router",
          "Free users have had no included credits since 7 October 2026, and buying credits needs a person in the account settings",
          "No OpenAPI document for the router, no batch API, and the Responses API is beta",
          "Data handling past the router depends on each provider's own policy"
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          "Read https://router.huggingface.co/v1/models before choosing a provider; it shows price, context and `supports_tools` per provider",
          "Pin a provider with `model:\u003cprovider\u003e` when tool calling or structured output matters, since support varies by provider",
          "Use a fine-grained token with only the Inference Providers permission, and send `X-HF-Bill-To` to bill an organisation",
          "Back off on 429 without assuming a Retry-After header, since none is documented for the router"
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              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 54
          }
        ],
        "editorialScores": {
          "ergonomics": 58,
          "maintenance": 80,
          "payments": 20,
          "reliability": 25,
          "schema": 62,
          "security": 79,
          "transparency": 58
        },
        "provenanceScore": 84,
        "checked": {
          "categories": {
            "ergonomics": "2026-11-06",
            "maintenance": "2026-11-06",
            "payments": "2026-11-06",
            "reliability": "2026-11-06",
            "schema": "2026-11-06",
            "security": "2026-11-06",
            "transparency": "2026-11-06"
          },
          "last": "2026-11-06",
          "oldest": "2026-11-06",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "pip install huggingface_hub   # or: pip install openai, with base_url https://router.huggingface.co/v1",
        "http": "curl https://router.huggingface.co/v1/chat/completions \\\n  -H \"Authorization: Bearer $HF_TOKEN\" -H \"Content-Type: application/json\" \\\n  -d '{\"model\":\"openai/gpt-oss-120b:fastest\",\"messages\":[{\"role\":\"user\",\"content\":\"How many Gs in huggingface?\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.router",
        "tool": "https://letme.dev/hugging-face-inference-providers"
      },
      "sameCompany": [
        "hugging-face-inference-endpoints",
        "smolagents",
        "carbon-x",
        "smollm3-3b"
      ],
      "area": "models",
      "unitPrices": [
        {
          "item": "openai/gpt-oss-120b input, cheapest provider listed (DeepInfra)",
          "unit": "1m-tokens",
          "usd": 0.037,
          "note": "Output $0.17. Groq lists $0.15/$0.75 and Cerebras $0.35/$0.75, per the router's model list of 6 November 2026"
        },
        {
          "item": "PRO monthly compute credits",
          "unit": "month",
          "usd": 2,
          "note": "Also $2.00 per seat for Team and Enterprise organisations"
        }
      ],
      "provenance": {
        "legalEntity": "Hugging Face, Inc.",
        "domain": "huggingface.co",
        "domainRegistered": "",
        "endpointOnVendorDomain": true,
        "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": "2026-11-06",
        "notes": [
          "The Terms of Service (effective 15 September 2022) name Hugging Face, Inc. and define Inference Providers as a hosted service for running inference through an API on Hub models.",
          "huggingface.co/robots.txt and router.huggingface.co/robots.txt allow all. status.huggingface.co serves an empty robots.txt.",
          "status.huggingface.co is a Better Stack page with components for the Hub, git hosting, Inference Endpoints, Spaces, the CDNs and Jobs, and none for Inference Providers or the router.",
          "huggingface.co/changelog covers the whole Hub and had no Inference Providers entry on its first page on 6 November 2026. Dated changes to the docs are in the hub-docs repository's history.",
          "security.txt, privacy policy and subprocessor list as recorded on the Inference Endpoints listing (checked 8 October and 2 November 2026); not re-read for this listing."
        ],
        "score": 84
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-providers.json",
      "live": {
        "slug": "hugging-face-inference-providers",
        "probe": {
          "target": "https://router.huggingface.co/v1",
          "method": "get",
          "lastAt": "2026-11-07T19:22:12.474650545Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 145,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 109,
          "p95ms24h": 196,
          "samples24h": 210,
          "samples30d": 210,
          "days": [
            {
              "date": "2026-11-06",
              "probes": 13,
              "ok": 13
            },
            {
              "date": "2026-11-07",
              "probes": 197,
              "ok": 197
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.huggingface.co",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-11-07T04:47:55.542550557Z"
        },
        "versions": [
          {
            "registry": "github",
            "name": "huggingface/huggingface_hub",
            "version": "v2.4.0",
            "released": "2026-10-29",
            "seenAt": "2026-11-06T23:33:27.894225298Z"
          },
          {
            "registry": "npm",
            "name": "@huggingface/inference",
            "version": "4.13.32",
            "seenAt": "2026-11-06T23:33:27.102558197Z"
          },
          {
            "registry": "pypi",
            "name": "huggingface_hub",
            "version": "2.4.0",
            "released": "2026-10-29",
            "seenAt": "2026-11-06T23:33:26.910773744Z"
          }
        ],
        "githubStars": 4034,
        "npmWeekly": 483470,
        "pypiWeekly": 71518708,
        "securityTxt": {
          "url": "https://huggingface.co/.well-known/security.txt",
          "state": "valid",
          "expires": "2030-07-01T08:42:00.000Z",
          "checkedAt": "2026-11-07T16:00:00.493446773Z"
        },
        "llmsTxt": {
          "url": "https://huggingface.co/docs/inference-providers/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-11-07T15:32:44.910268229Z"
        },
        "pages": [
          {
            "url": "https://huggingface.co/docs/inference-providers/pricing",
            "kind": "pricing",
            "status": 200,
            "checkedAt": "2026-11-07T14:11:37.221950067Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "2cbe821ca9d2"
          }
        ],
        "updatedAt": "2026-11-07T19:22:12.474650545Z"
      }
    },
    "edges": [
      {
        "by": 65,
        "category": "reliability",
        "leads": "groq",
        "name": "Reliability",
        "reasons": {
          "a": "Status page at groqstatus.com on incident.io, with components for the API, each production and preview model and the website (20). The page's RSS feed and the incident pages it links, read on 1 November, list three incidents in the 90-day window, all in October, and nothing since 12 October apart from a console maintenance on 18 October. On 10 October the enterprise-only preview MiniMax M2.7 had failed requests from data centre hardware issues from 10:09 to 16:14 UTC. The incident's header and impact record say degraded performance, while its Identified update set the model to partial outage and warned of failed requests. On 12 October console.groq.com returned 500 errors on metrics, /models and key creation from 03:17 to 03:38, and the vendor said inference requests were not affected. On 12 October MiniMax M2.7 had a partial outage from 18:17 to 18:36. None took down a core API for an hour, since the six-hour incident hit one enterprise preview model that the status page describes as for evaluation only, so minor incidents only (20). A stricter reading would count it as a major and give 10. Limits published per model, 30 requests a minute, 1,000 a day and 8,000 tokens a minute on gpt-oss for the free plan, re-read on 1 November (15). 429 carries `retry-after`, `x-ratelimit-*` headers come on every response, and the errors page says to wait before retrying a 503 and that a 502 may clear on retry (15). The Performance Tier, enterprise only, lists a 99.9% availability SLA with details in the offline agreement, per the 6 October check, not re-read on 1 November (10). gpt-oss and Whisper models are production, Qwen 3.8 27B, MiniMax M2.7 and Muse Spark Open are previews (10). 20+20+15+15+10+10 = 90.",
          "b": "Hosted lines. status.huggingface.co is a Better Stack page with 90-day component history for the Hub, Inference Endpoints, Spaces, the CDNs and Jobs, but no component for Inference Providers or the router (10 of 20). With no component, there is no readable incident history for the surface agents call, and the feed's 23 items from 10 June to 7 October 2026 don't name it (5). No rate limits for the router were found; the Hub rate-limits page gives numbers for Hub APIs, resolvers and pages only (0). No 429 or overload guidance for the router was found (0). No SLA found (0). Chat completions on the router is generally available; the Responses API is labelled beta (10). Routing between providers with `:fastest` or `:cheapest` softens a single provider's outage, which this checklist doesn't score."
        },
        "scores": {
          "a": 90,
          "b": 25
        }
      },
      {
        "by": 22,
        "category": "ergonomics",
        "leads": "groq",
        "name": "Agent ergonomics",
        "reasons": {
          "a": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use documented, parallel calls and forced choice not checked (15 of 20). Strict structured outputs (15). Automatic prompt caching at 50% off cached input, with a 2-hour cache life, on gpt-oss-20b, gpt-oss-120b and gpt-oss-safeguard-20b only (10 of 15). 131,072-token context on every self-serve model; only MiniMax M2.7, a preview on enterprise pricing, reaches 196,608 (5 of 15). Batch at half price (10). Official SDKs for Python and JavaScript (10). Errors page with codes, recovery advice and a typed error object (15).",
          "b": "Router reading of the model checklist (tool use, structured output, caching, context, batch, SDKs, errors), as for openrouter. Tool calling through the OpenAI-compatible API with `tool_choice`, support flagged per provider in /v1/models (15 of 20). Structured output documented, support flagged per provider and false on some (10 of 15). No prompt caching guidance found, though the Enterprise usage API counts cached input tokens (3 of 15). Routes to models with up to 1,048,576 tokens of context per the model list, a judgement call since a router has no default model (15). No batch API (0 of 10). Official clients in Python and JavaScript, plus any OpenAI SDK (10). Errors not documented (5 of 15)."
        },
        "scores": {
          "a": 80,
          "b": 58
        }
      },
      {
        "by": 20,
        "category": "payments",
        "leads": "groq",
        "name": "Payments \u0026 pricing",
        "reasons": {
          "a": "No machine payment protocol (0). Per-token prices on the models page, read without a login, such as gpt-oss-120b at $0.15 in and $0.60 out per million (20). Free plan with no card (20). Console sign-up in a browser (0).",
          "b": "No x402, MPP or L402 (0). Per-token prices for every model and provider published without a login in the router's /v1/models and on model pages (20). No free tier since 7 October 2026, when free users lost their included monthly credits; PRO's $2.00 of credits needs a subscription (0). Sign-up, token creation and credit purchase are browser steps (0)."
        },
        "scores": {
          "a": 40,
          "b": 20
        }
      },
      {
        "by": 14,
        "category": "transparency",
        "leads": "groq",
        "name": "Transparency \u0026 trust",
        "reasons": {
          "a": "Closed service with clear terms, SDKs Apache-2.0 (15). The data page agrees with the listing on retention and adds detail, batch files kept 30 days unless deleted, fine-tuning data kept until the customer deletes it, and SCCs for transfers. The services agreement bars training on inputs and outputs, and the DPA gives 15 days' notice of sub-processor changes to subscribers, both read on 6 October. The agreement extends zero retention to 'Eligible Customers' where the data page says all customers may enable it (26 of 30). Deprecations page with announcement and shutdown dates (20). All customer data in Google Cloud buckets in the US, per the data page. The DPA points to a sub-processor list at trust.groq.com/subprocessors, which needs JavaScript and wasn't read (10 of 20).",
          "b": "Closed service under Terms of Service that name Inference Providers, with an Apache-2.0 Python client and an MIT JavaScript client (20). The security page and the docs agree on no training, no stored bodies and 30-day logs, but the privacy policy dates from 28 March 2023 and each provider's own data policy governs the rest (18 of 30). No deprecation policy found. Provider support changes and the 7 October removal of free credits are dated only in the docs repository history (5 of 20). The privacy policy lists 11 subprocessors with countries per the Inference Endpoints check, and the docs name every provider a request can reach, though not where each runs (15 of 20)."
        },
        "scores": {
          "a": 85,
          "b": 71
        }
      },
      {
        "by": 8,
        "category": "maintenance",
        "leads": "hugging-face-inference-providers",
        "name": "Maintenance \u0026 community",
        "reasons": {
          "a": "Model reading. Meta's Muse Spark Open went into limited preview on GroqCloud on 15 October 2026, per Groq's announcement, 17 days before this check, and the models page lists it as an enterprise model (30). The newest shutdown is still `groq/compound` and `compound-mini` on 21 September. The changelog's newest entry is 18 April 2026, the Python SDK 1.7.0 (tagged 25 August) and TypeScript SDK 1.6.0 are still the newest tags, with commits to 4 September and no release since, and the deprecations page has no announcement after 24 August. Production models get an email and a migration path, previews may go at short notice, and no minimum period is stated. Llama 3.1 8B and 3.3 70B got 60 days on the free and developer tiers, Compound 28 days with no replacement named (4 of 12). Three shutdown dates in the 90 days to 1 November, 16 August, 14 September and 21 September. Three in 90 days is still frequent churn (0 of 8). A dated changelog with an RSS feed and a community forum exist, but the changelog's newest entry is 18 April 2026; support replies not checked (10 of 15). SDK issue replies not sampled, since GitHub's API refused our shell (5 of 10). Python SDK 1.7.0 and TypeScript SDK 1.6.0, both published on 26 August 2026 and still the newest tags on 1 November (15). CI, release-please and lock-file vulnerability fixes in 1.7.0 (8 of 10). 30+4+0+10+5+15+8 = 72.",
          "b": "Model reading. huggingface_hub 2.4.0 tagged on 29 October 2026 and the Inference Providers docs updated daily by an automated job, last on 6 November (30). huggingface_hub 2.2.0, 2.3.0 and 2.4.0 and @huggingface/inference 4.13.28 to 4.13.32 in the 90 days (20). No dedicated changelog; the Hub has a forum and Discord, and GitHub issue replies were not read (8 of 15). Current official SDKs in Python and JavaScript (15). The Python client supports Python 3.10 and later, per the Inference Endpoints check; CI not read (7 of 10)."
        },
        "scores": {
          "a": 72,
          "b": 80
        }
      }
    ],
    "facts": [
      {
        "a": "Model API",
        "b": "Model router",
        "name": "Kind"
      },
      {
        "a": "Groq",
        "b": "Hugging Face, Inc.",
        "name": "Vendor"
      },
      {
        "a": "https://api.groq.com/openai/v1",
        "b": "https://router.huggingface.co/v1",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP",
        "b": "HTTP",
        "name": "Transports"
      },
      {
        "a": "API key",
        "b": "API key",
        "name": "Auth"
      },
      {
        "a": "Freemium",
        "b": "Pay per use",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Apache-2.0 (SDKs)",
        "b": "Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-15",
        "b": "2026-10-29",
        "name": "Last release"
      },
      {
        "a": "2026-06-22",
        "b": "2022-09-15",
        "name": "Terms last updated"
      },
      {
        "a": "2025-11-12",
        "b": "2023-03-28",
        "name": "Privacy policy last updated"
      },
      {
        "a": "not found in the text",
        "b": "not found in the text",
        "name": "Customer content may train models"
      },
      {
        "a": "not found in the text",
        "b": "not found in the text",
        "name": "Terms restrict automated access"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "not found in the text",
        "b": "yes",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not found in the text",
        "b": "not found in the text",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "619 stars",
        "b": "483k npm/wk, 71.5M PyPI/wk",
        "name": "Popularity"
      },
      {
        "a": "3.5/5 (8)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "GroqCloud scores 74.5 (BB) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 6 of 7 scored categories. Hugging Face Inference Providers leads on maintenance \u0026 community.",
        "question": "Which is better for AI agents, GroqCloud or Hugging Face Inference Providers?"
      },
      {
        "answer": "Both need an API key.",
        "question": "Do GroqCloud and Hugging Face Inference Providers need an API key?"
      },
      {
        "answer": "Yes. GroqCloud has a hosted endpoint at https://api.groq.com/openai/v1 and Hugging Face Inference Providers at https://router.huggingface.co/v1.",
        "question": "Can an agent call GroqCloud and Hugging Face Inference Providers without installing anything?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reliability, 90 against 25",
          "Agent ergonomics, 80 against 58",
          "Payments \u0026 pricing, 40 against 20",
          "Transparency \u0026 trust, 85 against 71"
        ],
        "also": [
          "Agent-ready, a grade of BB or better",
          "Free to start without a card"
        ],
        "goodFor": "Many small, latency-sensitive calls on open-weight models, routing, extraction and classification, and agents that need to start free.",
        "slug": "groq",
        "watchFor": "Four model shutdown dates between 2026-07-17 and 2026-09-21, with no stated minimum notice"
      },
      {
        "aheadOn": [
          "Maintenance \u0026 community, 80 against 72"
        ],
        "also": null,
        "goodFor": "Agents and developers who want open-weight models from several hosts on one token and one bill, with a public price and capability list per provider.",
        "slug": "hugging-face-inference-providers",
        "watchFor": "No rate limits, 429 behaviour or error responses documented for the router"
      }
    ],
    "history": {
      "groq": [
        {
          "causes": [
            "reliability",
            "evidence"
          ],
          "date": "2026-10-17",
          "delta": -1.1,
          "from": 75.6,
          "fromGrade": "BB",
          "to": 74.5,
          "toGrade": "BB"
        },
        {
          "causes": [
            "method"
          ],
          "date": "2026-10-08",
          "delta": -0.1,
          "from": 75.7,
          "fromGrade": "BB",
          "to": 75.6,
          "toGrade": "BB"
        }
      ],
      "hugging-face-inference-providers": null
    },
    "job": {
      "capability": "inference.llm",
      "name": "LLM inference"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-groq.json",
        "title": "Amazon Bedrock vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-groq"
      },
      {
        "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers.json",
        "title": "Amazon Bedrock vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-groq.json",
        "title": "Claude API vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-groq"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-hugging-face-inference-providers.json",
        "title": "Claude API vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/antseed-vs-groq.json",
        "title": "Antseed vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/antseed-vs-groq"
      },
      {
        "json": "https://www.anchorterminal.com/compare/azure-openai-vs-groq.json",
        "title": "Azure OpenAI in Foundry Models vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/azure-openai-vs-groq"
      },
      {
        "json": "https://www.anchorterminal.com/compare/azure-openai-vs-hugging-face-inference-providers.json",
        "title": "Azure OpenAI in Foundry Models vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/azure-openai-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-groq.json",
        "title": "BlockRun.AI vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-groq"
      },
      {
        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-hugging-face-inference-providers.json",
        "title": "BlockRun.AI vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-groq.json",
        "title": "Cerebras Inference vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-groq"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-hugging-face-inference-providers.json",
        "title": "Cerebras Inference vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-groq.json",
        "title": "Cloudflare AI Gateway vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-groq"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-hugging-face-inference-providers.json",
        "title": "Cloudflare AI Gateway vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-groq.json",
        "title": "Cloudflare Workers AI vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-groq"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-hugging-face-inference-providers.json",
        "title": "Cloudflare Workers AI vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-groq.json",
        "title": "Cohere Chat API (Command models) vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-groq"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-hugging-face-inference-providers.json",
        "title": "Cohere Chat API (Command models) vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-hugging-face-inference-providers"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepinfra-vs-groq.json",
        "title": "DeepInfra vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/deepinfra-vs-groq"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepinfra-vs-hugging-face-inference-providers.json",
        "title": "DeepInfra vs Hugging Face Inference Providers",
        "url": "https://www.anchorterminal.com/compare/deepinfra-vs-hugging-face-inference-providers"
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      {
        "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-groq.json",
        "title": "DeepSeek API vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-groq"
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      {
        "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-hugging-face-inference-providers.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-hugging-face-inference-providers"
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      {
        "json": "https://www.anchorterminal.com/compare/eden-ai-vs-groq.json",
        "title": "Eden AI vs GroqCloud",
        "url": "https://www.anchorterminal.com/compare/eden-ai-vs-groq"
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      {
        "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-groq.json",
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        "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-groq"
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        "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-hugging-face-inference-providers.json",
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        "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-hugging-face-inference-providers"
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      {
        "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-groq.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-groq.json",
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        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-hugging-face-inference-providers"
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        "json": "https://www.anchorterminal.com/compare/groq-vs-inkling-2-small.json",
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        "json": "https://www.anchorterminal.com/compare/groq-vs-jais-3.json",
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        "json": "https://www.anchorterminal.com/compare/groq-vs-meta-model-api.json",
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        "url": "https://www.anchorterminal.com/compare/groq-vs-minimax-api"
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        "json": "https://www.anchorterminal.com/compare/groq-vs-mistral-api.json",
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        "json": "https://www.anchorterminal.com/compare/groq-vs-muse-spark-open.json",
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        "url": "https://www.anchorterminal.com/compare/groq-vs-muse-spark-open"
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        "json": "https://www.anchorterminal.com/compare/groq-vs-nemotron-3-5-super-vl.json",
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        "url": "https://www.anchorterminal.com/compare/groq-vs-nemotron-3-5-super-vl"
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        "json": "https://www.anchorterminal.com/compare/groq-vs-novita-ai.json",
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        "json": "https://www.anchorterminal.com/compare/groq-vs-openai-api.json",
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        "json": "https://www.anchorterminal.com/compare/groq-vs-reflection-beam.json",
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        "json": "https://www.anchorterminal.com/compare/groq-vs-routerplus.json",
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        "json": "https://www.anchorterminal.com/compare/groq-vs-sambanova.json",
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        "json": "https://www.anchorterminal.com/compare/groq-vs-siliconflow.json",
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        "json": "https://www.anchorterminal.com/compare/groq-vs-vertex-ai.json",
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        "json": "https://www.anchorterminal.com/compare/groq-vs-xai-api.json",
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        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-minimax-api.json",
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        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-mistral-api.json",
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        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-novita-ai.json",
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        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-xai-api.json",
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        "json": "https://www.anchorterminal.com/compare/antseed-vs-hugging-face-inference-providers.json",
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    "panel": null,
    "scores": [
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        "by": 65,
        "edge": "groq",
        "groq": 90,
        "hugging-face-inference-providers": 25,
        "key": "reliability",
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 2,
        "edge": "groq",
        "groq": 64,
        "hugging-face-inference-providers": 62,
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "by": 22,
        "edge": "groq",
        "groq": 80,
        "hugging-face-inference-providers": 58,
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "by": 3,
        "edge": "groq",
        "groq": 82,
        "hugging-face-inference-providers": 79,
        "key": "security",
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "by": 20,
        "edge": "groq",
        "groq": 40,
        "hugging-face-inference-providers": 20,
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
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        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
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        "edge": "hugging-face-inference-providers",
        "groq": 72,
        "hugging-face-inference-providers": 80,
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "by": 14,
        "edge": "groq",
        "groq": 85,
        "hugging-face-inference-providers": 71,
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "GroqCloud scores 74.5 (BB) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 6 of 7 scored categories. Hugging Face Inference Providers leads on maintenance \u0026 community. Both do llm inference.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "groq": "Free plan with no card, at 30 requests a minute and 1,000 a day on gpt-oss. Four model shutdown dates between 2026-07-17 and 2026-09-21, with no stated minimum notice.",
      "hugging-face-inference-providers": "One Hugging Face token reaches open models on 18 partner providers at the providers' own prices, with a public model list that shows each provider's price, context and tool support. Router rate limits, error responses and its own status component were not found in the reviewed documentation, and free accounts have had no included credits since 7 October 2026."
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  "markdown": "GroqCloud scores 74.5 (BB) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 6 of 7 scored categories. Hugging Face Inference Providers leads on maintenance \u0026 community. Both do llm inference.\n\n- GroqCloud: grade BB, 74.5/100, rank #81 of 1510. Markdown https://www.anchorterminal.com/tools/groq.md · JSON https://www.anchorterminal.com/api/v1/tools/groq.json\n- Hugging Face Inference Providers: grade C, 54/100, rank #926 of 1510. Markdown https://www.anchorterminal.com/tools/hugging-face-inference-providers.md · JSON https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-providers.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 830 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### GroqCloud (BB)\n\nGood for: Many small, latency-sensitive calls on open-weight models, routing, extraction and classification, and agents that need to start free.\n\nAhead on:\n- Reliability, 90 against 25\n- Agent ergonomics, 80 against 58\n- Payments \u0026 pricing, 40 against 20\n- Transparency \u0026 trust, 85 against 71\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- Free to start without a card\n\nWatch for: Four model shutdown dates between 2026-07-17 and 2026-09-21, with no stated minimum notice\n\n### Hugging Face Inference Providers (C)\n\nGood for: Agents and developers who want open-weight models from several hosts on one token and one bill, with a public price and capability list per provider.\n\nAhead on:\n- Maintenance \u0026 community, 80 against 72\n\nWatch for: No rate limits, 429 behaviour or error responses documented for the router\n\n\n## Why the edge\n\n### Reliability: GroqCloud +65\n\n- GroqCloud (90): Status page at groqstatus.com on incident.io, with components for the API, each production and preview model and the website (20). The page's RSS feed and the incident pages it links, read on 1 November, list three incidents in the 90-day window, all in October, and nothing since 12 October apart from a console maintenance on 18 October. On 10 October the enterprise-only preview MiniMax M2.7 had failed requests from data centre hardware issues from 10:09 to 16:14 UTC. The incident's header and impact record say degraded performance, while its Identified update set the model to partial outage and warned of failed requests. On 12 October console.groq.com returned 500 errors on metrics, /models and key creation from 03:17 to 03:38, and the vendor said inference requests were not affected. On 12 October MiniMax M2.7 had a partial outage from 18:17 to 18:36. None took down a core API for an hour, since the six-hour incident hit one enterprise preview model that the status page describes as for evaluation only, so minor incidents only (20). A stricter reading would count it as a major and give 10. Limits published per model, 30 requests a minute, 1,000 a day and 8,000 tokens a minute on gpt-oss for the free plan, re-read on 1 November (15). 429 carries `retry-after`, `x-ratelimit-*` headers come on every response, and the errors page says to wait before retrying a 503 and that a 502 may clear on retry (15). The Performance Tier, enterprise only, lists a 99.9% availability SLA with details in the offline agreement, per the 6 October check, not re-read on 1 November (10). gpt-oss and Whisper models are production, Qwen 3.8 27B, MiniMax M2.7 and Muse Spark Open are previews (10). 20+20+15+15+10+10 = 90.\n- Hugging Face Inference Providers (25): Hosted lines. status.huggingface.co is a Better Stack page with 90-day component history for the Hub, Inference Endpoints, Spaces, the CDNs and Jobs, but no component for Inference Providers or the router (10 of 20). With no component, there is no readable incident history for the surface agents call, and the feed's 23 items from 10 June to 7 October 2026 don't name it (5). No rate limits for the router were found; the Hub rate-limits page gives numbers for Hub APIs, resolvers and pages only (0). No 429 or overload guidance for the router was found (0). No SLA found (0). Chat completions on the router is generally available; the Responses API is labelled beta (10). Routing between providers with `:fastest` or `:cheapest` softens a single provider's outage, which this checklist doesn't score.\n\n### Agent ergonomics: GroqCloud +22\n\n- GroqCloud (80): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use documented, parallel calls and forced choice not checked (15 of 20). Strict structured outputs (15). Automatic prompt caching at 50% off cached input, with a 2-hour cache life, on gpt-oss-20b, gpt-oss-120b and gpt-oss-safeguard-20b only (10 of 15). 131,072-token context on every self-serve model; only MiniMax M2.7, a preview on enterprise pricing, reaches 196,608 (5 of 15). Batch at half price (10). Official SDKs for Python and JavaScript (10). Errors page with codes, recovery advice and a typed error object (15).\n- Hugging Face Inference Providers (58): Router reading of the model checklist (tool use, structured output, caching, context, batch, SDKs, errors), as for openrouter. Tool calling through the OpenAI-compatible API with `tool_choice`, support flagged per provider in /v1/models (15 of 20). Structured output documented, support flagged per provider and false on some (10 of 15). No prompt caching guidance found, though the Enterprise usage API counts cached input tokens (3 of 15). Routes to models with up to 1,048,576 tokens of context per the model list, a judgement call since a router has no default model (15). No batch API (0 of 10). Official clients in Python and JavaScript, plus any OpenAI SDK (10). Errors not documented (5 of 15).\n\n### Payments \u0026 pricing: GroqCloud +20\n\n- GroqCloud (40): No machine payment protocol (0). Per-token prices on the models page, read without a login, such as gpt-oss-120b at $0.15 in and $0.60 out per million (20). Free plan with no card (20). Console sign-up in a browser (0).\n- Hugging Face Inference Providers (20): No x402, MPP or L402 (0). Per-token prices for every model and provider published without a login in the router's /v1/models and on model pages (20). No free tier since 7 October 2026, when free users lost their included monthly credits; PRO's $2.00 of credits needs a subscription (0). Sign-up, token creation and credit purchase are browser steps (0).\n\n### Transparency \u0026 trust: GroqCloud +14\n\n- GroqCloud (85): Closed service with clear terms, SDKs Apache-2.0 (15). The data page agrees with the listing on retention and adds detail, batch files kept 30 days unless deleted, fine-tuning data kept until the customer deletes it, and SCCs for transfers. The services agreement bars training on inputs and outputs, and the DPA gives 15 days' notice of sub-processor changes to subscribers, both read on 6 October. The agreement extends zero retention to 'Eligible Customers' where the data page says all customers may enable it (26 of 30). Deprecations page with announcement and shutdown dates (20). All customer data in Google Cloud buckets in the US, per the data page. The DPA points to a sub-processor list at trust.groq.com/subprocessors, which needs JavaScript and wasn't read (10 of 20).\n- Hugging Face Inference Providers (71): Closed service under Terms of Service that name Inference Providers, with an Apache-2.0 Python client and an MIT JavaScript client (20). The security page and the docs agree on no training, no stored bodies and 30-day logs, but the privacy policy dates from 28 March 2023 and each provider's own data policy governs the rest (18 of 30). No deprecation policy found. Provider support changes and the 7 October removal of free credits are dated only in the docs repository history (5 of 20). The privacy policy lists 11 subprocessors with countries per the Inference Endpoints check, and the docs name every provider a request can reach, though not where each runs (15 of 20).\n\n### Maintenance \u0026 community: Hugging Face Inference Providers +8\n\n- GroqCloud (72): Model reading. Meta's Muse Spark Open went into limited preview on GroqCloud on 15 October 2026, per Groq's announcement, 17 days before this check, and the models page lists it as an enterprise model (30). The newest shutdown is still `groq/compound` and `compound-mini` on 21 September. The changelog's newest entry is 18 April 2026, the Python SDK 1.7.0 (tagged 25 August) and TypeScript SDK 1.6.0 are still the newest tags, with commits to 4 September and no release since, and the deprecations page has no announcement after 24 August. Production models get an email and a migration path, previews may go at short notice, and no minimum period is stated. Llama 3.1 8B and 3.3 70B got 60 days on the free and developer tiers, Compound 28 days with no replacement named (4 of 12). Three shutdown dates in the 90 days to 1 November, 16 August, 14 September and 21 September. Three in 90 days is still frequent churn (0 of 8). A dated changelog with an RSS feed and a community forum exist, but the changelog's newest entry is 18 April 2026; support replies not checked (10 of 15). SDK issue replies not sampled, since GitHub's API refused our shell (5 of 10). Python SDK 1.7.0 and TypeScript SDK 1.6.0, both published on 26 August 2026 and still the newest tags on 1 November (15). CI, release-please and lock-file vulnerability fixes in 1.7.0 (8 of 10). 30+4+0+10+5+15+8 = 72.\n- Hugging Face Inference Providers (80): Model reading. huggingface_hub 2.4.0 tagged on 29 October 2026 and the Inference Providers docs updated daily by an automated job, last on 6 November (30). huggingface_hub 2.2.0, 2.3.0 and 2.4.0 and @huggingface/inference 4.13.28 to 4.13.32 in the 90 days (20). No dedicated changelog; the Hub has a forum and Discord, and GitHub issue replies were not read (8 of 15). Current official SDKs in Python and JavaScript (15). The Python client supports Python 3.10 and later, per the Inference Endpoints check; CI not read (7 of 10).\n\n## Score by category\n\n| Category | Weight | GroqCloud | Hugging Face Inference Providers | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 90 | 25 | GroqCloud +65 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 64 | 62 | GroqCloud +2 |\n| Agent ergonomics | 13% (16.2 this run) | 80 | 58 | GroqCloud +22 |\n| Security \u0026 auth | 14% (17.5 this run) | 82 | 79 | GroqCloud +3 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 20 | GroqCloud +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 72 | 80 | Hugging Face Inference Providers +8 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 85 | 71 | GroqCloud +14 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **74.5 · BB** | **54 · C** | |\n\n## Facts side by side\n\n| Fact | GroqCloud | Hugging Face Inference Providers |\n| --- | --- | --- |\n| Kind | Model API | Model router |\n| Vendor | Groq | Hugging Face, Inc. |\n| Hosted endpoint | `https://api.groq.com/openai/v1` | `https://router.huggingface.co/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Freemium | Pay per use |\n| x402 | no | no |\n| Licence | Apache-2.0 (SDKs) | Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-15 | 2026-10-29 |\n| Terms last updated | 2026-06-22 | 2022-09-15 |\n| Privacy policy last updated | 2025-11-12 | 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 | yes | 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 | not found in the text | not found in the text |\n| Popularity | 619 stars | 483k npm/wk, 71.5M PyPI/wk |\n| Agent reviews | 3.5/5 (8) | none |\n\n## How the scores have moved\n\n### GroqCloud\n\n- -1.1 on 17 October 2026: reliability, new evidence\n- -0.1 on 8 October 2026: checklist\n\n### Hugging Face Inference Providers\n\nNo score change since it was listed.\n\n## Verdicts\n\n**GroqCloud.** Free plan with no card, at 30 requests a minute and 1,000 a day on gpt-oss. Four model shutdown dates between 2026-07-17 and 2026-09-21, with no stated minimum notice.\n\n**Hugging Face Inference Providers.** One Hugging Face token reaches open models on 18 partner providers at the providers' own prices, with a public model list that shows each provider's price, context and tool support. Router rate limits, error responses and its own status component were not found in the reviewed documentation, and free accounts have had no included credits since 7 October 2026.\n\n## Before you call either\n\n### GroqCloud\n\n1. Call `/models` at start-up. Four model ids stopped working between July and September\n2. Read `retry-after` on a 429 and the `x-ratelimit-remaining-tokens` header before the next call\n3. Free plan allows 8,000 tokens a minute on gpt-oss, so keep prompts small or batch them\n4. Don't build on Qwen 3.8 27B. It's a preview and previews can go at short notice\n5. Treat a 498 as Flex capacity and retry later; server errors aren't billed\n\n### Hugging Face Inference Providers\n\n1. Read https://router.huggingface.co/v1/models before choosing a provider; it shows price, context and `supports_tools` per provider\n2. Pin a provider with `model:\u003cprovider\u003e` when tool calling or structured output matters, since support varies by provider\n3. Use a fine-grained token with only the Inference Providers permission, and send `X-HF-Bill-To` to bill an organisation\n4. Back off on 429 without assuming a Retry-After header, since none is documented for the router\n\n## Questions\n\n### Which is better for AI agents, GroqCloud or Hugging Face Inference Providers?\n\nGroqCloud scores 74.5 (BB) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 6 of 7 scored categories. Hugging Face Inference Providers leads on maintenance \u0026 community.\n\n### Do GroqCloud and Hugging Face Inference Providers need an API key?\n\nBoth need an API key.\n\n### Can an agent call GroqCloud and Hugging Face Inference Providers without installing anything?\n\nYes. GroqCloud has a hosted endpoint at https://api.groq.com/openai/v1 and Hugging Face Inference Providers at https://router.huggingface.co/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/groq-vs-hugging-face-inference-providers.json, and with the fewest tokens: https://www.anchorterminal.com/compare/groq-vs-hugging-face-inference-providers.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"groq\", \"b\": \"hugging-face-inference-providers\"}`. 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