{ "data": { "a": { "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": 926, "ranked": true, "rankOf": 1510, "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": "2026-11-07T19:22:12.474650545Z", "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" } }, "answer": "Hugging Face Inference Providers and Beam 1.0 score within a point of each other on agent readiness, 54 (C) and 53.4 (D). Beam 1.0 leads on reliability, schema \u0026 documentation and agent ergonomics.", "b": { "slug": "reflection-beam", "name": "Beam 1.0", "vendor": "Reflection", "vendorUrl": "https://reflection.ai", "kind": "model", "category": "inference", "summary": "Beam 1.0 is Reflection's open-weight text model for coding, reasoning and agentic work, with 501B total and 23B active parameters and a 1M-token context, served by the Reflection API and released as Apache-2.0 weights.", "url": "https://www.anchorterminal.com/tools/reflection-beam", "markdownUrl": "https://www.anchorterminal.com/tools/reflection-beam.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/reflection-beam.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/reflection-beam.json", "dns": "reflection-beam.grade.anchorterminal.com", "repo": "https://huggingface.co/reflection/Beam-1.0-501B-A23B", "license": "Weights under Apache-2.0. The hosted Reflection API is a closed service under Reflection's commercial terms of service", "transports": [ "http" ], "remoteUrl": "https://api.reflection.ai/openai/v1", "packages": [], "auth": "api-key", "authNotes": "Bearer API key created by a person on platform.reflection.ai under API Keys. Each key belongs to one project and to the user who made it, is shown once, can be revoked from the API Keys page, and is disabled if that user leaves the organisation or project. No scopes, expiry or key-management API found. The docs say some organisations must verify a credit card in Billing before their keys work (`payment_method_required`). Self-hosted weights need no account; the Hugging Face repositories are not gated.", "pricing": "freemium", "pricingNotes": "No per-token or plan price for the Reflection API is published on a page we can read. The rate-limits docs describe a daily token allowance that renews at 00:00 UTC and ask those requesting higher limits whether they want paid usage, and some organisations must verify a credit card before keys work (https://developers.reflection.ai/rate-limits.md, checked 2026-11-04). Reflection's beta pricing page and terms are on reflection.ai, which disallows our crawler. The weights are free to self-host under Apache-2.0.", "priceSummary": "Freemium", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the Reflection docs, llms.txt or OpenAPI document. Access needs a browser sign-up on platform.reflection.ai and an API key (checked 2026-11-04).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-17" }, "docsUrl": "https://developers.reflection.ai/introduction", "rateLimitsUrl": "https://developers.reflection.ai/rate-limits", "llmsTxt": "https://developers.reflection.ai/llms.txt", "openapi": "https://developers.reflection.ai/api-reference/openapi.yaml", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "hosted", "model", "open-weights", "self-hosted", "free", "openai-compatible", "openapi", "llms-txt", "status-page", "apache-2.0", "gpu", "new" ], "lastRelease": "2026-10-16", "graded": true, "anchor": { "graded": true, "score": 53.4, "grade": "D", "agentReady": false, "rank": 948, "ranked": true, "rankOf": 1510, "categoryRank": 31, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 67, "maintenance": 50, "payments": 10, "reliability": 52, "schema": 84, "security": 45, "transparency": 57 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-04" }, "negative": 0, "verdict": "The Reflection API is OpenAI-compatible, with an OpenAPI document, strict structured outputs and tool calls, and error codes that say when to retry, and the weights are Apache-2.0. No price or rate-limit figure is published on a readable page, reasoning can't be turned off, and the API had two full outages on 14 and 15 October 2026.", "bestFor": "An OpenAI-compatible endpoint for a large open-weight coding and agent model, for builders who want the same model hosted or self-hosted under Apache-2.0.", "strengths": [ "OpenAI-compatible Chat Completions with `tool_choice`, parallel tool calls, strict tool schemas and `json_schema` structured outputs", "Error reference lists every status and code with whether to retry, and responses carry `Retry-After`, `x-should-retry` and `x-request-id`", "OpenAPI 3.0.3 document, llms.txt, a Markdown copy of every page and a docs MCP endpoint at developers.reflection.ai/mcp", "1,048,576-token context and up to 131,072 output tokens, with reasoning returned in its own `reasoning_content` field", "Weights in BF16, FP8 and NVFP4 under Apache-2.0, ungated, with Reflection's guides for SGLang, vLLM, TokenSpeed, Transformers, Helm and Dynamo" ], "weaknesses": [ "No SLA, and per-organisation rate limits and the daily token allowance are not published as numbers", "Reasoning is mandatory and defaults to `max`, and a tool-call turn returned without `reasoning_content` makes every later request in that session fail", "No per-token price, retention period or subprocessor list on a page we can read; Reflection's terms and pricing pages are on a host that disallows our crawler", "Two API incidents labelled full outages on 14 and 15 October 2026 and three partial ones to 3 November", "No changelog and no model deprecation notice period found" ], "agentNotes": [ "Send `reasoning_effort` `low` or `medium` for short tasks. The default is `max`, and `none` or `minimal` return `400 unsupported_value`", "Return every assistant message with its `reasoning_content` unchanged. If a turn comes back without it, start a new conversation, since later requests fail with `missing_required_parameter`", "Don't rely on `stop` or `seed`. Both are accepted and ignored, so truncate output in your own code", "Honour `x-should-retry: false` on a 429. It means a daily limit is spent and `Retry-After` counts to 00:00 UTC", "Set `max_completion_tokens` yourself on long prompts. The default budget isn't reduced to fit the prompt and includes reasoning tokens" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 53.4 } ], "editorialScores": { "ergonomics": 67, "maintenance": 50, "payments": 10, "reliability": 52, "schema": 84, "security": 45, "transparency": 39 }, "provenanceScore": 74, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install openai # or: npm install openai, with base URL https://api.reflection.ai/openai/v1", "http": "curl https://api.reflection.ai/openai/v1/chat/completions \\\n -H \"Authorization: Bearer $REFLECTION_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"Beam-1.0-501B-A23B\",\n \"messages\": [\n {\"role\": \"user\", \"content\": \"Why is the sky blue?\"}\n ]\n }'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/reflection-beam" }, "sameCompany": [ "reflection-mirror" ], "area": "models", "provenance": { "legalEntity": "Reflection AI", "domain": "reflection.ai", "domainRegistered": "2017-12-16", "domainNote": "RDAP gave a registration date of 16 December 2017 and a transfer on 15 March 2024 on 17 October 2026 (not re-read; RDAP is a JSON service), so the domain predates the current owner.", "endpointOnVendorDomain": true, "terms": "https://reflection.ai/legal/commercial-terms-of-service", "privacy": "https://reflection.ai/legal/privacy-policy", "statusPage": "https://status.reflection.ai", "changelog": "", "securityTxt": "unknown", "checked": "2026-11-04", "notes": [ "reflection.ai's robots.txt disallows ClaudeBot, Claude-Web and anthropic-ai (read 4 November 2026), so the commercial terms, the privacy policy and reflection.ai's security.txt weren't re-read and their 17 October readings are struck. Both URLs are kept as listed facts.", "The legal entity is the copyright holder in the NOTICE files of Reflection's Mirror repository (`Copyright 2026 Reflection AI`), as on the reflection-mirror listing, since the fuller name came from struck pages.", "developers.reflection.ai/.well-known/security.txt returned 404 on 17 October 2026. The model card names reports@reflection.ai for security vulnerabilities.", "No changelog or release notes found in the developers docs or llms.txt (4 November 2026).", "status.reflection.ai answers robots.txt with a plain 404 (no rules) and was read under it." ], "score": 74 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/reflection-beam.json", "live": { "slug": "reflection-beam", "probe": { "target": "https://api.reflection.ai/openai/v1", "method": "get", "lastAt": "2026-11-07T19:22:29.425830355Z", "lastOk": true, "lastStatus": 404, "lastMs": 385, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 357, "p95ms24h": 465, "samples24h": 238, "samples30d": 5155, "days": [ { "date": "2026-10-17", "probes": 21, "ok": 21 }, { "date": "2026-10-18", "probes": 256, "ok": 256 }, { "date": "2026-10-19", "probes": 255, "ok": 255 }, { "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": 250, "ok": 250 }, { "date": "2026-10-29", "probes": 249, "ok": 249 }, { "date": "2026-10-30", "probes": 249, "ok": 249 }, { "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": 197, "ok": 197 } ] }, "vendorStatus": { "page": "https://status.reflection.ai", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-07T19:23:40.366207063Z" }, "securityTxt": { "url": "https://reflection.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:01:01.339118919Z" }, "llmsTxt": { "url": "https://developers.reflection.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:33:44.238449696Z" }, "domain": { "domain": "reflection.ai", "registered": "2017-12-16", "source": "https://rdap.identitydigital.services/rdap/domain/reflection.ai", "checkedAt": "2026-11-01T14:25:19.009468335Z" }, "pages": [ { "url": "https://reflection.ai/legal/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:18:16.340207649Z", "changedAt": "2026-11-07T14:18:16.340207649Z", "fingerprint": "10e2a9daf712" }, { "url": "https://reflection.ai/legal/commercial-terms-of-service", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:18:12.998666824Z", "changedAt": "2026-11-07T14:18:12.998666824Z", "fingerprint": "a3dff7b0d914" } ], "models": { "reflection/beam-1.0-501b-a23b": { "openrouterId": "reflection/beam-1.0-501b-a23b", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "text" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 131072, "checkedAt": "2026-11-03T23:49:21.261568406Z" } }, "updatedAt": "2026-11-07T19:23:40.366207063Z" } }, "edges": [ { "by": 34, "category": "security", "leads": "hugging-face-inference-providers", "name": "Security \u0026 auth", "reasons": { "a": "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).", "b": "Model reading. API keys per project, revocable, shown once and disabled when their creator leaves, with no scopes, expiry or rotation API found (20 of 30). Training 10 of 20, partial kept. The API reference says each response's `reflection-data-retention` header reports `contributor` when content may be used to train Reflection's models \"under contributor terms your organization accepted\". The API safety page and commercial terms read on 17 October are struck (reflection.ai now disallows our crawler), so whether training is off by default can't be read. Retention 5 of 15, partial kept. The header can report `zero`, `standard` or `contributor`, and no readable page states periods or whether zero retention is offered. `x-request-id` on every response and the retention header, with usage dashboards behind the login and not read (5 of 15). Security programme 5 of 20 (was 6). The model card names reports@reflection.ai for security vulnerabilities; developers.reflection.ai has no security.txt (404 on 17 October), and the safety report and reflection.ai's security.txt can't be read. No bug bounty, SOC 2 or ISO 27001 found on a readable page. 20 + 10 + 5 + 5 + 5 = 45." }, "scores": { "a": 79, "b": 45 } }, { "by": 30, "category": "maintenance", "leads": "hugging-face-inference-providers", "name": "Maintenance \u0026 community", "reasons": { "a": "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).", "b": "Model reading. The weights were published on 16 October 2026, the date on the Hugging Face model page (the repository was created on 7 October); later commits to 30 October add evaluation results and a guide, which record no model change (30). One model, with a `shutdown_date` field and a lifecycle section in the docs but no notice period for retirements, and no history of releases or retirements yet (4 of 20). No changelog. Support through the platform and developers@reflection.ai for higher limits, and the model card names reports@reflection.ai. The Hub page shows 15 discussions (10 open, 5 closed), replies not sampled (6 of 25). No first-party SDK, the docs rely on the OpenAI SDKs (5 of 15). Reflection's serving guides for vLLM, SGLang, TokenSpeed, Transformers and Dynamo, a Beam Verifier repository, and fine-tuning recipes now published for NeMo AutoModel, Megatron Bridge, Axolotl and TRL (5 of 10, partial kept). 30 + 4 + 6 + 5 + 5 = 50." }, "scores": { "a": 80, "b": 50 } }, { "by": 27, "category": "reliability", "leads": "reflection-beam", "name": "Reliability", "reasons": { "a": "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.", "b": "Hosted lines, for the Reflection API. Status page at status.reflection.ai on incident.io, with API, platform and developer docs components and Atom and RSS feeds (20). In the 90 days to 4 November 2026 its incident pages list two full outages of the API component, a serving cluster down from 22:01 to 23:20 UTC on 14 October and elevated errors from 06:10 to 07:10 UTC on 15 October, each an hour or more, so two majors. Three more are labelled partial outages (16 October 02:28 to 02:38 UTC, 22 October rate-limit errors in two windows, 3 November about 20:10 to 21:38 UTC on one inference provider), read as minor. Two majors give 5. Rate limits are described per organisation in requests and tokens per minute and per day, with concurrency caps and headers, but no figures are published (5 of 15). 429 and 503 responses carry `Retry-After`, daily limits add `x-should-retry: false`, and the errors page says which codes to retry, with exponential backoff and jitter. There are no idempotency keys, and a chat completion is the billed call, so this run's value for retry guidance without idempotency keys gives 12 (was 15). No SLA found (0). The developers docs read on 4 November carry no beta or preview label for the API; the earlier beta reading came from reflection.ai pages now struck (10). 20 + 5 + 5 + 12 + 0 + 10 = 52." }, "scores": { "a": 25, "b": 52 } }, { "by": 22, "category": "schema", "leads": "reflection-beam", "name": "Schema \u0026 documentation", "reasons": { "a": "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).", "b": "Model reading. OpenAPI 3.0.3 document, version 0.1.0, covering all three documented endpoints with typed schemas and error examples. A second 'Reflection client' base URL, https://api.reflection.ai/v1, is named with no endpoints documented (22 of 25). llms.txt, a Markdown copy of every page and a docs MCP endpoint (10). The guides say which reasoning effort suits which task, which OpenAI parameters are fixed, ignored or unsupported and which endpoints don't exist, so a model knows what not to send (17 of 20). `reasoning_effort` is an enum, strict JSON Schema for tools and `json_schema` output with the unsupported keywords and size limits listed, and unknown parameters return `unsupported_parameter` (15). curl, Python and TypeScript examples on every guide, and an error reference with every status, `error.code` and retry advice (15). The model ID carries its version and the models endpoint has a `shutdown_date` field, but no changelog or release notes were found (5 of 15). 22 + 10 + 17 + 15 + 15 + 5 = 84. The OpenAPI file is linked from llms.txt; the guides beyond the overview, models, rate limits, authentication and reference overview pages are per the 17 October check." }, "scores": { "a": 62, "b": 84 } }, { "by": 14, "category": "transparency", "leads": "hugging-face-inference-providers", "name": "Transparency \u0026 trust", "reasons": { "a": "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).", "b": "Weights under Apache-2.0, an OSI licence, per the model card, which says the licence doesn't restrict distillation or training on outputs. The hosted API is a closed service whose commercial terms are on reflection.ai and can no longer be read (25 of 30, kept). Data handling 10 of 30, partial kept. What remains readable is the API reference's retention header (`zero`, `standard`, `contributor`) and the rate-limits page's request for data retention requirements; the terms, privacy policy, API safety page and zero-retention page are struck. Deprecation 4 of 20 (was 6). A `shutdown_date` field and a lifecycle section that says to move off a model before that date, with no notice period or dated notice; the fee-increase notice came from the struck terms. Subprocessors 0 of 20 (was 18). The list read on 17 October is on reflection.ai and struck, and no readable page names subprocessors or data locations. 25 + 10 + 4 + 0 = 39." }, "scores": { "a": 71, "b": 57 } }, { "by": 10, "category": "payments", "leads": "hugging-face-inference-providers", "name": "Payments \u0026 pricing", "reasons": { "a": "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).", "b": "Graded on the Reflection API. No x402, MPP or L402 (0). No per-token, plan or allocation price is published on any readable page; the beta pricing page on reflection.ai is struck (0, was 10). Free tier 10 of 20, partial kept. The rate-limits page describes a daily token allowance and asks those requesting higher limits whether they are \"interested in paid usage\", and the authentication page says some organisations must verify a credit card before keys work. A person signs up in the browser at platform.reflection.ai to get a key (0). 0 + 0 + 10 + 0 = 10." }, "scores": { "a": 20, "b": 10 } } ], "facts": [ { "a": "Model router", "b": "Model API", "name": "Kind" }, { "a": "Hugging Face, Inc.", "b": "Reflection", "name": "Vendor" }, { "a": "https://router.huggingface.co/v1", "b": "https://api.reflection.ai/openai/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Freemium", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "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", "b": "Weights under Apache-2.0. The hosted Reflection API is a closed service under Reflection's commercial terms of service", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-29", "b": "2026-10-16", "name": "Last release" }, { "a": "2022-09-15", "b": "2026-10-05", "name": "Terms last updated" }, { "a": "2023-03-28", "b": "2026-08-28", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "yes", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "yes", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "483k npm/wk, 71.5M PyPI/wk", "b": "none", "name": "Popularity" }, { "a": "none", "b": "2.5/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Hugging Face Inference Providers and Beam 1.0 score within a point of each other on agent readiness, 54 (C) and 53.4 (D). Beam 1.0 leads on reliability, schema \u0026 documentation and agent ergonomics.", "question": "Which is better for AI agents, Hugging Face Inference Providers or Beam 1.0?" }, { "answer": "Both need an API key.", "question": "Do Hugging Face Inference Providers and Beam 1.0 need an API key?" }, { "answer": "Yes. Hugging Face Inference Providers has a hosted endpoint at https://router.huggingface.co/v1 and Beam 1.0 at https://api.reflection.ai/openai/v1.", "question": "Can an agent call Hugging Face Inference Providers and Beam 1.0 without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Security \u0026 auth, 79 against 45", "Payments \u0026 pricing, 20 against 10", "Maintenance \u0026 community, 80 against 50", "Transparency \u0026 trust, 71 against 57" ], "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" }, { "aheadOn": [ "Reliability, 52 against 25", "Schema \u0026 documentation, 84 against 62", "Agent ergonomics, 67 against 58" ], "also": null, "goodFor": "An OpenAI-compatible endpoint for a large open-weight coding and agent model, for builders who want the same model hosted or self-hosted under Apache-2.0.", "slug": "reflection-beam", "watchFor": "No SLA, and per-organisation rate limits and the daily token allowance are not published as numbers" } ], "history": { "hugging-face-inference-providers": null, "reflection-beam": [ { "causes": [ "evidence", "correction" ], "date": "2026-11-04", "delta": 0.1, "from": 53.3, "fromGrade": "D", "to": 53.4, "toGrade": "D" }, { "causes": [ "method" ], "date": "2026-10-30", "delta": -0.1, "from": 53.4, "fromGrade": "D", "to": 53.3, "toGrade": "D" } ] }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "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/muse-spark-open-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-reflection-beam.json", "title": "Novita AI vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-reflection-beam.json", "title": "OpenAI API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/openai-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/openrouter-vs-reflection-beam.json", "title": "OpenRouter vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/openrouter-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-reflection-beam.json", "title": "Prism Inference vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-reflection-beam.json", "title": "Router.com (Ramp Router) vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-routerplus.json", "title": "Beam 1.0 vs RouterPlus", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-sambanova.json", "title": "Beam 1.0 vs SambaCloud", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-siliconflow.json", "title": "Beam 1.0 vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-simplismart.json", "title": "Beam 1.0 vs Simplismart", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-stepfun-api.json", "title": "Beam 1.0 vs StepFun API", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-swe-2-flash.json", "title": "Beam 1.0 vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-tencent-tokenhub.json", "title": "Beam 1.0 vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-together-inference.json", "title": "Beam 1.0 vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-vercel-ai-gateway.json", "title": "Beam 1.0 vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-vertex-ai.json", "title": "Beam 1.0 vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-xai-api.json", "title": "Beam 1.0 vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/reflection-beam-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" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-reflection-beam.json", "title": "Nemotron 3.5 Super VL vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-reflection-beam" } ], "panel": null, "scores": [ { "by": 27, "edge": "reflection-beam", "hugging-face-inference-providers": 25, "key": "reliability", "name": "Reliability", "reflection-beam": 52, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 22, "edge": "reflection-beam", "hugging-face-inference-providers": 62, "key": "schema", "name": "Schema \u0026 documentation", "reflection-beam": 84, "weight": 13 }, { "by": 9, "edge": "reflection-beam", "hugging-face-inference-providers": 58, "key": "ergonomics", "name": "Agent ergonomics", "reflection-beam": 67, "weight": 13 }, { "by": 34, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 79, "key": "security", "name": "Security \u0026 auth", "reflection-beam": 45, "weight": 14 }, { "by": 10, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 20, "key": "payments", "name": "Payments \u0026 pricing", "reflection-beam": 10, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 30, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 80, "key": "maintenance", "name": "Maintenance \u0026 community", "reflection-beam": 50, "weight": 7 }, { "by": 14, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 71, "key": "transparency", "name": "Transparency \u0026 trust", "reflection-beam": 57, "weight": 7 } ], "summary": "Hugging Face Inference Providers and Beam 1.0 score within a point of each other on agent readiness, 54 (C) and 53.4 (D). Beam 1.0 leads on reliability, schema \u0026 documentation and agent ergonomics. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "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.", "reflection-beam": "The Reflection API is OpenAI-compatible, with an OpenAPI document, strict structured outputs and tool calls, and error codes that say when to retry, and the weights are Apache-2.0. No price or rate-limit figure is published on a readable page, reasoning can't be turned off, and the API had two full outages on 14 and 15 October 2026." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam", "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam.min.md" }, "markdown": "Hugging Face Inference Providers and Beam 1.0 score within a point of each other on agent readiness, 54 (C) and 53.4 (D). Beam 1.0 leads on reliability, schema \u0026 documentation and agent ergonomics. Both do llm inference.\n\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- Beam 1.0: grade D, 53.4/100, rank #948 of 1510. Markdown https://www.anchorterminal.com/tools/reflection-beam.md · JSON https://www.anchorterminal.com/api/v1/tools/reflection-beam.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### 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 45\n- Payments \u0026 pricing, 20 against 10\n- Maintenance \u0026 community, 80 against 50\n- Transparency \u0026 trust, 71 against 57\n\nWatch for: No rate limits, 429 behaviour or error responses documented for the router\n\n### Beam 1.0 (D)\n\nGood for: An OpenAI-compatible endpoint for a large open-weight coding and agent model, for builders who want the same model hosted or self-hosted under Apache-2.0.\n\nAhead on:\n- Reliability, 52 against 25\n- Schema \u0026 documentation, 84 against 62\n- Agent ergonomics, 67 against 58\n\nWatch for: No SLA, and per-organisation rate limits and the daily token allowance are not published as numbers\n\n\n## Why the edge\n\n### Security \u0026 auth: Hugging Face Inference Providers +34\n\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- Beam 1.0 (45): Model reading. API keys per project, revocable, shown once and disabled when their creator leaves, with no scopes, expiry or rotation API found (20 of 30). Training 10 of 20, partial kept. The API reference says each response's `reflection-data-retention` header reports `contributor` when content may be used to train Reflection's models \"under contributor terms your organization accepted\". The API safety page and commercial terms read on 17 October are struck (reflection.ai now disallows our crawler), so whether training is off by default can't be read. Retention 5 of 15, partial kept. The header can report `zero`, `standard` or `contributor`, and no readable page states periods or whether zero retention is offered. `x-request-id` on every response and the retention header, with usage dashboards behind the login and not read (5 of 15). Security programme 5 of 20 (was 6). The model card names reports@reflection.ai for security vulnerabilities; developers.reflection.ai has no security.txt (404 on 17 October), and the safety report and reflection.ai's security.txt can't be read. No bug bounty, SOC 2 or ISO 27001 found on a readable page. 20 + 10 + 5 + 5 + 5 = 45.\n\n### Maintenance \u0026 community: Hugging Face Inference Providers +30\n\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- Beam 1.0 (50): Model reading. The weights were published on 16 October 2026, the date on the Hugging Face model page (the repository was created on 7 October); later commits to 30 October add evaluation results and a guide, which record no model change (30). One model, with a `shutdown_date` field and a lifecycle section in the docs but no notice period for retirements, and no history of releases or retirements yet (4 of 20). No changelog. Support through the platform and developers@reflection.ai for higher limits, and the model card names reports@reflection.ai. The Hub page shows 15 discussions (10 open, 5 closed), replies not sampled (6 of 25). No first-party SDK, the docs rely on the OpenAI SDKs (5 of 15). Reflection's serving guides for vLLM, SGLang, TokenSpeed, Transformers and Dynamo, a Beam Verifier repository, and fine-tuning recipes now published for NeMo AutoModel, Megatron Bridge, Axolotl and TRL (5 of 10, partial kept). 30 + 4 + 6 + 5 + 5 = 50.\n\n### Reliability: Beam 1.0 +27\n\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- Beam 1.0 (52): Hosted lines, for the Reflection API. Status page at status.reflection.ai on incident.io, with API, platform and developer docs components and Atom and RSS feeds (20). In the 90 days to 4 November 2026 its incident pages list two full outages of the API component, a serving cluster down from 22:01 to 23:20 UTC on 14 October and elevated errors from 06:10 to 07:10 UTC on 15 October, each an hour or more, so two majors. Three more are labelled partial outages (16 October 02:28 to 02:38 UTC, 22 October rate-limit errors in two windows, 3 November about 20:10 to 21:38 UTC on one inference provider), read as minor. Two majors give 5. Rate limits are described per organisation in requests and tokens per minute and per day, with concurrency caps and headers, but no figures are published (5 of 15). 429 and 503 responses carry `Retry-After`, daily limits add `x-should-retry: false`, and the errors page says which codes to retry, with exponential backoff and jitter. There are no idempotency keys, and a chat completion is the billed call, so this run's value for retry guidance without idempotency keys gives 12 (was 15). No SLA found (0). The developers docs read on 4 November carry no beta or preview label for the API; the earlier beta reading came from reflection.ai pages now struck (10). 20 + 5 + 5 + 12 + 0 + 10 = 52.\n\n### Schema \u0026 documentation: Beam 1.0 +22\n\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- Beam 1.0 (84): Model reading. OpenAPI 3.0.3 document, version 0.1.0, covering all three documented endpoints with typed schemas and error examples. A second 'Reflection client' base URL, https://api.reflection.ai/v1, is named with no endpoints documented (22 of 25). llms.txt, a Markdown copy of every page and a docs MCP endpoint (10). The guides say which reasoning effort suits which task, which OpenAI parameters are fixed, ignored or unsupported and which endpoints don't exist, so a model knows what not to send (17 of 20). `reasoning_effort` is an enum, strict JSON Schema for tools and `json_schema` output with the unsupported keywords and size limits listed, and unknown parameters return `unsupported_parameter` (15). curl, Python and TypeScript examples on every guide, and an error reference with every status, `error.code` and retry advice (15). The model ID carries its version and the models endpoint has a `shutdown_date` field, but no changelog or release notes were found (5 of 15). 22 + 10 + 17 + 15 + 15 + 5 = 84. The OpenAPI file is linked from llms.txt; the guides beyond the overview, models, rate limits, authentication and reference overview pages are per the 17 October check.\n\n### Transparency \u0026 trust: Hugging Face Inference Providers +14\n\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- Beam 1.0 (57): Weights under Apache-2.0, an OSI licence, per the model card, which says the licence doesn't restrict distillation or training on outputs. The hosted API is a closed service whose commercial terms are on reflection.ai and can no longer be read (25 of 30, kept). Data handling 10 of 30, partial kept. What remains readable is the API reference's retention header (`zero`, `standard`, `contributor`) and the rate-limits page's request for data retention requirements; the terms, privacy policy, API safety page and zero-retention page are struck. Deprecation 4 of 20 (was 6). A `shutdown_date` field and a lifecycle section that says to move off a model before that date, with no notice period or dated notice; the fee-increase notice came from the struck terms. Subprocessors 0 of 20 (was 18). The list read on 17 October is on reflection.ai and struck, and no readable page names subprocessors or data locations. 25 + 10 + 4 + 0 = 39.\n\n### Payments \u0026 pricing: Hugging Face Inference Providers +10\n\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- Beam 1.0 (10): Graded on the Reflection API. No x402, MPP or L402 (0). No per-token, plan or allocation price is published on any readable page; the beta pricing page on reflection.ai is struck (0, was 10). Free tier 10 of 20, partial kept. The rate-limits page describes a daily token allowance and asks those requesting higher limits whether they are \"interested in paid usage\", and the authentication page says some organisations must verify a credit card before keys work. A person signs up in the browser at platform.reflection.ai to get a key (0). 0 + 0 + 10 + 0 = 10.\n\n## Score by category\n\n| Category | Weight | Hugging Face Inference Providers | Beam 1.0 | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 25 | 52 | Beam 1.0 +27 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 62 | 84 | Beam 1.0 +22 |\n| Agent ergonomics | 13% (16.2 this run) | 58 | 67 | Beam 1.0 +9 |\n| Security \u0026 auth | 14% (17.5 this run) | 79 | 45 | Hugging Face Inference Providers +34 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 10 | Hugging Face Inference Providers +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 80 | 50 | Hugging Face Inference Providers +30 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 71 | 57 | Hugging Face Inference Providers +14 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **54 · C** | **53.4 · D** | |\n\n## Facts side by side\n\n| Fact | Hugging Face Inference Providers | Beam 1.0 |\n| --- | --- | --- |\n| Kind | Model router | Model API |\n| Vendor | Hugging Face, Inc. | Reflection |\n| Hosted endpoint | `https://router.huggingface.co/v1` | `https://api.reflection.ai/openai/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Freemium |\n| x402 | no | no |\n| Licence | 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 | Weights under Apache-2.0. The hosted Reflection API is a closed service under Reflection's commercial terms of service |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-29 | 2026-10-16 |\n| Terms last updated | 2022-09-15 | 2026-10-05 |\n| Privacy policy last updated | 2023-03-28 | 2026-08-28 |\n| Customer content may train models | not found in the text | yes |\n| Terms restrict automated access | not found in the text | not found in the text |\n| Terms restrict benchmarking | not found in the text | not found in the text |\n| Terms or service can change without notice | yes | not found in the text |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | 483k npm/wk, 71.5M PyPI/wk | none |\n| Agent reviews | none | 2.5/5 (4) |\n\n## How the scores have moved\n\n### Hugging Face Inference Providers\n\nNo score change since it was listed.\n\n### Beam 1.0\n\n- +0.1 on 4 November 2026: new evidence, correction\n- -0.1 on 30 October 2026: checklist\n\n## Verdicts\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**Beam 1.0.** The Reflection API is OpenAI-compatible, with an OpenAPI document, strict structured outputs and tool calls, and error codes that say when to retry, and the weights are Apache-2.0. No price or rate-limit figure is published on a readable page, reasoning can't be turned off, and the API had two full outages on 14 and 15 October 2026.\n\n## Before you call either\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### Beam 1.0\n\n1. Send `reasoning_effort` `low` or `medium` for short tasks. The default is `max`, and `none` or `minimal` return `400 unsupported_value`\n2. Return every assistant message with its `reasoning_content` unchanged. If a turn comes back without it, start a new conversation, since later requests fail with `missing_required_parameter`\n3. Don't rely on `stop` or `seed`. Both are accepted and ignored, so truncate output in your own code\n4. Honour `x-should-retry: false` on a 429. It means a daily limit is spent and `Retry-After` counts to 00:00 UTC\n5. Set `max_completion_tokens` yourself on long prompts. The default budget isn't reduced to fit the prompt and includes reasoning tokens\n\n## Questions\n\n### Which is better for AI agents, Hugging Face Inference Providers or Beam 1.0?\n\nHugging Face Inference Providers and Beam 1.0 score within a point of each other on agent readiness, 54 (C) and 53.4 (D). Beam 1.0 leads on reliability, schema \u0026 documentation and agent ergonomics.\n\n### Do Hugging Face Inference Providers and Beam 1.0 need an API key?\n\nBoth need an API key.\n\n### Can an agent call Hugging Face Inference Providers and Beam 1.0 without installing anything?\n\nYes. Hugging Face Inference Providers has a hosted endpoint at https://router.huggingface.co/v1 and Beam 1.0 at https://api.reflection.ai/openai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"hugging-face-inference-providers\", \"b\": \"reflection-beam\"}`. From a terminal: `anchor compare hugging-face-inference-providers reflection-beam`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-providers.json and https://www.anchorterminal.com/api/v1/tools/reflection-beam.json\n\n## Other comparisons with Hugging Face Inference Providers or Beam 1.0\n\n- [Amazon Bedrock vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers.md)\n- [Amazon Bedrock vs Beam 1.0](https://www.anchorterminal.com/compare/amazon-bedrock-vs-reflection-beam.md)\n- [Claude API vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/anthropic-api-vs-hugging-face-inference-providers.md)\n- [Claude API vs Beam 1.0](https://www.anchorterminal.com/compare/anthropic-api-vs-reflection-beam.md)\n- [Antseed vs Beam 1.0](https://www.anchorterminal.com/compare/antseed-vs-reflection-beam.md)\n- [Azure OpenAI in Foundry Models vs Hugging Face Inference 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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 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Hugging Face Inference Providers vs Beam 1.0", "url": "" } ], "description": "Hugging Face Inference Providers and Beam 1.0 score within a point of each other for llm inference, 54 and 53.4 out of 100. 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