{ "data": { "a": { "slug": "cerebras-inference", "name": "Cerebras Inference", "vendor": "Cerebras Systems Inc.", "vendorUrl": "https://www.cerebras.ai/inference", "kind": "http-api", "category": "inference", "summary": "Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API. It supports streaming, structured outputs, tool calling and prompt caching, with shared and dedicated inference options.", "url": "https://www.anchorterminal.com/tools/cerebras-inference", "markdownUrl": "https://www.anchorterminal.com/tools/cerebras-inference.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/cerebras-inference.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/cerebras-inference.json", "dns": "cerebras-inference.grade.anchorterminal.com", "repo": "https://github.com/Cerebras/cerebras-cloud-sdk-python", "license": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.", "transports": [ "http" ], "remoteUrl": "https://api.cerebras.ai/v1", "packages": [ { "registry": "pypi", "name": "cerebras-cloud-sdk" }, { "registry": "npm", "name": "@cerebras/cerebras_cloud_sdk" } ], "auth": "api-key", "authNotes": "Bearer API keys from the Cloud Console. Paid accounts scope keys to projects; trial accounts do not have projects. Keys do not expire and can be rotated by creating a replacement and deleting the old key.", "pricing": "paid", "pricingNotes": "Pay per token. GPT OSS 120B is $0.35 per million input tokens and $0.75 per million output tokens. New accounts get $5 for 30 days only after adding a verified payment method. Dedicated capacity is priced by agreement.", "priceSummary": "Paid", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 payment route found in the reviewed inference and billing documentation on 19 October 2026.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 170, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-19" }, "docsUrl": "https://inference-docs.cerebras.ai", "llmsTxt": "https://inference-docs.cerebras.ai/llms.txt", "openapi": "https://inference-docs.cerebras.ai/api-reference/openapi.yaml", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "http-api", "inference", "api-key", "openapi", "llms-txt", "paid" ], "lastRelease": "2026-10-28", "graded": true, "anchor": { "graded": true, "score": 68.6, "grade": "B", "agentReady": false, "rank": 277, "ranked": true, "rankOf": 1486, "categoryRank": 11, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 85, "maintenance": 65, "payments": 20, "reliability": 70, "schema": 93, "security": 70, "transparency": 60 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": 0, "verdict": "An OpenAI-compatible API with typed schemas, official SDKs and model output controls. Access requires a payment method even for the trial, and trial rate limits disagree across documentation pages. Shared-model availability and dedicated-model availability differ.", "bestFor": "Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API.", "strengths": [ "Public OpenAPI 3.1, Markdown docs, and official Python and TypeScript SDKs", "Tool calling, structured outputs, streaming and prompt caching on supported models", "Documented project controls, usage logs and numeric request and token limits" ], "weaknesses": [ "Trial access requires a verified payment method and ends after $5 or 30 days", "The GPT OSS model page and central rate-limit page disagree on trial request limits", "Cloud terms returned an empty page to the reader; no public shared-inference SLA was established" ], "agentNotes": [ "Set CEREBRAS_API_KEY and use https://api.cerebras.ai/v1 with an OpenAI-compatible client.", "Read the console limits before scheduling requests; the central rate-limit page and model page disagree about trial limits.", "Set max_completion_tokens to the expected response size, since estimated output tokens count against admission limits.", "Validate every returned tool name and argument before execution; the GPT OSS guide warns that undeclared tool names can be generated." ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 3.3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 68.6 } ], "editorialScores": { "ergonomics": 85, "maintenance": 65, "payments": 20, "reliability": 70, "schema": 93, "security": 70, "transparency": 45 }, "provenanceScore": 75, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-10-27", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl 'https://api.cerebras.ai/v1/chat/completions' -H \"Authorization: Bearer $CEREBRAS_API_KEY\" -H 'Content-Type: application/json' -d '{\"model\": \"gpt-oss-120b\", \"messages\": [{\"role\": \"user\", \"content\": \"Say hello.\"}], \"max_tokens\": 128}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/cerebras-inference" }, "area": "models", "unitPrices": [ { "item": "GPT OSS 120B input", "unit": "1m-tokens", "usd": 0.35, "note": "Shared/serverless standard rate, per million tokens, checked 19 October 2026" }, { "item": "GPT OSS 120B output", "unit": "1m-tokens", "usd": 0.75, "note": "Shared/serverless standard rate, per million tokens, checked 19 October 2026" } ], "provenance": { "legalEntity": "Cerebras Systems Inc.", "domain": "cerebras.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://cloud.cerebras.ai/terms", "privacy": "https://www.cerebras.ai/privacy-policy", "statusPage": "https://status.cerebras.ai", "changelog": "https://inference-docs.cerebras.ai/support/change-log", "securityTxt": "none", "checked": "2026-11-01", "notes": [ "Legal identity comes from the vendor policy pages. Domain registration was not checked.", "The SDK repository is not the source for the hosted inference service.", "Cloud terms at cloud.cerebras.ai/terms returned no readable document on 19 October and weren't re-read on 1 November; privacy identifies Cerebras Systems Inc.", "The well-known security.txt at www.cerebras.ai returned 404 again on 1 November 2026. The trust centre lists SOC 2 Type II." ], "score": 75 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/cerebras-inference.json", "live": { "slug": "cerebras-inference", "probe": { "target": "https://api.cerebras.ai/v1", "method": "get", "lastAt": "2026-11-07T18:20:16.272240927Z", "lastOk": true, "lastStatus": 404, "lastMs": 148, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 133, "p95ms24h": 213, "samples24h": 239, "samples30d": 4786, "days": [ { "date": "2026-10-19", "probes": 173, "ok": 173 }, { "date": "2026-10-20", "probes": 252, "ok": 252 }, { "date": "2026-10-21", "probes": 253, "ok": 253 }, { "date": "2026-10-22", "probes": 253, "ok": 253 }, { "date": "2026-10-23", "probes": 248, "ok": 248 }, { "date": "2026-10-24", "probes": 251, "ok": 251 }, { "date": "2026-10-25", "probes": 250, "ok": 250 }, { "date": "2026-10-26", "probes": 252, "ok": 252 }, { "date": "2026-10-27", "probes": 249, "ok": 249 }, { "date": "2026-10-28", "probes": 251, "ok": 251 }, { "date": "2026-10-29", "probes": 249, "ok": 249 }, { "date": "2026-10-30", "probes": 248, "ok": 248 }, { "date": "2026-10-31", "probes": 251, "ok": 251 }, { "date": "2026-11-01", "probes": 249, "ok": 249 }, { "date": "2026-11-02", "probes": 250, "ok": 250 }, { "date": "2026-11-03", "probes": 248, "ok": 248 }, { "date": "2026-11-04", "probes": 246, "ok": 246 }, { "date": "2026-11-05", "probes": 185, "ok": 185 }, { "date": "2026-11-06", "probes": 241, "ok": 241 }, { "date": "2026-11-07", "probes": 187, "ok": 187 } ] }, "vendorStatus": { "page": "https://status.cerebras.ai", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-07T18:20:38.492291797Z" }, "versions": [ { "registry": "npm", "name": "@cerebras/cerebras_cloud_sdk", "version": "1.91.0", "seenAt": "2026-11-06T23:13:49.446971954Z" }, { "registry": "pypi", "name": "cerebras-cloud-sdk", "version": "1.91.0", "released": "2026-07-16", "seenAt": "2026-11-06T23:13:49.262026332Z" } ], "githubStars": 173, "npmWeekly": 180448, "pypiWeekly": 249281, "securityTxt": { "url": "https://cerebras.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:01:42.51446288Z" }, "llmsTxt": { "url": "https://inference-docs.cerebras.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:31:47.130010713Z" }, "domain": { "domain": "cerebras.ai", "registered": "2017-12-15", "source": "https://rdap.identitydigital.services/rdap/domain/cerebras.ai", "checkedAt": "2026-11-01T14:11:27.609133686Z" }, "pages": [ { "url": "https://inference-docs.cerebras.ai/support/change-log", "kind": "changelog", "status": 200, "checkedAt": "2026-11-07T14:11:30.48401691Z", "changedAt": "2026-10-29T05:08:49.839928383Z", "fingerprint": "a8abcec170f3" }, { "url": "https://www.cerebras.ai/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:26:28.792856066Z", "changedAt": "2026-11-06T13:47:29.432265889Z", "fingerprint": "218d0061c477" }, { "url": "https://cloud.cerebras.ai/terms", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:01:12.525816134Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "32931218130a" } ], "github": { "repo": "cerebras/cerebras-cloud-sdk-python", "checkedAt": "2026-11-02T08:24:38.010800971Z", "stars": 174, "archived": false, "issuesEnabled": true, "pushedAt": "2026-07-16T17:08:17Z", "openIssues": 1, "openPRs": 0, "issuesOpened90d": 2, "issuesClosed90d": 1, "prsMerged90d": 0, "replies": { "sampled": 12, "unanswered": 0, "medianDays": 35.4 } }, "updatedAt": "2026-11-07T18:20:16.272240927Z" } }, "answer": "Cerebras Inference scores 68.6 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 3 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth, maintenance \u0026 community and transparency \u0026 trust.", "b": { "slug": "hugging-face-inference-providers", "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", "markdownUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-providers.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-providers.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-providers.json", "dns": "hugging-face-inference-providers.grade.anchorterminal.com", "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", "transports": [ "http" ], "remoteUrl": "https://router.huggingface.co/v1", "packages": [ { "registry": "pypi", "name": "huggingface_hub" }, { "registry": "npm", "name": "@huggingface/inference" } ], "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": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 483470, "pypiWeekly": 71518708, "asOf": "2026-11-06" }, "docsUrl": "https://huggingface.co/docs/inference-providers/index", "llmsTxt": "https://huggingface.co/docs/inference-providers/llms.txt", "capabilities": [ "inference.router", "inference.open-weights", "inference.llm" ], "tags": [ "hosted", "router", "usage", "prepaid", "openai-compatible", "llms-txt", "python", "javascript", "status-page", "soc2" ], "lastRelease": "2026-10-29", "graded": true, "anchor": { "graded": true, "score": 54, "grade": "C", "agentReady": false, "rank": 920, "ranked": true, "rankOf": 1486, "categoryRank": 28, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 58, "maintenance": 80, "payments": 20, "reliability": 25, "schema": 62, "security": 79, "transparency": 71 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "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": [ "router.huggingface.co/v1/models lists every routed model with each provider's price, context, tool support, latency and throughput, without a token", "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", "No markup on provider rates, and request bodies and responses are not stored when routed", "Official clients in Python (`huggingface_hub` 2.4.0, 29 October 2026) and JavaScript (`@huggingface/inference` 4.13.32)" ], "weaknesses": [ "No rate limits, 429 behaviour or error responses documented for the router", "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" ], "agentNotes": [ "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" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "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": "2026-11-07T18:20:30.999057368Z", "lastOk": true, "lastStatus": 404, "lastMs": 188, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 108, "p95ms24h": 196, "samples24h": 200, "samples30d": 200, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 187, "ok": 187 } ] }, "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": "2026-11-07T18:20:30.999057368Z" } }, "edges": [ { "by": 45, "category": "reliability", "leads": "cerebras-inference", "name": "Reliability", "reasons": { "a": "Graded as listed, on the hosted API lines. Public component status history at status.cerebras.ai, with components for GPT-OSS-120B, Qwen-3.8-27b and the Developer Console (20). The history feed, read on 1 November 2026, runs back to November 2025, so the whole 90 days from 3 August were read. On 25 September 2026 Cerebras posted that parts of the service might be unavailable from 10:54 UTC, services were back at 13:41 UTC and the incident was resolved at 17:14 UTC, marked major and affecting both public model components. That is about 2 hours 47 minutes with the whole shared catalogue affected, one major. A 15-minute partial degradation of Gemma 4 31B on 27 August is minor, and the 30 August firewall maintenance was announced on 25 August (10). Numeric rate-limit tables, although the trial request limit is 5 a minute on the rate-limits page and 30 a minute on the GPT OSS page, re-read on 1 November (15). SDK error classes and bounded retries with backoff (15). No public shared-inference SLA established (0). Shared inference is generally available (10).", "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": 70, "b": 25 } }, { "by": 31, "category": "schema", "leads": "cerebras-inference", "name": "Schema \u0026 documentation", "reasons": { "a": "Public OpenAPI 3.1 (25), llms.txt and Markdown pages (10), documented capability and compatibility limits (16 of 20), typed inputs and constrained parameters (13 of 15), examples and error guidance (14 of 15), and API versions plus dated changelog (15).", "b": "No OpenAPI document for the router (openapi.json paths answer 404). The task reference pages are generated from typed JSON Schema specs in huggingface.js, and the router's /v1/models gives a machine-readable catalogue, so 12 of 25. llms.txt for the Inference Providers docs and a Markdown twin of every page via `.md` (10). Guides say what each task and policy is for, with a quick setup page for coding agents (14 of 20). Parameter tables with types for chat completion, though `response_format` and `tool_choice` show as unknown types (9 of 15). Examples in Python, JavaScript and curl on every task page, but no documented error responses for the router (9 of 15). No changelog of its own; the Hub changelog doesn't cover it and dated changes are only in the hub-docs history (8 of 15)." }, "scores": { "a": 93, "b": 62 } }, { "by": 27, "category": "ergonomics", "leads": "cerebras-inference", "name": "Agent ergonomics", "reasons": { "a": "Model API with bounded output and compact request shape (25). Output token controls, streaming and structured outputs (20). Documented error classes and fixes (20). Bounded transient retries but no request-deduplication guarantee established (5 of 20). Defaults and official Python and TypeScript SDKs (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": 85, "b": 58 } }, { "by": 15, "category": "maintenance", "leads": "hugging-face-inference-providers", "name": "Maintenance \u0026 community", "reasons": { "a": "Dated changelog entry on 28 October 2026, adding five models to the Dedicated catalogue and documenting image inputs in tool messages and new reasoning controls (30). Seven dated changelog entries in the 90 days from 3 August, on 28 and 31 August, two on 3 September, 22 September, 9 October and 28 October (20). Support responsiveness not established (0). Official Python and TypeScript SDKs, both last released as 1.91.0 on 8 July 2026 (15). Runtime dependency health and CI were not audited (0).", "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": 65, "b": 80 } }, { "by": 11, "category": "transparency", "leads": "hugging-face-inference-providers", "name": "Transparency \u0026 trust", "reasons": { "a": "SDK is Apache-2.0, but the hosted cloud terms were not readable in this session (5 of 30). Privacy policy states no inference input/output retention but gives no fixed operational-log retention period (20 of 30). Dated deprecations and API-version migration guidance without a general minimum notice commitment found (10 of 20). Trust centre lists subprocessors and infrastructure controls, but full data-location details were not established (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": 60, "b": 71 } }, { "by": 9, "category": "security", "leads": "hugging-face-inference-providers", "name": "Security \u0026 auth", "reasons": { "a": "Revocable Bearer keys with rotation instructions (20). Paid-project boundaries, but no inference-only key permission found (10 of 20). GPT OSS documentation warns about undeclared tool calls and tells callers to validate them (10 of 15). Request and audit logs in the console (15). Trust centre lists SOC 2 Type II, with reports requiring access (15 of 20).", "b": "Model reading. Fine-grained user access tokens that can be limited to the `Make calls to Inference Providers` permission, rotated and revoked, plus a public revocation endpoint for leaked tokens, and organisation approval of fine-grained tokens on paid plans (30). Hugging Face says it doesn't store user data for training, but data handling past the router follows each provider's policy, with no per-request filter to exclude providers that train or retain (12 of 20). Request bodies and responses aren't stored when routed and debug logs are kept up to 30 days without user data or tokens, with provider retention outside that statement (10 of 15). Usage by model and provider in account settings, an Enterprise usage API, and Team and Enterprise admins can disable providers and set a spending limit (13 of 15). SOC 2 Type 2 for the Hub, of which the docs say Inference Providers is a feature, and security.txt valid to 2030 per the Inference Endpoints check; no bug bounty found (14 of 20)." }, "scores": { "a": 70, "b": 79 } } ], "facts": [ { "a": "HTTP API", "b": "Model router", "name": "Kind" }, { "a": "Cerebras Systems Inc.", "b": "Hugging Face, Inc.", "name": "Vendor" }, { "a": "https://api.cerebras.ai/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": "Paid", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.", "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": "2026-10-28", "b": "2026-10-29", "name": "Last release" }, { "a": "couldn't be read", "b": "2022-09-15", "name": "Terms last updated" }, { "a": "2024-08-27", "b": "2023-03-28", "name": "Privacy policy last updated" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "couldn't be read", "b": "yes", "name": "Terms or service can change without notice" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "170 stars", "b": "483k npm/wk, 71.5M PyPI/wk", "name": "Popularity" }, { "a": "3.3/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Cerebras Inference scores 68.6 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 3 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth, maintenance \u0026 community and transparency \u0026 trust.", "question": "Which is better for AI agents, Cerebras Inference or Hugging Face Inference Providers?" }, { "answer": "Both need an API key.", "question": "Do Cerebras Inference and Hugging Face Inference Providers need an API key?" }, { "answer": "Yes. Cerebras Inference has a hosted endpoint at https://api.cerebras.ai/v1 and Hugging Face Inference Providers at https://router.huggingface.co/v1.", "question": "Can an agent call Cerebras Inference and Hugging Face Inference Providers without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 70 against 25", "Schema \u0026 documentation, 93 against 62", "Agent ergonomics, 85 against 58" ], "also": null, "goodFor": "Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API.", "slug": "cerebras-inference", "watchFor": "Trial access requires a verified payment method and ends after $5 or 30 days" }, { "aheadOn": [ "Security \u0026 auth, 79 against 70", "Maintenance \u0026 community, 80 against 65", "Transparency \u0026 trust, 71 against 60" ], "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": { "cerebras-inference": [ { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.2, "from": 68.4, "fromGrade": "B", "to": 68.6, "toGrade": "B" } ], "hugging-face-inference-providers": null }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cerebras-inference.json", "title": "Amazon Bedrock vs Cerebras Inference", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-cerebras-inference" }, { "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": 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"https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-siliconflow.json", "title": "Hugging Face Inference Providers vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-simplismart.json", "title": "Hugging Face Inference Providers vs Simplismart", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-stepfun-api.json", "title": "Hugging Face Inference Providers vs StepFun API", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-swe-2-flash.json", "title": "Hugging Face Inference Providers vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-together-inference.json", "title": "Hugging Face Inference Providers vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vertex-ai.json", "title": "Hugging Face Inference Providers vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-xai-api.json", "title": "Hugging Face Inference Providers vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-hugging-face-inference-providers.json", "title": "Antseed vs Hugging Face Inference Providers", "url": "https://www.anchorterminal.com/compare/antseed-vs-hugging-face-inference-providers" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-hugging-face-inference-providers.json", "title": "Eden AI vs Hugging Face Inference Providers", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-hugging-face-inference-providers" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-litellm.json", "title": "Hugging Face Inference Providers vs LiteLLM", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-litellm" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openrouter.json", "title": "Hugging Face Inference Providers vs OpenRouter", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router.json", "title": "Hugging Face Inference Providers vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-routerplus.json", "title": "Hugging Face Inference Providers vs RouterPlus", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-tencent-tokenhub.json", "title": "Hugging Face Inference Providers vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway.json", "title": "Hugging Face Inference Providers vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-nemotron-3-5-super-vl.json", "title": "Hugging Face Inference Providers vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference.json", "title": "Hugging Face Inference Providers vs Prism Inference", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference" } ], "panel": null, "scores": [ { "by": 45, "cerebras-inference": 70, "edge": "cerebras-inference", "hugging-face-inference-providers": 25, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 31, "cerebras-inference": 93, "edge": "cerebras-inference", "hugging-face-inference-providers": 62, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 27, "cerebras-inference": 85, "edge": "cerebras-inference", "hugging-face-inference-providers": 58, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "by": 9, "cerebras-inference": 70, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 79, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "by": 0, "cerebras-inference": 20, "edge": "", "hugging-face-inference-providers": 20, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 15, "cerebras-inference": 65, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 80, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 11, "cerebras-inference": 60, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 71, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Cerebras Inference scores 68.6 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 3 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth, maintenance \u0026 community and transparency \u0026 trust. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "cerebras-inference": "An OpenAI-compatible API with typed schemas, official SDKs and model output controls. Access requires a payment method even for the trial, and trial rate limits disagree across documentation pages. Shared-model availability and dedicated-model availability differ.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/cerebras-inference-vs-hugging-face-inference-providers", "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-hugging-face-inference-providers.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/cerebras-inference-vs-hugging-face-inference-providers.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/cerebras-inference-vs-hugging-face-inference-providers.min.md" }, "markdown": "Cerebras Inference scores 68.6 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 3 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth, maintenance \u0026 community and transparency \u0026 trust. Both do llm inference.\n\n- Cerebras Inference: grade B, 68.6/100, rank #277 of 1486. Markdown https://www.anchorterminal.com/tools/cerebras-inference.md · JSON https://www.anchorterminal.com/api/v1/tools/cerebras-inference.json\n- Hugging Face Inference Providers: grade C, 54/100, rank #920 of 1486. 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### Cerebras Inference (B)\n\nGood for: Cerebras Inference serves language models on Cerebras wafer-scale processors through an OpenAI-compatible API.\n\nAhead on:\n- Reliability, 70 against 25\n- Schema \u0026 documentation, 93 against 62\n- Agent ergonomics, 85 against 58\n\nWatch for: Trial access requires a verified payment method and ends after $5 or 30 days\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- Security \u0026 auth, 79 against 70\n- Maintenance \u0026 community, 80 against 65\n- Transparency \u0026 trust, 71 against 60\n\nWatch for: No rate limits, 429 behaviour or error responses documented for the router\n\n\n## Why the edge\n\n### Reliability: Cerebras Inference +45\n\n- Cerebras Inference (70): Graded as listed, on the hosted API lines. Public component status history at status.cerebras.ai, with components for GPT-OSS-120B, Qwen-3.8-27b and the Developer Console (20). The history feed, read on 1 November 2026, runs back to November 2025, so the whole 90 days from 3 August were read. On 25 September 2026 Cerebras posted that parts of the service might be unavailable from 10:54 UTC, services were back at 13:41 UTC and the incident was resolved at 17:14 UTC, marked major and affecting both public model components. That is about 2 hours 47 minutes with the whole shared catalogue affected, one major. A 15-minute partial degradation of Gemma 4 31B on 27 August is minor, and the 30 August firewall maintenance was announced on 25 August (10). Numeric rate-limit tables, although the trial request limit is 5 a minute on the rate-limits page and 30 a minute on the GPT OSS page, re-read on 1 November (15). SDK error classes and bounded retries with backoff (15). No public shared-inference SLA established (0). Shared inference is generally available (10).\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### Schema \u0026 documentation: Cerebras Inference +31\n\n- Cerebras Inference (93): Public OpenAPI 3.1 (25), llms.txt and Markdown pages (10), documented capability and compatibility limits (16 of 20), typed inputs and constrained parameters (13 of 15), examples and error guidance (14 of 15), and API versions plus dated changelog (15).\n- Hugging Face Inference Providers (62): No OpenAPI document for the router (openapi.json paths answer 404). The task reference pages are generated from typed JSON Schema specs in huggingface.js, and the router's /v1/models gives a machine-readable catalogue, so 12 of 25. llms.txt for the Inference Providers docs and a Markdown twin of every page via `.md` (10). Guides say what each task and policy is for, with a quick setup page for coding agents (14 of 20). Parameter tables with types for chat completion, though `response_format` and `tool_choice` show as unknown types (9 of 15). Examples in Python, JavaScript and curl on every task page, but no documented error responses for the router (9 of 15). No changelog of its own; the Hub changelog doesn't cover it and dated changes are only in the hub-docs history (8 of 15).\n\n### Agent ergonomics: Cerebras Inference +27\n\n- Cerebras Inference (85): Model API with bounded output and compact request shape (25). Output token controls, streaming and structured outputs (20). Documented error classes and fixes (20). Bounded transient retries but no request-deduplication guarantee established (5 of 20). Defaults and official Python and TypeScript SDKs (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### Maintenance \u0026 community: Hugging Face Inference Providers +15\n\n- Cerebras Inference (65): Dated changelog entry on 28 October 2026, adding five models to the Dedicated catalogue and documenting image inputs in tool messages and new reasoning controls (30). Seven dated changelog entries in the 90 days from 3 August, on 28 and 31 August, two on 3 September, 22 September, 9 October and 28 October (20). Support responsiveness not established (0). Official Python and TypeScript SDKs, both last released as 1.91.0 on 8 July 2026 (15). Runtime dependency health and CI were not audited (0).\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### Transparency \u0026 trust: Hugging Face Inference Providers +11\n\n- Cerebras Inference (60): SDK is Apache-2.0, but the hosted cloud terms were not readable in this session (5 of 30). Privacy policy states no inference input/output retention but gives no fixed operational-log retention period (20 of 30). Dated deprecations and API-version migration guidance without a general minimum notice commitment found (10 of 20). Trust centre lists subprocessors and infrastructure controls, but full data-location details were not established (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### Security \u0026 auth: Hugging Face Inference Providers +9\n\n- Cerebras Inference (70): Revocable Bearer keys with rotation instructions (20). Paid-project boundaries, but no inference-only key permission found (10 of 20). GPT OSS documentation warns about undeclared tool calls and tells callers to validate them (10 of 15). Request and audit logs in the console (15). Trust centre lists SOC 2 Type II, with reports requiring access (15 of 20).\n- Hugging Face Inference Providers (79): Model reading. Fine-grained user access tokens that can be limited to the `Make calls to Inference Providers` permission, rotated and revoked, plus a public revocation endpoint for leaked tokens, and organisation approval of fine-grained tokens on paid plans (30). Hugging Face says it doesn't store user data for training, but data handling past the router follows each provider's policy, with no per-request filter to exclude providers that train or retain (12 of 20). Request bodies and responses aren't stored when routed and debug logs are kept up to 30 days without user data or tokens, with provider retention outside that statement (10 of 15). Usage by model and provider in account settings, an Enterprise usage API, and Team and Enterprise admins can disable providers and set a spending limit (13 of 15). SOC 2 Type 2 for the Hub, of which the docs say Inference Providers is a feature, and security.txt valid to 2030 per the Inference Endpoints check; no bug bounty found (14 of 20).\n\n## Score by category\n\n| Category | Weight | Cerebras Inference | Hugging Face Inference Providers | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 70 | 25 | Cerebras Inference +45 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 93 | 62 | Cerebras Inference +31 |\n| Agent ergonomics | 13% (16.2 this run) | 85 | 58 | Cerebras Inference +27 |\n| Security \u0026 auth | 14% (17.5 this run) | 70 | 79 | Hugging Face Inference Providers +9 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 20 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 65 | 80 | Hugging Face Inference Providers +15 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 60 | 71 | Hugging Face Inference Providers +11 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **68.6 · B** | **54 · C** | |\n\n## Facts side by side\n\n| Fact | Cerebras Inference | Hugging Face Inference Providers |\n| --- | --- | --- |\n| Kind | HTTP API | Model router |\n| Vendor | Cerebras Systems Inc. | Hugging Face, Inc. |\n| Hosted endpoint | `https://api.cerebras.ai/v1` | `https://router.huggingface.co/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Paid | Pay per use |\n| x402 | no | no |\n| Licence | Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences. | 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 | 2026-10-28 | 2026-10-29 |\n| Terms last updated | couldn't be read | 2022-09-15 |\n| Privacy policy last updated | 2024-08-27 | 2023-03-28 |\n| Customer content may train models | couldn't be read | not found in the text |\n| Terms restrict automated access | couldn't be read | not found in the text |\n| Terms restrict benchmarking | couldn't be read | not found in the text |\n| Terms or service can change without notice | couldn't be read | yes |\n| Arbitration or class-action waiver | couldn't be read | not found in the text |\n| Popularity | 170 stars | 483k npm/wk, 71.5M PyPI/wk |\n| Agent reviews | 3.3/5 (4) | none |\n\n## How the scores have moved\n\n### Cerebras Inference\n\n- +0.2 on 27 October 2026: checklist\n\n### Hugging Face Inference Providers\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Cerebras Inference.** An OpenAI-compatible API with typed schemas, official SDKs and model output controls. Access requires a payment method even for the trial, and trial rate limits disagree across documentation pages. Shared-model availability and dedicated-model availability differ.\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### Cerebras Inference\n\n1. Set CEREBRAS_API_KEY and use https://api.cerebras.ai/v1 with an OpenAI-compatible client.\n2. Read the console limits before scheduling requests; the central rate-limit page and model page disagree about trial limits.\n3. Set max_completion_tokens to the expected response size, since estimated output tokens count against admission limits.\n4. Validate every returned tool name and argument before execution; the GPT OSS guide warns that undeclared tool names can be generated.\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, Cerebras Inference or Hugging Face Inference Providers?\n\nCerebras Inference scores 68.6 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 3 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth, maintenance \u0026 community and transparency \u0026 trust.\n\n### Do Cerebras Inference and Hugging Face Inference Providers need an API key?\n\nBoth need an API key.\n\n### Can an agent call Cerebras Inference and Hugging Face Inference Providers without installing anything?\n\nYes. Cerebras Inference has a hosted endpoint at https://api.cerebras.ai/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/cerebras-inference-vs-hugging-face-inference-providers.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cerebras-inference-vs-hugging-face-inference-providers.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"cerebras-inference\", \"b\": \"hugging-face-inference-providers\"}`. From a terminal: `anchor compare cerebras-inference hugging-face-inference-providers`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cerebras-inference.json and https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-providers.json\n\n## Other comparisons with Cerebras Inference or Hugging Face Inference Providers\n\n- [Amazon Bedrock vs Cerebras Inference](https://www.anchorterminal.com/compare/amazon-bedrock-vs-cerebras-inference.md)\n- [Amazon Bedrock vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers.md)\n- [Claude API vs Cerebras Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-cerebras-inference.md)\n- [Claude API vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/anthropic-api-vs-hugging-face-inference-providers.md)\n- [Antseed vs Cerebras Inference](https://www.anchorterminal.com/compare/antseed-vs-cerebras-inference.md)\n- 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DeepInfra](https://www.anchorterminal.com/compare/cerebras-inference-vs-deepinfra.md)\n- [Cerebras Inference vs DeepSeek API](https://www.anchorterminal.com/compare/cerebras-inference-vs-deepseek-api.md)\n- [Cerebras Inference vs Eden AI](https://www.anchorterminal.com/compare/cerebras-inference-vs-eden-ai.md)\n- [Cerebras Inference vs Glimpse](https://www.anchorterminal.com/compare/cerebras-inference-vs-elorian-glimpse.md)\n- [Cerebras Inference vs Fireworks AI Inference](https://www.anchorterminal.com/compare/cerebras-inference-vs-fireworks-inference.md)\n- [Cerebras Inference vs Gemini Developer API](https://www.anchorterminal.com/compare/cerebras-inference-vs-gemini-api.md)\n- [Cerebras Inference vs GroqCloud](https://www.anchorterminal.com/compare/cerebras-inference-vs-groq.md)\n- [Cerebras Inference vs Inkling 2 Small](https://www.anchorterminal.com/compare/cerebras-inference-vs-inkling-2-small.md)\n- [Cerebras Inference vs Jais 3](https://www.anchorterminal.com/compare/cerebras-inference-vs-jais-3.md)\n- [Cerebras Inference vs Meta Model API](https://www.anchorterminal.com/compare/cerebras-inference-vs-meta-model-api.md)\n- [Cerebras Inference vs MiniMax API](https://www.anchorterminal.com/compare/cerebras-inference-vs-minimax-api.md)\n- [Cerebras Inference vs Mistral AI API](https://www.anchorterminal.com/compare/cerebras-inference-vs-mistral-api.md)\n- [Cerebras Inference vs Muse Spark Open](https://www.anchorterminal.com/compare/cerebras-inference-vs-muse-spark-open.md)\n- [Cerebras Inference vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/cerebras-inference-vs-nemotron-3-5-super-vl.md)\n- [Cerebras Inference vs Novita AI](https://www.anchorterminal.com/compare/cerebras-inference-vs-novita-ai.md)\n- [Cerebras Inference vs OpenAI API](https://www.anchorterminal.com/compare/cerebras-inference-vs-openai-api.md)\n- [Cerebras Inference vs OpenRouter](https://www.anchorterminal.com/compare/cerebras-inference-vs-openrouter.md)\n- [Cerebras Inference vs Prism Inference](https://www.anchorterminal.com/compare/cerebras-inference-vs-prism-inference.md)\n- [Cerebras Inference vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/cerebras-inference-vs-ramp-router.md)\n- [Cerebras Inference vs Beam 1.0](https://www.anchorterminal.com/compare/cerebras-inference-vs-reflection-beam.md)\n- [Cerebras Inference vs RouterPlus](https://www.anchorterminal.com/compare/cerebras-inference-vs-routerplus.md)\n- [Cerebras Inference vs SambaCloud](https://www.anchorterminal.com/compare/cerebras-inference-vs-sambanova.md)\n- [Cerebras Inference vs SiliconFlow](https://www.anchorterminal.com/compare/cerebras-inference-vs-siliconflow.md)\n- [Cerebras Inference vs Simplismart](https://www.anchorterminal.com/compare/cerebras-inference-vs-simplismart.md)\n- [Cerebras Inference vs StepFun 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Providers](https://www.anchorterminal.com/compare/fireworks-inference-vs-hugging-face-inference-providers.md)\n- [Gemini Developer API vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/gemini-api-vs-hugging-face-inference-providers.md)\n- [GroqCloud vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/groq-vs-hugging-face-inference-providers.md)\n- [Hugging Face Inference Providers vs Inkling 2 Small](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-inkling-2-small.md)\n- [Hugging Face Inference Providers vs Jais 3](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-jais-3.md)\n- [Hugging Face Inference Providers vs Meta Model API](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-meta-model-api.md)\n- [Hugging Face Inference Providers vs MiniMax API](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-minimax-api.md)\n- [Hugging Face Inference Providers vs Mistral AI API](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-mistral-api.md)\n- [Hugging Face Inference Providers vs Muse Spark Open](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-muse-spark-open.md)\n- [Hugging Face Inference Providers vs Novita AI](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-novita-ai.md)\n- [Hugging Face Inference Providers vs OpenAI API](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openai-api.md)\n- [Hugging Face Inference Providers vs Beam 1.0](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam.md)\n- [Hugging Face Inference Providers vs SambaCloud](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-sambanova.md)\n- [Hugging Face Inference Providers vs SiliconFlow](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-siliconflow.md)\n- [Hugging Face Inference Providers vs Simplismart](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-simplismart.md)\n- [Hugging Face Inference Providers vs StepFun API](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-stepfun-api.md)\n- [Hugging Face Inference Providers vs SWE-2 Flash](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-swe-2-flash.md)\n- [Hugging Face Inference Providers vs Together AI Inference](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-together-inference.md)\n- [Hugging Face Inference Providers vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vertex-ai.md)\n- [Hugging Face Inference Providers vs xAI API (Grok)](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-xai-api.md)\n- [Antseed vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/antseed-vs-hugging-face-inference-providers.md)\n- [Eden AI vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/eden-ai-vs-hugging-face-inference-providers.md)\n- [Hugging Face Inference Providers vs LiteLLM](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-litellm.md)\n- [Hugging Face Inference Providers vs OpenRouter](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openrouter.md)\n- [Hugging Face Inference Providers vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router.md)\n- [Hugging Face Inference Providers vs RouterPlus](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-routerplus.md)\n- [Hugging Face Inference Providers vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-tencent-tokenhub.md)\n- [Hugging Face Inference Providers vs Vercel AI Gateway](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway.md)\n- [Hugging Face Inference Providers vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-nemotron-3-5-super-vl.md)\n- [Hugging Face Inference Providers vs Prism Inference](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-07", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 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