{ "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 scores 54 (C) on agent readiness against Simplismart's 29.5 (F), and leads in 6 of 7 scored categories. Simplismart leads on payments \u0026 pricing.", "b": { "slug": "simplismart", "name": "Simplismart", "vendor": "Verute Technologies Private Limited", "vendorUrl": "https://simplismart.ai", "kind": "http-api", "category": "inference", "summary": "Simplismart is an inference platform for open models. It runs 150+ models on shared pay-per-token endpoints with an OpenAI-compatible API, and handles dedicated GPU deployments, bring-your-own-cloud clusters and fine-tuning jobs.", "url": "https://www.anchorterminal.com/tools/simplismart", "markdownUrl": "https://www.anchorterminal.com/tools/simplismart.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/simplismart.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/simplismart.json", "dns": "simplismart.grade.anchorterminal.com", "license": "Proprietary hosted service. The community Pipecat integration (pipecat-simplismart, by the simpli-smart GitHub account) is BSD-2-Clause; served models keep their own licences.", "transports": [ "http" ], "remoteUrl": "https://api.simplismart.live", "packages": [ { "registry": "pypi", "name": "simplismart-sdk" } ], "auth": "api-key", "authNotes": "Bearer API keys made under Settings, API Keys. Each key has a unique name and an expiry chosen at creation; non-expiring keys need a request to support. Keys return 401 after midnight UTC on the expiry date and can be deleted at once. The Python SDK and CLI use a separate Playground token. Organisation roles are Admin, Member and Billing User, and workspaces scope models and deployments.", "pricing": "usage", "pricingNotes": "Shared endpoints are priced per 1M tokens, per image or per audio minute, such as Llama 3.1 8B at $0.13 and DeepSeek-V3 at $0.90 per 1M tokens. Dedicated GPUs run from $1.20 (T4) to $5.20 (H200) per GPU-hour. Prepaid credits at $1 each; new organisations may receive $5 of free credits.", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs (llms.txt index, billing, API keys and API reference pages) or on the pricing page, checked 28 October 2026. Credits are bought by card, UPI or netbanking, or billed postpaid.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-28" }, "docsUrl": "https://docs.simplismart.ai", "llmsTxt": "https://docs.simplismart.ai/llms.txt", "openapi": "https://docs.simplismart.ai/openapi-specs/playground/llama-8b.yaml", "capabilities": [ "inference.llm", "inference.open-weights", "speech.stt", "image.generate", "compute.endpoints", "finetune.sft", "finetune.lora", "finetune.preference", "finetune.rl" ], "tags": [ "hosted", "model", "open-weights", "usage-based", "openai-compatible", "openapi", "llms-txt", "python", "dedicated-endpoints", "byoc", "fine-tuning" ], "lastRelease": "2026-10-19", "graded": true, "anchor": { "graded": true, "score": 29.5, "grade": "F", "agentReady": false, "rank": 1424, "ranked": true, "rankOf": 1510, "categoryRank": 42, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 17, "maintenance": 42, "payments": 25, "reliability": 15, "schema": 51, "security": 35, "transparency": 29 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-28" }, "negative": 0, "verdict": "Simplismart exposes open models through an OpenAI-compatible endpoint with public per-token prices and expiring, revocable keys. Its public docs give no request rate limits, status page, retry guidance, tool-calling or structured-output reference, and its terms and privacy policy cover the website, not API data.", "bestFor": "Teams that want open models on a pay-per-token OpenAI-compatible endpoint and a path to dedicated GPUs, their own cloud or fine-tuning with one vendor, and can work without published rate limits or data-handling terms.", "strengths": [ "Public per-unit prices without a login, such as Llama 3.1 8B at $0.13 per 1M tokens and Whisper v3 Turbo at $0.0018 per audio minute", "API keys are named, carry an expiry date chosen at creation, return 401 after expiry and can be deleted at once", "Markdown docs and an llms.txt index, with OpenAPI 3.1 files for seven LLMs, Whisper and Flux", "Shared endpoints, dedicated GPU deployments and bring-your-own-cloud clusters sit on one account, with workspaces and organisation roles" ], "weaknesses": [ "No request or token rate limits, 429 handling or retry guidance found in the docs; only GPU quotas, given as 1 and as 8 H100s on two pages", "No status page, incident history or SLA document found; the 99.99% uptime figure is a homepage claim", "Tool calling, structured output, prompt caching and context lengths are not documented for the shared endpoints", "The terms (13 January 2023) and privacy policy cover the website and say nothing about prompt retention or training on API data", "The pricing page lists older models (Llama 3.1, DeepSeek-R1) and omits Gemma 4 31B, the model the quickstart uses" ], "agentNotes": [ "Point an OpenAI-compatible client at https://api.simplismart.live with SIMPLISMART_API_KEY as a Bearer token, and take model ids from the marketplace or the per-model API pages.", "Set a key expiry and rotate before midnight UTC on the expiry date, because an expired key returns 401.", "Cap retries yourself with exponential backoff, because no rate limits, 429 format or retry guidance are published.", "Check that a model supports tools or JSON output with a test call before relying on it, because neither is documented.", "Confirm the per-token price of the exact model in the console before running large jobs, because the public price list is incomplete." ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "F", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 29.5 } ], "editorialScores": { "ergonomics": 17, "maintenance": 42, "payments": 25, "reliability": 15, "schema": 51, "security": 35, "transparency": 14 }, "provenanceScore": 44, "checked": { "categories": { "ergonomics": "2026-10-28", "maintenance": "2026-10-28", "payments": "2026-10-28", "reliability": "2026-10-28", "schema": "2026-10-28", "security": "2026-10-28", "transparency": "2026-10-28" }, "last": "2026-10-28", "lastMoved": "2026-10-30", "oldest": "2026-10-28", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl 'https://api.simplismart.live/chat/completions' -H 'Content-Type: application/json' -H \"Authorization: Bearer $SIMPLISMART_API_KEY\" -d '{\"model\": \"meta-llama/Meta-Llama-3.1-8B-Instruct\", \"messages\": [{\"role\": \"user\", \"content\": \"Say hello.\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/simplismart" }, "area": "models", "unitPrices": [ { "item": "Llama 3.1 8B (shared)", "unit": "1m-tokens", "usd": 0.13, "note": "Single per-1M-token rate on the pricing page, checked 28 October 2026; input and output are not priced separately" }, { "item": "Llama 3.3 70B (shared)", "unit": "1m-tokens", "usd": 0.74, "note": "Pricing page, checked 28 October 2026" }, { "item": "DeepSeek-V3 (shared)", "unit": "1m-tokens", "usd": 0.9, "note": "Pricing page, checked 28 October 2026" }, { "item": "Whisper v3 Turbo (shared)", "unit": "audio-minute", "usd": 0.0018, "note": "Pricing page, checked 28 October 2026" }, { "item": "Flux Dev (shared, 1024x1024)", "unit": "image", "usd": 0.03, "note": "Pricing page, checked 28 October 2026" }, { "item": "NVIDIA H100, dedicated", "unit": "gpu-hour", "usd": 5, "note": "Pricing page table order, checked 28 October 2026; a Simplismart article gives $4.00 per hour" } ], "provenance": { "legalEntity": "Verute Technologies Private Limited", "domain": "simplismart.ai", "domainRegistered": "", "endpointOnVendorDomain": false, "terms": "https://simplismart.ai/terms-of-service", "privacy": "https://simplismart.ai/privacy-policy", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-28", "notes": [ "The terms (last updated 13 January 2023) and privacy policy (effective 13 January 2023) name Verute Technologies Private Limited, Indian law and an address on Residency Road, Bengaluru. Both define the Service as the simplismart.ai website.", "The inference API answers on api.simplismart.live, a separate domain named in the docs. Domain registration was not checked.", "No status page found. The docs and site link none, and status.simplismart.ai could not be reached from our network.", "No changelog found in the docs sitemap or llms.txt. Model additions appear as blog posts.", "simplismart.ai/.well-known/security.txt answered 404." ], "score": 44 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/simplismart.json", "live": { "slug": "simplismart", "probe": { "target": "https://api.simplismart.live", "method": "get", "lastAt": "2026-11-07T19:22:33.217760995Z", "lastOk": true, "lastStatus": 405, "lastMs": 63, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 60, "p95ms24h": 169, "samples24h": 238, "samples30d": 2573, "days": [ { "date": "2026-10-28", "probes": 208, "ok": 208 }, { "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 } ] }, "versions": [ { "registry": "pypi", "name": "simplismart-sdk", "version": "0.1.15", "released": "2026-11-02", "seenAt": "2026-11-07T00:06:08.735466052Z" } ], "pypiWeekly": 186, "securityTxt": { "url": "https://simplismart.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:01:22.590979779Z" }, "llmsTxt": { "url": "https://docs.simplismart.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:33:56.047475338Z" }, "domain": { "domain": "simplismart.ai", "registered": "2022-11-18", "source": "https://rdap.identitydigital.services/rdap/domain/simplismart.ai", "checkedAt": "2026-11-01T14:28:09.738527702Z" }, "pages": [ { "url": "https://simplismart.ai/privacy-policy", "kind": "privacy", "status": 304, "checkedAt": "2026-11-07T14:19:55.485469388Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "bd2d6d5ffe37" }, { "url": "https://simplismart.ai/terms-of-service", "kind": "terms", "status": 304, "checkedAt": "2026-11-07T14:19:59.722810598Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "94fe8807daf7" } ], "updatedAt": "2026-11-07T19:22:33.217760995Z" } }, "edges": [ { "by": 44, "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. Named Bearer keys with an expiry chosen at creation, a 401 after expiry and immediate deletion. No scopes or per-key limits found, keys belong to the organisation, and the SDK uses a separate Playground token (20 of 30). No statement on training on API data in the terms, the privacy policy, the AI policy or the docs (0 of 20). No retention or zero-retention statement for prompts and outputs. The privacy policy covers the website only (0 of 15). The Usage page shows request counts and a per-request timeline per model, and an LLM metrics call returns token counts and timings per request id. A Simplismart article claims exportable audit trails, not documented (8 of 15). The homepage shows GDPR, ISO 27001 v2022 and AICPA SOC 2 badges, and a Simplismart article says it holds a SOC 2 Type 2 report, available on request. No trust centre was reachable, security.txt answered 404, and no disclosure policy or bug bounty was found (7 of 20). 20+0+0+8+7 = 35." }, "scores": { "a": 79, "b": 35 } }, { "by": 42, "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": "Closed service. The terms, last updated 13 January 2023, name Verute Technologies Private Limited and Indian law but define the Service as the website, grant Simplismart a licence to use and redistribute posted Content, bar robots and automatic access, and rule out refunds. No API or platform terms were found (8 of 30). The privacy policy, effective 13 January 2023, is a website policy that says personal data is processed in India. It says nothing about prompts, outputs, logs or training, and no DPA, retention period or subprocessor list was found. A Simplismart article claims GDPR and HIPAA support (3 of 30). No deprecation policy or dated removals (0 of 20). Data goes to India per the privacy policy, and an article says workloads are kept in approved regions by scheduling policy. No subprocessor or hosting-provider list (3 of 20). 8+3+0+3 = 14." }, "scores": { "a": 71, "b": 29 } }, { "by": 41, "category": "ergonomics", "leads": "hugging-face-inference-providers", "name": "Agent ergonomics", "reasons": { "a": "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).", "b": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). The LiveKit guide calls the LLM API fully OpenAI-compatible, but no page documents tools or tool_choice, and the OpenAPI files allow only system, user and assistant roles (3 of 20). No structured-output or JSON mode documented (0 of 15). No prompt caching documented for shared endpoints (0 of 15). Context lengths are not stated per model; output is capped at 4,096 tokens in the API files (3 of 15). No batch API for shared endpoints (0 of 10). Inference goes through the OpenAI client; the simplismart-sdk Python package and CLI manage repositories and deployments, not inference, and a community Pipecat package exists (5 of 10). Expired keys return a documented 401, and the SDK exposes status_code, message and payload, but no error codes or bodies are listed for the inference API (6 of 15). 3+0+0+3+0+5+6 = 17." }, "scores": { "a": 58, "b": 17 } }, { "by": 38, "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 for a closed service. Muse Spark Open was added in beta on 19 October 2026, and the docs sitemap shows pages changed on 7 October (30). No deprecation policy or notice period found (0 of 12). One dated model addition in the 90 days to 28 October and no recorded removals; the pricing page still lists Llama 3.1 405B and DeepSeek-R1, which the API reference doesn't cover, so the live model set is unclear (2 of 8). No public changelog or community channel. Support is support@simplismart.ai and a contact form, not tested (4 of 15). SDK issue replies not read, because github.com gave no readable robots.txt (0 of 10). simplismart-sdk for Python, documented with a CLI, and the OpenAI client for inference. No TypeScript SDK, and the PyPI page answered with a browser challenge, so the version and date are unchecked (6 of 15). CI not checked (0 of 10). 30+0+2+4+0+6+0 = 42." }, "scores": { "a": 80, "b": 42 } }, { "by": 11, "category": "schema", "leads": "hugging-face-inference-providers", "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 3.1 files for seven LLMs and 3.0 or 3.1 files for Whisper, Flux, an LLM metrics call and training jobs. They cover a handful of the 150+ models, omit tools and response_format, show a streaming `delta` as the non-streaming response, and several name hosts on s9t.link instead of api.simplismart.live. The Llama 4 Maverick file gives `llama3_1` as its only model id, and /api-reference/openapi.json is the Flux spec (12 of 25). llms.txt and a Markdown copy of each docs page (10). The docs say when to use shared or dedicated endpoints; model pages carry one-line descriptions (10 of 20). Roles are enums, temperature is bounded 0 to 2, max_tokens 1 to 4096, and messages and model are required (10 of 15). curl and OpenAI-client Python examples. Errors are bare 400, 401 and 500 descriptions, plus an SDK example of a 404 payload (7 of 15). No changelog. Every spec reads version 1.0.0 (2 of 15). 12+10+10+10+7+2 = 51." }, "scores": { "a": 62, "b": 51 } }, { "by": 10, "category": "reliability", "leads": "hugging-face-inference-providers", "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 reading. No status page found. The docs and site link none, a search found none, and status.simplismart.ai could not be reached from our network (0). No readable incident history (5). No request or token rate limits are published for shared endpoints. The docs give GPU quotas for training, compilation and private deployments only, 1 H100 and 1 L40 on the Quotas page and 8 of each on the Organisation page (0). No 429 response, Retry-After header or retry guidance found; the OpenAPI files list only 400, 401 and 500 (0). No SLA document found. The homepage claims 99.99% uptime and a Simplismart post calls its autoscaling SLA-backed, but no terms state a commitment, and the terms provide the service as is (0). Shared endpoints carry no beta label, while Muse Spark Open is in beta (10). 0+5+0+0+0+10 = 15." }, "scores": { "a": 25, "b": 15 } } ], "facts": [ { "a": "Model router", "b": "HTTP API", "name": "Kind" }, { "a": "Hugging Face, Inc.", "b": "Verute Technologies Private Limited", "name": "Vendor" }, { "a": "https://router.huggingface.co/v1", "b": "https://api.simplismart.live", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "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": "Proprietary hosted service. The community Pipecat integration (pipecat-simplismart, by the simpli-smart GitHub account) is BSD-2-Clause; served models keep their own licences.", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-29", "b": "2026-10-19", "name": "Last release" }, { "a": "2022-09-15", "b": "2023-01-13", "name": "Terms last updated" }, { "a": "2023-03-28", "b": "2023-01-13", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "yes", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "yes", "b": "yes", "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" } ], "faq": [ { "answer": "Hugging Face Inference Providers scores 54 (C) on agent readiness against Simplismart's 29.5 (F), and leads in 6 of 7 scored categories. Simplismart leads on payments \u0026 pricing.", "question": "Which is better for AI agents, Hugging Face Inference Providers or Simplismart?" }, { "answer": "Both need an API key.", "question": "Do Hugging Face Inference Providers and Simplismart need an API key?" }, { "answer": "Yes. Hugging Face Inference Providers has a hosted endpoint at https://router.huggingface.co/v1 and Simplismart at https://api.simplismart.live.", "question": "Can an agent call Hugging Face Inference Providers and Simplismart without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 25 against 15", "Schema \u0026 documentation, 62 against 51", "Agent ergonomics, 58 against 17", "Security \u0026 auth, 79 against 35", "Maintenance \u0026 community, 80 against 42", "Transparency \u0026 trust, 71 against 29" ], "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": [ "Payments \u0026 pricing, 25 against 20" ], "also": null, "goodFor": "Teams that want open models on a pay-per-token OpenAI-compatible endpoint and a path to dedicated GPUs, their own cloud or fine-tuning with one vendor, and can work without published rate limits or data-handling terms.", "slug": "simplismart", "watchFor": "No request or token rate limits, 429 handling or retry guidance found in the docs; only GPU quotas, given as 1 and as 8 H100s on two pages" } ], "history": { "hugging-face-inference-providers": null, "simplismart": [ { "causes": [ "method" ], "date": "2026-10-30", "delta": -0.2, "from": 29.7, "fromGrade": "F", "to": 29.5, "toGrade": "F" } ] }, "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": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-simplismart.json", "title": "Amazon Bedrock vs 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TokenHub", "url": "https://www.anchorterminal.com/compare/simplismart-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-together-inference.json", "title": "Simplismart vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/simplismart-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-vercel-ai-gateway.json", "title": "Simplismart vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/simplismart-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-vertex-ai.json", "title": "Simplismart vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/simplismart-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-xai-api.json", "title": "Simplismart vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/simplismart-vs-xai-api" }, { "json": 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"https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-simplismart" } ], "panel": null, "scores": [ { "by": 10, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 25, "key": "reliability", "name": "Reliability", "simplismart": 15, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 11, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 62, "key": "schema", "name": "Schema \u0026 documentation", "simplismart": 51, "weight": 13 }, { "by": 41, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 58, "key": "ergonomics", "name": "Agent ergonomics", "simplismart": 17, "weight": 13 }, { "by": 44, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 79, "key": "security", "name": "Security \u0026 auth", "simplismart": 35, "weight": 14 }, { "by": 5, "edge": "simplismart", "hugging-face-inference-providers": 20, "key": "payments", "name": "Payments \u0026 pricing", "simplismart": 25, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 38, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 80, "key": "maintenance", "name": "Maintenance \u0026 community", "simplismart": 42, "weight": 7 }, { "by": 42, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 71, "key": "transparency", "name": "Transparency \u0026 trust", "simplismart": 29, "weight": 7 } ], "summary": "Hugging Face Inference Providers scores 54 (C) on agent readiness against Simplismart's 29.5 (F), and leads in 6 of 7 scored categories. Simplismart leads on payments \u0026 pricing. 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.", "simplismart": "Simplismart exposes open models through an OpenAI-compatible endpoint with public per-token prices and expiring, revocable keys. Its public docs give no request rate limits, status page, retry guidance, tool-calling or structured-output reference, and its terms and privacy policy cover the website, not API data." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-simplismart", "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-simplismart.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-simplismart.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-simplismart.min.md" }, "markdown": "Hugging Face Inference Providers scores 54 (C) on agent readiness against Simplismart's 29.5 (F), and leads in 6 of 7 scored categories. Simplismart leads on payments \u0026 pricing. 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- Simplismart: grade F, 29.5/100, rank #1424 of 1510. Markdown https://www.anchorterminal.com/tools/simplismart.md · JSON https://www.anchorterminal.com/api/v1/tools/simplismart.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- Reliability, 25 against 15\n- Schema \u0026 documentation, 62 against 51\n- Agent ergonomics, 58 against 17\n- Security \u0026 auth, 79 against 35\n- Maintenance \u0026 community, 80 against 42\n- Transparency \u0026 trust, 71 against 29\n\nWatch for: No rate limits, 429 behaviour or error responses documented for the router\n\n### Simplismart (F)\n\nGood for: Teams that want open models on a pay-per-token OpenAI-compatible endpoint and a path to dedicated GPUs, their own cloud or fine-tuning with one vendor, and can work without published rate limits or data-handling terms.\n\nAhead on:\n- Payments \u0026 pricing, 25 against 20\n\nWatch for: No request or token rate limits, 429 handling or retry guidance found in the docs; only GPU quotas, given as 1 and as 8 H100s on two pages\n\n\n## Why the edge\n\n### Security \u0026 auth: Hugging Face Inference Providers +44\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- Simplismart (35): Model reading. Named Bearer keys with an expiry chosen at creation, a 401 after expiry and immediate deletion. No scopes or per-key limits found, keys belong to the organisation, and the SDK uses a separate Playground token (20 of 30). No statement on training on API data in the terms, the privacy policy, the AI policy or the docs (0 of 20). No retention or zero-retention statement for prompts and outputs. The privacy policy covers the website only (0 of 15). The Usage page shows request counts and a per-request timeline per model, and an LLM metrics call returns token counts and timings per request id. A Simplismart article claims exportable audit trails, not documented (8 of 15). The homepage shows GDPR, ISO 27001 v2022 and AICPA SOC 2 badges, and a Simplismart article says it holds a SOC 2 Type 2 report, available on request. No trust centre was reachable, security.txt answered 404, and no disclosure policy or bug bounty was found (7 of 20). 20+0+0+8+7 = 35.\n\n### Transparency \u0026 trust: Hugging Face Inference Providers +42\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- Simplismart (29): Closed service. The terms, last updated 13 January 2023, name Verute Technologies Private Limited and Indian law but define the Service as the website, grant Simplismart a licence to use and redistribute posted Content, bar robots and automatic access, and rule out refunds. No API or platform terms were found (8 of 30). The privacy policy, effective 13 January 2023, is a website policy that says personal data is processed in India. It says nothing about prompts, outputs, logs or training, and no DPA, retention period or subprocessor list was found. A Simplismart article claims GDPR and HIPAA support (3 of 30). No deprecation policy or dated removals (0 of 20). Data goes to India per the privacy policy, and an article says workloads are kept in approved regions by scheduling policy. No subprocessor or hosting-provider list (3 of 20). 8+3+0+3 = 14.\n\n### Agent ergonomics: Hugging Face Inference Providers +41\n\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- Simplismart (17): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). The LiveKit guide calls the LLM API fully OpenAI-compatible, but no page documents tools or tool_choice, and the OpenAPI files allow only system, user and assistant roles (3 of 20). No structured-output or JSON mode documented (0 of 15). No prompt caching documented for shared endpoints (0 of 15). Context lengths are not stated per model; output is capped at 4,096 tokens in the API files (3 of 15). No batch API for shared endpoints (0 of 10). Inference goes through the OpenAI client; the simplismart-sdk Python package and CLI manage repositories and deployments, not inference, and a community Pipecat package exists (5 of 10). Expired keys return a documented 401, and the SDK exposes status_code, message and payload, but no error codes or bodies are listed for the inference API (6 of 15). 3+0+0+3+0+5+6 = 17.\n\n### Maintenance \u0026 community: Hugging Face Inference Providers +38\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- Simplismart (42): Model reading for a closed service. Muse Spark Open was added in beta on 19 October 2026, and the docs sitemap shows pages changed on 7 October (30). No deprecation policy or notice period found (0 of 12). One dated model addition in the 90 days to 28 October and no recorded removals; the pricing page still lists Llama 3.1 405B and DeepSeek-R1, which the API reference doesn't cover, so the live model set is unclear (2 of 8). No public changelog or community channel. Support is support@simplismart.ai and a contact form, not tested (4 of 15). SDK issue replies not read, because github.com gave no readable robots.txt (0 of 10). simplismart-sdk for Python, documented with a CLI, and the OpenAI client for inference. No TypeScript SDK, and the PyPI page answered with a browser challenge, so the version and date are unchecked (6 of 15). CI not checked (0 of 10). 30+0+2+4+0+6+0 = 42.\n\n### Schema \u0026 documentation: Hugging Face Inference Providers +11\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- Simplismart (51): Model reading. OpenAPI 3.1 files for seven LLMs and 3.0 or 3.1 files for Whisper, Flux, an LLM metrics call and training jobs. They cover a handful of the 150+ models, omit tools and response_format, show a streaming `delta` as the non-streaming response, and several name hosts on s9t.link instead of api.simplismart.live. The Llama 4 Maverick file gives `llama3_1` as its only model id, and /api-reference/openapi.json is the Flux spec (12 of 25). llms.txt and a Markdown copy of each docs page (10). The docs say when to use shared or dedicated endpoints; model pages carry one-line descriptions (10 of 20). Roles are enums, temperature is bounded 0 to 2, max_tokens 1 to 4096, and messages and model are required (10 of 15). curl and OpenAI-client Python examples. Errors are bare 400, 401 and 500 descriptions, plus an SDK example of a 404 payload (7 of 15). No changelog. Every spec reads version 1.0.0 (2 of 15). 12+10+10+10+7+2 = 51.\n\n### Reliability: Hugging Face Inference Providers +10\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- Simplismart (15): Hosted reading. No status page found. The docs and site link none, a search found none, and status.simplismart.ai could not be reached from our network (0). No readable incident history (5). No request or token rate limits are published for shared endpoints. The docs give GPU quotas for training, compilation and private deployments only, 1 H100 and 1 L40 on the Quotas page and 8 of each on the Organisation page (0). No 429 response, Retry-After header or retry guidance found; the OpenAPI files list only 400, 401 and 500 (0). No SLA document found. The homepage claims 99.99% uptime and a Simplismart post calls its autoscaling SLA-backed, but no terms state a commitment, and the terms provide the service as is (0). Shared endpoints carry no beta label, while Muse Spark Open is in beta (10). 0+5+0+0+0+10 = 15.\n\n## Score by category\n\n| Category | Weight | Hugging Face Inference Providers | Simplismart | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 25 | 15 | Hugging Face Inference Providers +10 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 62 | 51 | Hugging Face Inference Providers +11 |\n| Agent ergonomics | 13% (16.2 this run) | 58 | 17 | Hugging Face Inference Providers +41 |\n| Security \u0026 auth | 14% (17.5 this run) | 79 | 35 | Hugging Face Inference Providers +44 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 25 | Simplismart +5 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 80 | 42 | Hugging Face Inference Providers +38 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 71 | 29 | Hugging Face Inference Providers +42 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **54 · C** | **29.5 · F** | |\n\n## Facts side by side\n\n| Fact | Hugging Face Inference Providers | Simplismart |\n| --- | --- | --- |\n| Kind | Model router | HTTP API |\n| Vendor | Hugging Face, Inc. | Verute Technologies Private Limited |\n| Hosted endpoint | `https://router.huggingface.co/v1` | `https://api.simplismart.live` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\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 | Proprietary hosted service. The community Pipecat integration (pipecat-simplismart, by the simpli-smart GitHub account) is BSD-2-Clause; served models keep their own licences. |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-29 | 2026-10-19 |\n| Terms last updated | 2022-09-15 | 2023-01-13 |\n| Privacy policy last updated | 2023-03-28 | 2023-01-13 |\n| Customer content may train models | not found in the text | not found in the text |\n| Terms restrict automated access | not found in the text | yes |\n| Terms restrict benchmarking | not found in the text | not found in the text |\n| Terms or service can change without notice | yes | yes |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | 483k npm/wk, 71.5M PyPI/wk | none |\n\n## How the scores have moved\n\n### Hugging Face Inference Providers\n\nNo score change since it was listed.\n\n### Simplismart\n\n- -0.2 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**Simplismart.** Simplismart exposes open models through an OpenAI-compatible endpoint with public per-token prices and expiring, revocable keys. Its public docs give no request rate limits, status page, retry guidance, tool-calling or structured-output reference, and its terms and privacy policy cover the website, not API data.\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### Simplismart\n\n1. Point an OpenAI-compatible client at https://api.simplismart.live with SIMPLISMART_API_KEY as a Bearer token, and take model ids from the marketplace or the per-model API pages.\n2. Set a key expiry and rotate before midnight UTC on the expiry date, because an expired key returns 401.\n3. Cap retries yourself with exponential backoff, because no rate limits, 429 format or retry guidance are published.\n4. Check that a model supports tools or JSON output with a test call before relying on it, because neither is documented.\n5. Confirm the per-token price of the exact model in the console before running large jobs, because the public price list is incomplete.\n\n## Questions\n\n### Which is better for AI agents, Hugging Face Inference Providers or Simplismart?\n\nHugging Face Inference Providers scores 54 (C) on agent readiness against Simplismart's 29.5 (F), and leads in 6 of 7 scored categories. Simplismart leads on payments \u0026 pricing.\n\n### Do Hugging Face Inference Providers and Simplismart need an API key?\n\nBoth need an API key.\n\n### Can an agent call Hugging Face Inference Providers and Simplismart without installing anything?\n\nYes. Hugging Face Inference Providers has a hosted endpoint at https://router.huggingface.co/v1 and Simplismart at https://api.simplismart.live.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-simplismart.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-simplismart.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"hugging-face-inference-providers\", \"b\": \"simplismart\"}`. From a terminal: `anchor compare hugging-face-inference-providers simplismart`\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/simplismart.json\n\n## Other comparisons with Hugging Face Inference Providers or Simplismart\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 Simplismart](https://www.anchorterminal.com/compare/amazon-bedrock-vs-simplismart.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 Simplismart](https://www.anchorterminal.com/compare/anthropic-api-vs-simplismart.md)\n- [Antseed vs Simplismart](https://www.anchorterminal.com/compare/antseed-vs-simplismart.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 Simplismart", "url": "" } ], "description": "Hugging Face Inference Providers scores 54 (C) to Simplismart's 29.5 (F) for llm inference. 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