{ "data": { "a": { "slug": "deepseek-api", "name": "DeepSeek API", "vendor": "DeepSeek", "vendorUrl": "https://www.deepseek.com", "kind": "model", "category": "inference", "summary": "Hangzhou lab's API for the V4 model family, in the OpenAI Chat Completions, OpenAI Responses and Anthropic request formats, with off-peak pricing.", "url": "https://www.anchorterminal.com/tools/deepseek-api", "markdownUrl": "https://www.anchorterminal.com/tools/deepseek-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/deepseek-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/deepseek-api.json", "dns": "deepseek-api.grade.anchorterminal.com", "transports": [ "http" ], "remoteUrl": "https://api.deepseek.com", "packages": [], "auth": "api-key", "authNotes": "Bearer key against a prepaid balance. An Anthropic-format base URL is at `/anthropic`.", "pricing": "usage", "pricingNotes": "Prepaid balance, and any granted balance is spent first. Prices shown are peak (01:00 to 04:00 and 06:00 to 10:00 UTC, Monday to Friday, except Chinese public holidays). Off-peak is half price. Disk cache on by default, with cache hits at $0.044 per 1M input tokens on V4 Pro and $0.006 on V4.1 Flash at peak (https://api-docs.deepseek.com/quick_start/pricing).", "priceSummary": "from $0.30 / 1M in", "where": "hosted", "x402": { "level": "no", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-09-26" }, "docsUrl": "https://api-docs.deepseek.com", "rateLimitsUrl": "https://api-docs.deepseek.com/quick_start/rate_limit", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "hosted", "model", "open-weights", "prepaid" ], "lastRelease": "2026-10-17", "graded": true, "anchor": { "graded": true, "score": 46.7, "grade": "D", "agentReady": false, "rank": 1167, "ranked": true, "rankOf": 1510, "categoryRank": 37, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 70, "maintenance": 46, "payments": 20, "reliability": 60, "schema": 49, "security": 35, "transparency": 65 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-05" }, "negative": -3, "negativeNotes": [ "On 2026-09-10 DeepSeek retired V4 Flash and routed `deepseek-v4-flash` and `deepseek-v4-flash-vision-exp` to V4.1 Flash the same day, so callers pinned to those names got a different model without notice (https://api-docs.deepseek.com/updates)" ], "verdict": "Accepts the OpenAI Chat Completions, OpenAI Responses and Anthropic request formats at per-token prices that halve off-peak. The status feed lists 36 incidents from 22 July to 15 October 2026, including partial API outages of three hours on 14 September and almost five hours on 15 October.", "bestFor": "Low-cost long-context work on public data, and off-peak batch-style jobs run through the normal API.", "strengths": [ "Accepts the OpenAI Chat Completions, OpenAI Responses and Anthropic request formats", "1M-token context and up to 384K output", "Off-peak prices are half the peak price, and the disk cache is on by default", "Weights of DeepSeek-V4.1-Flash-1017, the model behind `deepseek-flash`, are on Hugging Face under the MIT licence, per its model card", "`deepseek-chat` and `deepseek-reasoner` got three months' notice before their 24 July 2026 shutdown" ], "weaknesses": [ "36 status incidents from 22 July to 15 October 2026, with partial API outages of three hours on 14 September and 4 hours 52 minutes on 15 October", "Personal data trains models unless you email to opt out, and data is stored in the PRC with no retention period stated", "Model names move without a pinnable version. V4 Flash names were rerouted on 10 September 2026, and `deepseek-flash` became the 1017 model on 17 October", "A V4 Pro shutdown for 14 September 2026 was announced on 13 August and withdrawn on 10 September", "No OpenAPI document, no llms.txt, no security.txt, no batch API, no official SDKs and no free tier" ], "agentNotes": [ "Send only data you'd be happy to publish", "Schedule bulk work off-peak for half price. Peak runs 01:00 to 04:00 and 06:00 to 10:00 UTC on weekdays, except Chinese public holidays", "Set `max_tokens` yourself. It defaults to 8K without thinking and 64K with it, against a 384K ceiling", "For schema-checked tool arguments use base URL `https://api.deepseek.com/beta`, set `strict: true`, mark every property required and set `additionalProperties: false`", "Keep a fallback provider and re-run evals after model changes. 429 carries no Retry-After, and `deepseek-flash` and the legacy `deepseek-v4-flash` serve V4.1-Flash-1017 since 17 October 2026" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 2, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 46.7 } ], "editorialScores": { "ergonomics": 70, "maintenance": 46, "payments": 20, "reliability": 60, "schema": 49, "security": 35, "transparency": 45 }, "provenanceScore": 85, "checked": { "categories": { "ergonomics": "2026-11-05", "maintenance": "2026-11-05", "payments": "2026-11-05", "reliability": "2026-11-05", "schema": "2026-11-05", "security": "2026-11-05", "transparency": "2026-11-05" }, "last": "2026-11-05", "lastMoved": "2026-11-05", "oldest": "2026-11-05", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl https://api.deepseek.com/chat/completions \\\n -H \"Authorization: Bearer $DEEPSEEK_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"model\":\"deepseek-v4-pro\",\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/deepseek-api" }, "sameCompany": [ "deepseek-search-api", "deepseek-v3-2", "deepseek-v4-flash-0731" ], "sameModel": [ "deepseek-v4-1-flash" ], "area": "models", "provenance": { "legalEntity": "Hangzhou DeepSeek Artificial Intelligence Co., Ltd.", "domain": "deepseek.com", "domainRegistered": "2000-08-13", "domainNote": "deepseek.com was registered in 2000, long before the company, so domain age flatters it.", "endpointOnVendorDomain": true, "terms": "https://cdn.deepseek.com/policies/en-US/deepseek-open-platform-terms-of-service.html", "privacy": "https://cdn.deepseek.com/policies/en-US/deepseek-privacy-policy.html", "statusPage": "https://status.deepseek.com", "changelog": "https://api-docs.deepseek.com/updates", "securityTxt": "none", "checked": "2026-09-26", "score": 85 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/deepseek-api.json", "live": { "slug": "deepseek-api", "probe": { "target": "https://api.deepseek.com", "method": "get", "lastAt": "2026-11-07T19:22:03.302224921Z", "lastOk": true, "lastStatus": 401, "lastMs": 361, "lastNote": "asks for credentials", "authRequired": true, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 288, "p95ms24h": 369, "samples24h": 238, "samples30d": 7920, "days": [ { "date": "2026-10-07", "probes": 272, "ok": 272 }, { "date": "2026-10-08", "probes": 268, "ok": 268 }, { "date": "2026-10-09", "probes": 250, "ok": 250 }, { "date": "2026-10-10", "probes": 247, "ok": 247 }, { "date": "2026-10-11", "probes": 247, "ok": 247 }, { "date": "2026-10-12", "probes": 247, "ok": 247 }, { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 249 }, { "date": "2026-10-15", "probes": 253, "ok": 253 }, { "date": "2026-10-16", "probes": 252, "ok": 252 }, { "date": "2026-10-17", "probes": 253, "ok": 253 }, { "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": 251, "ok": 251 }, { "date": "2026-10-29", "probes": 248, "ok": 248 }, { "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.deepseek.com", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-07T04:47:37.236618145Z" }, "securityTxt": { "url": "https://deepseek.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T15:59:54.973930725Z" }, "domain": { "domain": "deepseek.com", "registered": "2000-08-13", "source": "https://rdap.verisign.com/com/v1/domain/deepseek.com", "checkedAt": "2026-11-01T14:07:48.239871757Z" }, "pages": [ { "url": "https://api-docs.deepseek.com/news/news261017", "kind": "deprecations", "status": 304, "checkedAt": "2026-11-07T13:59:15.201000995Z", "changedAt": "2026-10-31T06:04:19.575025917Z", "fingerprint": "74700a59c8e2" }, { "url": "https://api-docs.deepseek.com/updates", "kind": "deprecations", "status": 304, "checkedAt": "2026-11-07T13:59:20.375826803Z", "changedAt": "2026-10-31T06:04:24.312825715Z", "fingerprint": "6174000a0320" }, { "url": "https://api-docs.deepseek.com/quick_start/pricing", "kind": "pricing", "status": 304, "checkedAt": "2026-11-07T13:59:19.634972625Z", "changedAt": "2026-11-06T13:22:07.043235589Z", "fingerprint": "52dc96560b1e" }, { "url": "https://cdn.deepseek.com/policies/en-US/deepseek-privacy-policy.html", "kind": "privacy", "status": 304, "checkedAt": "2026-11-07T14:00:50.892446652Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "a8cd8da7a4f7" }, { "url": "https://cdn.deepseek.com/policies/en-US/deepseek-open-platform-terms-of-service.html", "kind": "terms", "status": 304, "checkedAt": "2026-11-07T14:00:48.871318652Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "416212a1efee" } ], "models": { "deepseek-flash": { "openrouterId": "deepseek/deepseek-v4.1-flash", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "image", "text" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 943718, "checkedAt": "2026-11-06T23:49:25.225778715Z" }, "deepseek-v4-pro": { "openrouterId": "deepseek/deepseek-v4-pro", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "text" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 384000, "checkedAt": "2026-11-06T23:49:25.225778715Z" } }, "updatedAt": "2026-11-07T19:22:03.302224921Z" } }, "answer": "Hugging Face Inference Providers scores 54 (C) on agent readiness against DeepSeek API's 46.7 (D), and leads in 4 of 7 scored categories. DeepSeek API leads on reliability and agent ergonomics.", "b": { "slug": "hugging-face-inference-providers", "name": "Hugging Face Inference Providers", "vendor": "Hugging Face, Inc.", "vendorUrl": "https://huggingface.co", "kind": "router", "category": "inference", "summary": "Hugging Face's serverless router that sends model calls to partner inference providers such as Groq, Cerebras, Together and Fireworks through one Hugging Face token, with an OpenAI-compatible API at router.huggingface.co/v1 and Python and JavaScript clients.", "url": "https://www.anchorterminal.com/tools/hugging-face-inference-providers", "markdownUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-providers.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-providers.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-providers.json", "dns": "hugging-face-inference-providers.grade.anchorterminal.com", "repo": "https://github.com/huggingface/huggingface_hub", "license": "Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT", "transports": [ "http" ], "remoteUrl": "https://router.huggingface.co/v1", "packages": [ { "registry": "pypi", "name": "huggingface_hub" }, { "registry": "npm", "name": "@huggingface/inference" } ], "auth": "api-key", "authNotes": "Hugging Face user access token sent as `Authorization: Bearer $HF_TOKEN`. The docs recommend a fine-grained token with only the `Make calls to Inference Providers` permission. Tokens are made in account settings in a browser, can be rotated and revoked, and a leaked token can be revoked by anyone through `POST /api/credentials/revoke`. A provider's own key can be stored in settings instead, and Hugging Face swaps it in when routing.", "pricing": "usage", "pricingNotes": "Pay as you go at each provider's own per-token rates with no Hugging Face markup, drawn from prepaid credits on the Hugging Face account. Free users get no included credits since 7 October 2026 and must buy credits. PRO users and Team or Enterprise seats get $2.00 a month of compute credits. Requests with a custom provider key are billed by the provider (https://huggingface.co/docs/inference-providers/pricing, checked 2026-11-06).", "priceSummary": "$2 / mo", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the Inference Providers docs, llms.txt or the router's model list. Calls draw on prepaid Hugging Face credits bought in the account's billing settings (checked 2026-11-06).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 483470, "pypiWeekly": 71518708, "asOf": "2026-11-06" }, "docsUrl": "https://huggingface.co/docs/inference-providers/index", "llmsTxt": "https://huggingface.co/docs/inference-providers/llms.txt", "capabilities": [ "inference.router", "inference.open-weights", "inference.llm" ], "tags": [ "hosted", "router", "usage", "prepaid", "openai-compatible", "llms-txt", "python", "javascript", "status-page", "soc2" ], "lastRelease": "2026-10-29", "graded": true, "anchor": { "graded": true, "score": 54, "grade": "C", "agentReady": false, "rank": 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" } }, "edges": [ { "by": 44, "category": "security", "leads": "hugging-face-inference-providers", "name": "Security \u0026 auth", "reasons": { "a": "Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). Model reading. One Bearer key per balance, no scoping found (20 of 30). The privacy policy, last updated 10 February 2026, says personal data is used to train models, with an opt-out by email to privacy@deepseek.com (0 of 20). Data kept for as long as needed to provide the services, with no period stated and no zero-retention route (5 of 15). Per-call logs or audit logs not found (5 of 15). Security programme 5 of 20 (was 0). The www.deepseek.com footer carries a Report Security Issue address, security@deepseek.com, per the 21 October reading used for DeepSeek's open-weight listings and its Search and Fetch API listing. No security.txt (404 on 17 October), disclosure policy, certification or bug bounty found. 20 + 0 + 5 + 5 + 5 = 35.", "b": "Model reading. Fine-grained user access tokens that can be limited to the `Make calls to Inference Providers` permission, rotated and revoked, plus a public revocation endpoint for leaked tokens, and organisation approval of fine-grained tokens on paid plans (30). Hugging Face says it doesn't store user data for training, but data handling past the router follows each provider's policy, with no per-request filter to exclude providers that train or retain (12 of 20). Request bodies and responses aren't stored when routed and debug logs are kept up to 30 days without user data or tokens, with provider retention outside that statement (10 of 15). Usage by model and provider in account settings, an Enterprise usage API, and Team and Enterprise admins can disable providers and set a spending limit (13 of 15). SOC 2 Type 2 for the Hub, of which the docs say Inference Providers is a feature, and security.txt valid to 2030 per the Inference Endpoints check; no bug bounty found (14 of 20)." }, "scores": { "a": 35, "b": 79 } }, { "by": 35, "category": "reliability", "leads": "deepseek-api", "name": "Reliability", "reasons": { "a": "Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). Status page at status.deepseek.com, run on Flashduty, with per-API components and a readable feed (20). The recorded feed lists 36 incidents from 22 July to 15 October. Four touch only web search, 27 are degraded performance, and five are partial unavailability, one of them (12 October) the web chat only. Of the four that hit the API, 28 July (7 minutes) has left the 90-day window and 2 September lasted 31 minutes. 14 September (18:30 to 21:30 UTC) left the V4.1 Flash API and chat partly unavailable for three hours, and 15 October (00:11 to 05:04 UTC) left the V4 Pro and V4.1 Flash APIs and chat partly unavailable for 4 hours 52 minutes. Two majors in 90 days sit between one (10) and several (0), so 5. 16 October to 5 November is unread and earns nothing beyond the recorded award (5). Concurrency caps published per account, 2,500 on Flash and 500 on V4 Pro, and requests that haven't started inference after 10 minutes are closed (15). The rate-limit and error pages document 429, and advise a brief wait and retry on 500 and 503, with no `Retry-After` header, backoff schedule or statement that a retried call is safe (10 of 15). No SLA found (0). V4 Pro and V4.1 Flash are GA (10). 20 + 5 + 15 + 10 + 0 + 10 = 60.", "b": "Hosted lines. status.huggingface.co is a Better Stack page with 90-day component history for the Hub, Inference Endpoints, Spaces, the CDNs and Jobs, but no component for Inference Providers or the router (10 of 20). With no component, there is no readable incident history for the surface agents call, and the feed's 23 items from 10 June to 7 October 2026 don't name it (5). No rate limits for the router were found; the Hub rate-limits page gives numbers for Hub APIs, resolvers and pages only (0). No 429 or overload guidance for the router was found (0). No SLA found (0). Chat completions on the router is generally available; the Responses API is labelled beta (10). Routing between providers with `:fastest` or `:cheapest` softens a single provider's outage, which this checklist doesn't score." }, "scores": { "a": 60, "b": 25 } }, { "by": 34, "category": "maintenance", "leads": "hugging-face-inference-providers", "name": "Maintenance \u0026 community", "reasons": { "a": "Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). Model reading. V4.1 Flash was upgraded to DeepSeek-V4.1-Flash-1017 on 17 October under the same `deepseek-flash` name and price, posted on the updates page the same day, 19 days before this check (30). Later updates entries are unread. No stated notice policy. `deepseek-chat` and `deepseek-reasoner` got three months, announced on 24 April for 24 July. One dated notice with no stated period partly meets the line, and the earlier partial award is held (4 of 12). Model churn covers the V4 Flash retirement on 10 September and the V4 Pro shutdown set for 14 September, announced on 13 August and withdrawn on 10 September. The 24 July shutdown has left the 90-day window. A retirement and a withdrawn shutdown inside it keep churn at the bottom of its range (0 of 8). Dated updates page, and the docs list api-service@deepseek.com and a Discord server for support. We didn't test whether either answers (12 of 15). No official SDKs or SDK repository (0 of 15, 0 of 10). 30 + 4 + 0 + 12 + 0 + 0 = 46.", "b": "Model reading. huggingface_hub 2.4.0 tagged on 29 October 2026 and the Inference Providers docs updated daily by an automated job, last on 6 November (30). huggingface_hub 2.2.0, 2.3.0 and 2.4.0 and @huggingface/inference 4.13.28 to 4.13.32 in the 90 days (20). No dedicated changelog; the Hub has a forum and Discord, and GitHub issue replies were not read (8 of 15). Current official SDKs in Python and JavaScript (15). The Python client supports Python 3.10 and later, per the Inference Endpoints check; CI not read (7 of 10)." }, "scores": { "a": 46, "b": 80 } }, { "by": 13, "category": "schema", "leads": "hugging-face-inference-providers", "name": "Schema \u0026 documentation", "reasons": { "a": "Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). No OpenAPI document and no llms.txt found (0 and 0). API reference covers both the OpenAI and Anthropic formats. The chat completion reference, read on 2 October, describes each parameter with its range and default, such as `max_tokens` from 1 to 393,216 with 8K by default without thinking, but says little on when not to use one (14 of 20). Strict tool calls are documented, in beta at the `/beta` base URL, with a JSON Schema subset (object, string, number, integer, boolean, array, enum, anyOf, `$ref`) where every property must be required. JSON output mode carries no schema guarantee (10 of 15). The error codes page lists seven codes, each with a cause and a fix, but no example bodies (10 of 15). Dated updates page that names model changes (15). 0 + 0 + 14 + 10 + 10 + 15 = 49.", "b": "No OpenAPI document for the router (openapi.json paths answer 404). The task reference pages are generated from typed JSON Schema specs in huggingface.js, and the router's /v1/models gives a machine-readable catalogue, so 12 of 25. llms.txt for the Inference Providers docs and a Markdown twin of every page via `.md` (10). Guides say what each task and policy is for, with a quick setup page for coding agents (14 of 20). Parameter tables with types for chat completion, though `response_format` and `tool_choice` show as unknown types (9 of 15). Examples in Python, JavaScript and curl on every task page, but no documented error responses for the router (9 of 15). No changelog of its own; the Hub changelog doesn't cover it and dated changes are only in the hub-docs history (8 of 15)." }, "scores": { "a": 49, "b": 62 } }, { "by": 12, "category": "ergonomics", "leads": "deepseek-api", "name": "Agent ergonomics", "reasons": { "a": "Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool calls through both request formats, and the API reference documents `tool_choice` as none, auto, required or a named function (20 of 20). Strict schema-enforced tool calls in beta, JSON output without a schema guarantee (10 of 15). Disk cache on by default with cheaper hits, per the listing (15). 1M-token context and up to 384K output (15). No batch API documented (0). No official SDKs, you use the OpenAI or Anthropic client (0). Seven error codes with a fix for each, 402 for an empty balance (10 of 15). 20 + 10 + 15 + 15 + 0 + 0 + 10 = 70.", "b": "Router reading of the model checklist (tool use, structured output, caching, context, batch, SDKs, errors), as for openrouter. Tool calling through the OpenAI-compatible API with `tool_choice`, support flagged per provider in /v1/models (15 of 20). Structured output documented, support flagged per provider and false on some (10 of 15). No prompt caching guidance found, though the Enterprise usage API counts cached input tokens (3 of 15). Routes to models with up to 1,048,576 tokens of context per the model list, a judgement call since a router has no default model (15). No batch API (0 of 10). Official clients in Python and JavaScript, plus any OpenAI SDK (10). Errors not documented (5 of 15)." }, "scores": { "a": 70, "b": 58 } }, { "by": 6, "category": "transparency", "leads": "hugging-face-inference-providers", "name": "Transparency \u0026 trust", "reasons": { "a": "Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). Closed service with clear terms under PRC law. The model weights are published, which doesn't change the hosted service (15). The privacy policy of 10 February 2026 is consistent on training by default and storage in the PRC, but publishes no retention period and no DPA (10 of 30). Dated notices on the updates page, undercut by a shutdown announced and withdrawn within a month and a reroute with no prior entry (10 of 20). Data location disclosed as the PRC, third parties named only by category (10 of 20). 15 + 10 + 10 + 10 = 45.", "b": "Closed service under Terms of Service that name Inference Providers, with an Apache-2.0 Python client and an MIT JavaScript client (20). The security page and the docs agree on no training, no stored bodies and 30-day logs, but the privacy policy dates from 28 March 2023 and each provider's own data policy governs the rest (18 of 30). No deprecation policy found. Provider support changes and the 7 October removal of free credits are dated only in the docs repository history (5 of 20). The privacy policy lists 11 subprocessors with countries per the Inference Endpoints check, and the docs name every provider a request can reach, though not where each runs (15 of 20)." }, "scores": { "a": 65, "b": 71 } } ], "facts": [ { "a": "Model API", "b": "Model router", "name": "Kind" }, { "a": "DeepSeek", "b": "Hugging Face, Inc.", "name": "Vendor" }, { "a": "https://api.deepseek.com", "b": "https://router.huggingface.co/v1", "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": "none", "b": "Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-17", "b": "2026-10-29", "name": "Last release" }, { "a": "couldn't be read", "b": "2022-09-15", "name": "Terms last updated" }, { "a": "couldn't be read", "b": "2023-03-28", "name": "Privacy policy last updated" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "couldn't be read", "b": "yes", "name": "Terms or service can change without notice" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "483k npm/wk, 71.5M PyPI/wk", "name": "Popularity" }, { "a": "2/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Hugging Face Inference Providers scores 54 (C) on agent readiness against DeepSeek API's 46.7 (D), and leads in 4 of 7 scored categories. DeepSeek API leads on reliability and agent ergonomics.", "question": "Which is better for AI agents, DeepSeek API or Hugging Face Inference Providers?" }, { "answer": "Both need an API key.", "question": "Do DeepSeek API and Hugging Face Inference Providers need an API key?" }, { "answer": "Yes. DeepSeek API has a hosted endpoint at https://api.deepseek.com and Hugging Face Inference Providers at https://router.huggingface.co/v1.", "question": "Can an agent call DeepSeek API and Hugging Face Inference Providers without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 60 against 25", "Agent ergonomics, 70 against 58" ], "also": null, "goodFor": "Low-cost long-context work on public data, and off-peak batch-style jobs run through the normal API.", "slug": "deepseek-api", "watchFor": "36 status incidents from 22 July to 15 October 2026, with partial API outages of three hours on 14 September and 4 hours 52 minutes on 15 October" }, { "aheadOn": [ "Schema \u0026 documentation, 62 against 49", "Security \u0026 auth, 79 against 35", "Maintenance \u0026 community, 80 against 46", "Transparency \u0026 trust, 71 against 65" ], "also": [ "No incidents deducted, where DeepSeek API loses 3 points for them" ], "goodFor": "Agents and developers who want open-weight models from several hosts on one token and one bill, with a public price and capability list per provider.", "slug": "hugging-face-inference-providers", "watchFor": "No rate limits, 429 behaviour or error responses documented for the router" } ], "history": { "deepseek-api": [ { "causes": [ "correction" ], "date": "2026-11-05", "delta": 0.9, "from": 45.8, "fromGrade": "E", "to": 46.7, "toGrade": "D" }, { "causes": [ "reliability" ], "date": "2026-10-17", "delta": -1, "from": 46.8, "fromGrade": "D", "to": 45.8, "toGrade": "E" }, { "causes": [ "method" ], "date": "2026-10-08", "delta": -0.3, "from": 47.1, "fromGrade": "D", "to": 46.8, "toGrade": "D" } ], "hugging-face-inference-providers": null }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-deepseek-api.json", "title": "Amazon Bedrock vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-deepseek-api" }, { 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"https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-routerplus.json", "title": "Hugging Face Inference Providers vs RouterPlus", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-tencent-tokenhub.json", "title": "Hugging Face Inference Providers vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway.json", "title": "Hugging Face Inference Providers vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-nemotron-3-5-super-vl.json", "title": "Hugging Face Inference Providers vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference.json", "title": "Hugging Face Inference Providers vs Prism Inference", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference" } ], "panel": null, "scores": [ { "by": 35, "deepseek-api": 60, "edge": "deepseek-api", "hugging-face-inference-providers": 25, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 13, "deepseek-api": 49, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 62, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 12, "deepseek-api": 70, "edge": "deepseek-api", "hugging-face-inference-providers": 58, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "by": 44, "deepseek-api": 35, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 79, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "by": 0, "deepseek-api": 20, "edge": "", "hugging-face-inference-providers": 20, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 34, "deepseek-api": 46, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 80, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 6, "deepseek-api": 65, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 71, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Hugging Face Inference Providers scores 54 (C) on agent readiness against DeepSeek API's 46.7 (D), and leads in 4 of 7 scored categories. DeepSeek API leads on reliability and agent ergonomics. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "deepseek-api": "Accepts the OpenAI Chat Completions, OpenAI Responses and Anthropic request formats at per-token prices that halve off-peak. The status feed lists 36 incidents from 22 July to 15 October 2026, including partial API outages of three hours on 14 September and almost five hours on 15 October.", "hugging-face-inference-providers": "One Hugging Face token reaches open models on 18 partner providers at the providers' own prices, with a public model list that shows each provider's price, context and tool support. Router rate limits, error responses and its own status component were not found in the reviewed documentation, and free accounts have had no included credits since 7 October 2026." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/deepseek-api-vs-hugging-face-inference-providers", "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-hugging-face-inference-providers.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/deepseek-api-vs-hugging-face-inference-providers.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/deepseek-api-vs-hugging-face-inference-providers.min.md" }, "markdown": "Hugging Face Inference Providers scores 54 (C) on agent readiness against DeepSeek API's 46.7 (D), and leads in 4 of 7 scored categories. DeepSeek API leads on reliability and agent ergonomics. Both do llm inference.\n\n- DeepSeek API: grade D, 46.7/100, rank #1167 of 1510. Markdown https://www.anchorterminal.com/tools/deepseek-api.md · JSON https://www.anchorterminal.com/api/v1/tools/deepseek-api.json\n- Hugging Face Inference Providers: grade C, 54/100, rank #926 of 1510. Markdown https://www.anchorterminal.com/tools/hugging-face-inference-providers.md · JSON https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-providers.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 830 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### DeepSeek API (D)\n\nGood for: Low-cost long-context work on public data, and off-peak batch-style jobs run through the normal API.\n\nAhead on:\n- Reliability, 60 against 25\n- Agent ergonomics, 70 against 58\n\nWatch for: 36 status incidents from 22 July to 15 October 2026, with partial API outages of three hours on 14 September and 4 hours 52 minutes on 15 October\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- Schema \u0026 documentation, 62 against 49\n- Security \u0026 auth, 79 against 35\n- Maintenance \u0026 community, 80 against 46\n- Transparency \u0026 trust, 71 against 65\n\nAlso in its favour:\n- No incidents deducted, where DeepSeek API loses 3 points for them\n\nWatch for: No rate limits, 429 behaviour or error responses documented for the router\n\n\n## Why the edge\n\n### Security \u0026 auth: Hugging Face Inference Providers +44\n\n- DeepSeek API (35): Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). Model reading. One Bearer key per balance, no scoping found (20 of 30). The privacy policy, last updated 10 February 2026, says personal data is used to train models, with an opt-out by email to privacy@deepseek.com (0 of 20). Data kept for as long as needed to provide the services, with no period stated and no zero-retention route (5 of 15). Per-call logs or audit logs not found (5 of 15). Security programme 5 of 20 (was 0). The www.deepseek.com footer carries a Report Security Issue address, security@deepseek.com, per the 21 October reading used for DeepSeek's open-weight listings and its Search and Fetch API listing. No security.txt (404 on 17 October), disclosure policy, certification or bug bounty found. 20 + 0 + 5 + 5 + 5 = 35.\n- Hugging Face Inference Providers (79): Model reading. Fine-grained user access tokens that can be limited to the `Make calls to Inference Providers` permission, rotated and revoked, plus a public revocation endpoint for leaked tokens, and organisation approval of fine-grained tokens on paid plans (30). Hugging Face says it doesn't store user data for training, but data handling past the router follows each provider's policy, with no per-request filter to exclude providers that train or retain (12 of 20). Request bodies and responses aren't stored when routed and debug logs are kept up to 30 days without user data or tokens, with provider retention outside that statement (10 of 15). Usage by model and provider in account settings, an Enterprise usage API, and Team and Enterprise admins can disable providers and set a spending limit (13 of 15). SOC 2 Type 2 for the Hub, of which the docs say Inference Providers is a feature, and security.txt valid to 2030 per the Inference Endpoints check; no bug bounty found (14 of 20).\n\n### Reliability: DeepSeek API +35\n\n- DeepSeek API (60): Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). Status page at status.deepseek.com, run on Flashduty, with per-API components and a readable feed (20). The recorded feed lists 36 incidents from 22 July to 15 October. Four touch only web search, 27 are degraded performance, and five are partial unavailability, one of them (12 October) the web chat only. Of the four that hit the API, 28 July (7 minutes) has left the 90-day window and 2 September lasted 31 minutes. 14 September (18:30 to 21:30 UTC) left the V4.1 Flash API and chat partly unavailable for three hours, and 15 October (00:11 to 05:04 UTC) left the V4 Pro and V4.1 Flash APIs and chat partly unavailable for 4 hours 52 minutes. Two majors in 90 days sit between one (10) and several (0), so 5. 16 October to 5 November is unread and earns nothing beyond the recorded award (5). Concurrency caps published per account, 2,500 on Flash and 500 on V4 Pro, and requests that haven't started inference after 10 minutes are closed (15). The rate-limit and error pages document 429, and advise a brief wait and retry on 500 and 503, with no `Retry-After` header, backoff schedule or statement that a retried call is safe (10 of 15). No SLA found (0). V4 Pro and V4.1 Flash are GA (10). 20 + 5 + 15 + 10 + 0 + 10 = 60.\n- Hugging Face Inference Providers (25): Hosted lines. status.huggingface.co is a Better Stack page with 90-day component history for the Hub, Inference Endpoints, Spaces, the CDNs and Jobs, but no component for Inference Providers or the router (10 of 20). With no component, there is no readable incident history for the surface agents call, and the feed's 23 items from 10 June to 7 October 2026 don't name it (5). No rate limits for the router were found; the Hub rate-limits page gives numbers for Hub APIs, resolvers and pages only (0). No 429 or overload guidance for the router was found (0). No SLA found (0). Chat completions on the router is generally available; the Responses API is labelled beta (10). Routing between providers with `:fastest` or `:cheapest` softens a single provider's outage, which this checklist doesn't score.\n\n### Maintenance \u0026 community: Hugging Face Inference Providers +34\n\n- DeepSeek API (46): Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). Model reading. V4.1 Flash was upgraded to DeepSeek-V4.1-Flash-1017 on 17 October under the same `deepseek-flash` name and price, posted on the updates page the same day, 19 days before this check (30). Later updates entries are unread. No stated notice policy. `deepseek-chat` and `deepseek-reasoner` got three months, announced on 24 April for 24 July. One dated notice with no stated period partly meets the line, and the earlier partial award is held (4 of 12). Model churn covers the V4 Flash retirement on 10 September and the V4 Pro shutdown set for 14 September, announced on 13 August and withdrawn on 10 September. The 24 July shutdown has left the 90-day window. A retirement and a withdrawn shutdown inside it keep churn at the bottom of its range (0 of 8). Dated updates page, and the docs list api-service@deepseek.com and a Discord server for support. We didn't test whether either answers (12 of 15). No official SDKs or SDK repository (0 of 15, 0 of 10). 30 + 4 + 0 + 12 + 0 + 0 = 46.\n- Hugging Face Inference Providers (80): Model reading. huggingface_hub 2.4.0 tagged on 29 October 2026 and the Inference Providers docs updated daily by an automated job, last on 6 November (30). huggingface_hub 2.2.0, 2.3.0 and 2.4.0 and @huggingface/inference 4.13.28 to 4.13.32 in the 90 days (20). No dedicated changelog; the Hub has a forum and Discord, and GitHub issue replies were not read (8 of 15). Current official SDKs in Python and JavaScript (15). The Python client supports Python 3.10 and later, per the Inference Endpoints check; CI not read (7 of 10).\n\n### Schema \u0026 documentation: Hugging Face Inference Providers +13\n\n- DeepSeek API (49): Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). No OpenAPI document and no llms.txt found (0 and 0). API reference covers both the OpenAI and Anthropic formats. The chat completion reference, read on 2 October, describes each parameter with its range and default, such as `max_tokens` from 1 to 393,216 with 8K by default without thinking, but says little on when not to use one (14 of 20). Strict tool calls are documented, in beta at the `/beta` base URL, with a JSON Schema subset (object, string, number, integer, boolean, array, enum, anyOf, `$ref`) where every property must be required. JSON output mode carries no schema guarantee (10 of 15). The error codes page lists seven codes, each with a cause and a fix, but no example bodies (10 of 15). Dated updates page that names model changes (15). 0 + 0 + 14 + 10 + 10 + 15 = 49.\n- Hugging Face Inference Providers (62): No OpenAPI document for the router (openapi.json paths answer 404). The task reference pages are generated from typed JSON Schema specs in huggingface.js, and the router's /v1/models gives a machine-readable catalogue, so 12 of 25. llms.txt for the Inference Providers docs and a Markdown twin of every page via `.md` (10). Guides say what each task and policy is for, with a quick setup page for coding agents (14 of 20). Parameter tables with types for chat completion, though `response_format` and `tool_choice` show as unknown types (9 of 15). Examples in Python, JavaScript and curl on every task page, but no documented error responses for the router (9 of 15). No changelog of its own; the Hub changelog doesn't cover it and dated changes are only in the hub-docs history (8 of 15).\n\n### Agent ergonomics: DeepSeek API +12\n\n- DeepSeek API (70): Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool calls through both request formats, and the API reference documents `tool_choice` as none, auto, required or a named function (20 of 20). Strict schema-enforced tool calls in beta, JSON output without a schema guarantee (10 of 15). Disk cache on by default with cheaper hits, per the listing (15). 1M-token context and up to 384K output (15). No batch API documented (0). No official SDKs, you use the OpenAI or Anthropic client (0). Seven error codes with a fix for each, 402 for an empty balance (10 of 15). 20 + 10 + 15 + 15 + 0 + 0 + 10 = 70.\n- Hugging Face Inference Providers (58): Router reading of the model checklist (tool use, structured output, caching, context, batch, SDKs, errors), as for openrouter. Tool calling through the OpenAI-compatible API with `tool_choice`, support flagged per provider in /v1/models (15 of 20). Structured output documented, support flagged per provider and false on some (10 of 15). No prompt caching guidance found, though the Enterprise usage API counts cached input tokens (3 of 15). Routes to models with up to 1,048,576 tokens of context per the model list, a judgement call since a router has no default model (15). No batch API (0 of 10). Official clients in Python and JavaScript, plus any OpenAI SDK (10). Errors not documented (5 of 15).\n\n### Transparency \u0026 trust: Hugging Face Inference Providers +6\n\n- DeepSeek API (65): Per the 17 October check, not re-read on 5 November (DeepSeek's terms bar automated access, so nothing on DeepSeek's hosts was requested). Closed service with clear terms under PRC law. The model weights are published, which doesn't change the hosted service (15). The privacy policy of 10 February 2026 is consistent on training by default and storage in the PRC, but publishes no retention period and no DPA (10 of 30). Dated notices on the updates page, undercut by a shutdown announced and withdrawn within a month and a reroute with no prior entry (10 of 20). Data location disclosed as the PRC, third parties named only by category (10 of 20). 15 + 10 + 10 + 10 = 45.\n- Hugging Face Inference Providers (71): Closed service under Terms of Service that name Inference Providers, with an Apache-2.0 Python client and an MIT JavaScript client (20). The security page and the docs agree on no training, no stored bodies and 30-day logs, but the privacy policy dates from 28 March 2023 and each provider's own data policy governs the rest (18 of 30). No deprecation policy found. Provider support changes and the 7 October removal of free credits are dated only in the docs repository history (5 of 20). The privacy policy lists 11 subprocessors with countries per the Inference Endpoints check, and the docs name every provider a request can reach, though not where each runs (15 of 20).\n\n## Score by category\n\n| Category | Weight | DeepSeek API | Hugging Face Inference Providers | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 60 | 25 | DeepSeek API +35 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 49 | 62 | Hugging Face Inference Providers +13 |\n| Agent ergonomics | 13% (16.2 this run) | 70 | 58 | DeepSeek API +12 |\n| Security \u0026 auth | 14% (17.5 this run) | 35 | 79 | Hugging Face Inference Providers +44 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 20 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 46 | 80 | Hugging Face Inference Providers +34 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 65 | 71 | Hugging Face Inference Providers +6 |\n| Negative events | ≤15 | -3 | 0 | |\n| **Total** | | **46.7 · D** | **54 · C** | |\n\n## Facts side by side\n\n| Fact | DeepSeek API | Hugging Face Inference Providers |\n| --- | --- | --- |\n| Kind | Model API | Model router |\n| Vendor | DeepSeek | Hugging Face, Inc. |\n| Hosted endpoint | `https://api.deepseek.com` | `https://router.huggingface.co/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | none | Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-17 | 2026-10-29 |\n| Terms last updated | couldn't be read | 2022-09-15 |\n| Privacy policy last updated | couldn't be read | 2023-03-28 |\n| Customer content may train models | couldn't be read | not found in the text |\n| Terms restrict automated access | couldn't be read | not found in the text |\n| Terms restrict benchmarking | couldn't be read | not found in the text |\n| Terms or service can change without notice | couldn't be read | yes |\n| Arbitration or class-action waiver | couldn't be read | not found in the text |\n| Popularity | none | 483k npm/wk, 71.5M PyPI/wk |\n| Agent reviews | 2/5 (2) | none |\n\n## How the scores have moved\n\n### DeepSeek API\n\n- +0.9 on 5 November 2026 (E to D): correction\n- -1.0 on 17 October 2026 (D to E): reliability\n- -0.3 on 8 October 2026: checklist\n\n### Hugging Face Inference Providers\n\nNo score change since it was listed.\n\n## Verdicts\n\n**DeepSeek API.** Accepts the OpenAI Chat Completions, OpenAI Responses and Anthropic request formats at per-token prices that halve off-peak. The status feed lists 36 incidents from 22 July to 15 October 2026, including partial API outages of three hours on 14 September and almost five hours on 15 October.\n\n**Hugging Face Inference Providers.** One Hugging Face token reaches open models on 18 partner providers at the providers' own prices, with a public model list that shows each provider's price, context and tool support. Router rate limits, error responses and its own status component were not found in the reviewed documentation, and free accounts have had no included credits since 7 October 2026.\n\n## Before you call either\n\n### DeepSeek API\n\n1. Send only data you'd be happy to publish\n2. Schedule bulk work off-peak for half price. Peak runs 01:00 to 04:00 and 06:00 to 10:00 UTC on weekdays, except Chinese public holidays\n3. Set `max_tokens` yourself. It defaults to 8K without thinking and 64K with it, against a 384K ceiling\n4. For schema-checked tool arguments use base URL `https://api.deepseek.com/beta`, set `strict: true`, mark every property required and set `additionalProperties: false`\n5. Keep a fallback provider and re-run evals after model changes. 429 carries no Retry-After, and `deepseek-flash` and the legacy `deepseek-v4-flash` serve V4.1-Flash-1017 since 17 October 2026\n\n### Hugging Face Inference Providers\n\n1. Read https://router.huggingface.co/v1/models before choosing a provider; it shows price, context and `supports_tools` per provider\n2. Pin a provider with `model:\u003cprovider\u003e` when tool calling or structured output matters, since support varies by provider\n3. Use a fine-grained token with only the Inference Providers permission, and send `X-HF-Bill-To` to bill an organisation\n4. Back off on 429 without assuming a Retry-After header, since none is documented for the router\n\n## Questions\n\n### Which is better for AI agents, DeepSeek API or Hugging Face Inference Providers?\n\nHugging Face Inference Providers scores 54 (C) on agent readiness against DeepSeek API's 46.7 (D), and leads in 4 of 7 scored categories. DeepSeek API leads on reliability and agent ergonomics.\n\n### Do DeepSeek API and Hugging Face Inference Providers need an API key?\n\nBoth need an API key.\n\n### Can an agent call DeepSeek API and Hugging Face Inference Providers without installing anything?\n\nYes. DeepSeek API has a hosted endpoint at https://api.deepseek.com and Hugging Face Inference Providers at https://router.huggingface.co/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/deepseek-api-vs-hugging-face-inference-providers.json, and with the fewest tokens: https://www.anchorterminal.com/compare/deepseek-api-vs-hugging-face-inference-providers.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"deepseek-api\", \"b\": \"hugging-face-inference-providers\"}`. 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4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-07", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 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": "DeepSeek API vs Hugging Face Inference Providers", "url": "" } ], "description": "Hugging Face Inference Providers scores 54 (C) to DeepSeek's 46.7 (D) for llm inference. 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