{ "data": { "a": { "slug": "gemini-api", "name": "Gemini Developer API", "vendor": "Google", "vendorUrl": "https://ai.google.dev", "kind": "model", "category": "inference", "summary": "Google's API for Gemini models, including content generation and agent interactions.", "url": "https://www.anchorterminal.com/tools/gemini-api", "markdownUrl": "https://www.anchorterminal.com/tools/gemini-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/gemini-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/gemini-api.json", "dns": "gemini-api.grade.anchorterminal.com", "repo": "https://github.com/googleapis/python-genai", "license": "Apache-2.0 (SDKs)", "transports": [ "http" ], "remoteUrl": "https://generativelanguage.googleapis.com/v1beta", "packages": [ { "registry": "pypi", "name": "google-genai", "main": true }, { "registry": "npm", "name": "@google/genai", "main": true } ], "auth": "api-key", "authNotes": "`x-goog-api-key` header with a key from AI Studio. A Google account is needed to make one.", "pricing": "freemium", "pricingNotes": "Free tier on 3.8 Flash, 3.6 Flash and the Flash-Lite models, not on Gemini 4 Argon or 3.1 Pro preview, and free-tier content is used to improve Google products. Gemini 4 Argon (`gemini-4-argon`) costs $2/$10 per million tokens through 2026-11-30, then $4/$20, with implicit caching only. 3.1 Pro preview costs $2/$12 per million tokens, $4/$18 over 200K. 3.8 Flash is $0.75/$3.75 until 2026-12-31, then $1.50/$7.50. Cached input 0.1x. Nano Banana 2.1 (`gemini-nano-banana-2.1`, images) is paid tier only at $1.50 input and $30 per million image output tokens, about $0.034 a 1K image, $0.050 at 2K and $0.113 at 4K, half that in batch. Search grounding 5,000 free a month, then $14 per 1,000. Batch half price (https://ai.google.dev/gemini-api/docs/pricing).", "priceSummary": "from $0.25 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No machine payment. The free tier needs a Google account and paid use needs billing on a Cloud project.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 3992, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-09-26" }, "docsUrl": "https://ai.google.dev/gemini-api/docs", "rateLimitsUrl": "https://ai.google.dev/gemini-api/docs/rate-limits", "llmsTxt": "https://ai.google.dev/gemini-api/docs/llms.txt", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "free-tier", "no-card", "llms-txt" ], "lastRelease": "2026-10-30", "graded": true, "anchor": { "graded": true, "score": 62.2, "grade": "B", "agentReady": false, "rank": 568, "ranked": true, "rankOf": 1510, "categoryRank": 21, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 93, "maintenance": 83, "payments": 40, "reliability": 45, "schema": 85, "security": 50, "transparency": 72 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": -3, "negativeNotes": [ "2026-10-08. Google deprecated the generally available `gemini-3.7-flash` and `gemini-3.5-flash` and routed API requests for them to `gemini-3.8-flash` and `gemini-3.6-flash` the same day, announced in that day's changelog. Callers pinned to those names got a different model without notice, the reading DeepSeek API takes for its 10 September routing, so 3 points (https://ai.google.dev/gemini-api/docs/changelog, https://ai.google.dev/gemini-api/docs/deprecations)." ], "verdict": "Free tier on 3.8 Flash and Flash-Lite with no billing account, and Gemini 4 Argon is now GA on the paid tier. Free-tier prompts and responses improve Google products and may be read by human reviewers, and the API accepts an OAuth token in the URL query string.", "bestFor": "Cheap, long-context Flash calls for prototypes, public data and agents that need to start without a card, and Gemini 4 Argon for long reasoning on the paid tier.", "strengths": [ "Free tier on 3.8 Flash and Flash-Lite with no billing account", "Gemini 4 Argon went GA on 13 October 2026 with a 1,048,576-token shared window and long decode up to 1M tokens", "Backoff guidance with jitter, and the Python SDK retries transient errors four times", "New keys are bound to a service account and restricted to the Gemini API, and unrestricted standard keys are rejected", "A keyless Discovery document types the v1beta GenerateContent surface, and function calling can be forced to named tools" ], "weaknesses": [ "Free-tier prompts and responses improve Google products and may be read by human reviewers", "The API reads an OAuth access token from the `access_token` query parameter", "No SLA and no zero-retention route found for the Developer API", "Gemini 4 Argon isn't on the free tier and doesn't support explicit context caching", "Shutdown dates are 'earliest possible' with no stated minimum notice, and one preview agent got 15 days" ], "agentNotes": [ "Never send customer data through a free-tier key. Link billing first", "Send keys in the `x-goog-api-key` header, never as `key` or `access_token` in the URL", "Back off exponentially on 429 RESOURCE_EXHAUSTED and 503, and don't retry 400, 402 or 403", "Remove temperature, top_p and top_k. Gemini 4 and 3.6+ ignore them and a future release returns 400", "On `gemini-4-argon`, set max_output_tokens to at least 32,768 and client timeouts to 15 minutes, or use background execution" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 62.2 } ], "editorialScores": { "ergonomics": 93, "maintenance": 83, "payments": 40, "reliability": 45, "schema": 85, "security": 50, "transparency": 55 }, "provenanceScore": 89, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-11-01", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install google-genai # or: npm i @google/genai", "http": "curl \"https://generativelanguage.googleapis.com/v1beta/models/gemini-3.8-flash:generateContent\" \\\n -H \"x-goog-api-key: $GEMINI_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"contents\":[{\"parts\":[{\"text\":\"hello\"}]}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/gemini-api" }, "sameCompany": [ "vertex-ai", "gemini-embedding", "vertex-ai-tuning", "cloud-run-gpus", "google-model-armor", "google-imagen", "google-veo", "google-lyria", "google-speech-to-text", "google-cloud-tts", "gemini-live", "google-adk", "google-memory-bank", "google-secret-manager", "google-cloud-document-ai", "google-weather-api", "chrome-devtools-mcp", "google-maps-platform", "google-cloud-translation", "google-calendar-api", "firebase-cloud-messaging", "google-cloud-storage", "google-drive-api", "gemini-enterprise", "gemini-cli", "google-search-console", "google-ads-api", "google-forms", "google-sheets-api", "gmail-api", "google-people-api" ], "sameModel": [ "gemma-4-26b-a4b-it", "gemma-4-31b-it" ], "area": "models", "unitPrices": [ { "item": "Search grounding over 5,000 a month", "unit": "1k-requests", "usd": 14 }, { "item": "Nano Banana 2.1 image, 1K", "unit": "image", "usd": 0.0336, "note": "1,120 output tokens at $30 per million. Paid tier only, half price in batch" }, { "item": "Nano Banana 2.1 image, 2K", "unit": "image", "usd": 0.0504, "note": "1,680 output tokens" }, { "item": "Nano Banana 2.1 image, 4K", "unit": "image", "usd": 0.113, "note": "3,780 output tokens" } ], "provenance": { "legalEntity": "Google LLC", "domain": "google.com", "domainRegistered": "1997-09-15", "domainNote": "The endpoint is on googleapis.com, Google's API domain. google.com was registered in 1997.", "endpointOnVendorDomain": true, "terms": "https://ai.google.dev/gemini-api/terms", "privacy": "https://policies.google.com/privacy", "statusPage": "https://aistudio.google.com/status", "changelog": "https://ai.google.dev/gemini-api/docs/changelog", "securityTxt": "valid", "checked": "2026-11-01", "score": 89 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/gemini-api.json", "live": { "slug": "gemini-api", "probe": { "target": "https://generativelanguage.googleapis.com/v1beta", "method": "get", "lastAt": "2026-11-07T19:22:08.506489918Z", "lastOk": true, "lastStatus": 404, "lastMs": 40, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 37, "p95ms24h": 119, "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://aistudio.google.com/status", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-07T04:47:49.73911967Z" }, "versions": [ { "registry": "github", "name": "googleapis/python-genai", "version": "v3.0.0", "released": "2026-11-06", "seenAt": "2026-11-06T23:27:37.766484844Z" }, { "registry": "npm", "name": "@google/genai", "version": "3.0.0", "seenAt": "2026-11-06T23:27:37.49484945Z" }, { "registry": "pypi", "name": "google-genai", "version": "3.0.0", "released": "2026-11-06", "seenAt": "2026-11-06T23:27:37.329000252Z" } ], "githubStars": 4057, "npmWeekly": 31989360, "pypiWeekly": 38431674, "securityTxt": { "url": "https://google.com/.well-known/security.txt", "state": "valid", "expires": "2030-04-01T00:00:00z", "checkedAt": "2026-11-07T16:01:22.068349931Z" }, "llmsTxt": { "url": "https://ai.google.dev/gemini-api/docs/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:32:33.34914217Z" }, "domain": { "domain": "google.com", "registered": "1997-09-15", "source": "https://rdap.verisign.com/com/v1/domain/google.com", "checkedAt": "2026-11-01T14:17:18.719851913Z" }, "pages": [ { "url": "https://ai.google.dev/gemini-api/docs/changelog", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T13:58:55.08107274Z", "changedAt": "2026-11-07T13:58:55.08107274Z", "fingerprint": "5bad8c4d68e3" }, { "url": "https://ai.google.dev/gemini-api/docs/deprecations", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T13:58:57.400152684Z", "changedAt": "2026-11-07T13:58:57.400152684Z", "fingerprint": "f0958caa84a5" }, { "url": "https://ai.google.dev/gemini-api/docs/pricing", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T13:58:59.844674867Z", "changedAt": "2026-11-06T13:21:47.729671724Z", "fingerprint": "d3b5522104e1" }, { "url": "https://ai.google.dev/gemini-api/terms", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T13:59:01.357633499Z", "changedAt": "2026-11-03T07:41:20.562939041Z", "fingerprint": "07b98470ed02" } ], "models": { "gemini-3.1-flash-lite": { "openrouterId": "google/gemini-3.1-flash-lite", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "audio", "file", "image", "text", "video" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 65536, "checkedAt": "2026-11-06T23:49:25.225778715Z" }, "gemini-3.1-pro-preview": { "openrouterId": "google/gemini-3.1-pro-preview", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "audio", "file", "image", "text", "video" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 65536, "checkedAt": "2026-11-06T23:49:25.225778715Z" }, "gemini-3.5-flash-lite": { "openrouterId": "google/gemini-3.5-flash-lite", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "audio", "file", "image", "text", "video" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 65536, "checkedAt": "2026-11-06T23:49:25.225778715Z" }, "gemini-3.8-flash": { "openrouterId": "google/gemini-3.8-flash", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "audio", "file", "image", "text", "video" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 65536, "checkedAt": "2026-11-06T23:49:25.225778715Z" }, "gemini-4-argon": { "openrouterId": "google/gemini-4-argon", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "audio", "file", "image", "text", "video" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 943718, "checkedAt": "2026-11-06T23:49:25.225778715Z" } }, "github": { "repo": "googleapis/python-genai", "checkedAt": "2026-11-02T08:52:22.518653754Z", "stars": 4054, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-31T00:34:25Z", "openIssues": 227, "openPRs": 143, "issuesOpened90d": 78, "issuesClosed90d": 38, "prsMerged90d": 216, "ci": { "branch": "main", "runs": 50, "success": 50, "failure": 0, "other": 0, "latest": "success", "latestAt": "2026-10-30T23:58:40Z" }, "replies": { "sampled": 25, "unanswered": 16, "medianDays": 7.5 } }, "updatedAt": "2026-11-07T19:22:08.506489918Z" } }, "answer": "Gemini Developer API scores 62.2 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 6 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth.", "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": 35, "category": "ergonomics", "leads": "gemini-api", "name": "Agent ergonomics", "reasons": { "a": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling documented, and `FunctionCallingConfig` mode `ANY` with `allowedFunctionNames` forces a call to a named tool, with a `VALIDATED` mode that checks calls by constrained decoding (20 of 20). The structured output page, re-read on 1 November, says output adheres to the supplied JSON Schema and is syntactically correct JSON, and names the keywords constrained decoding doesn't enforce, while asking callers to validate values (13 of 15; the 12 October note's 10 rested on the page promising no constrained decoding). Context caching at 0.1x input, $0.075 per million on 3.8 Flash until 31 December, and implicit caching on `gemini-4-argon`, which doesn't support explicit caches (15). 1,048,576-token context on the default and flagship models (15). Batch half price (10). Official SDKs for Python and JavaScript (10). Documented error codes with backoff guidance (10 of 15, because 400, 402 and 403 are flagged as not retryable but recovery advice per code sits on a separate page we only skimmed).", "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": 93, "b": 58 } }, { "by": 29, "category": "security", "leads": "hugging-face-inference-providers", "name": "Security \u0026 auth", "reasons": { "a": "Model reading. Keys live in a Cloud project. Since 28 May 2026 new keys are authorisation keys bound to a service account and restricted to the Gemini API, keys can be limited by IP or origin, unrestricted standard keys are rejected, and the docs give a leak checklist, per the API key page re-read on 1 November. No permission scopes, so 25 of 30, less 10 because the API reads a token from the URL. The Discovery document (revision 20261101) lists `access_token`, `oauth_token` and `key` as query parameters, and on 1 November a generateContent request with no credential answered 403 'Method doesn't allow unregistered callers' while one with a made-up `?access_token=` answered 401 'Request had invalid authentication credentials' (ACCESS_TOKEN_TYPE_UNSUPPORTED), the deduction Google APIs took on 17 October and 1 November and Gemini Embedding and Gemini Live carry (15 of 30). Terms (effective 23 March 2026, re-read 1 November) say free-tier prompts and responses are used to improve Google products and human reviewers may read them, paid tier isn't used (10 of 20). Abuse monitoring on paid services is kept 'a limited period' with no number, grounding data 30 days, and since 26 October new paid projects store Generate Content requests by default unless `store=false`. No zero-retention route on this API was found (5 of 15). Request logs in AI Studio for billed projects (15). security.txt on google.com valid to 2030-04-01 with a vulnerability reward programme, re-read on 1 November. No certification naming the Developer API found, the reading Gemini Embedding takes (5 of 20).", "b": "Model reading. Fine-grained user access tokens that can be limited to the `Make calls to Inference Providers` permission, rotated and revoked, plus a public revocation endpoint for leaked tokens, and organisation approval of fine-grained tokens on paid plans (30). Hugging Face says it doesn't store user data for training, but data handling past the router follows each provider's policy, with no per-request filter to exclude providers that train or retain (12 of 20). Request bodies and responses aren't stored when routed and debug logs are kept up to 30 days without user data or tokens, with provider retention outside that statement (10 of 15). Usage by model and provider in account settings, an Enterprise usage API, and Team and Enterprise admins can disable providers and set a spending limit (13 of 15). SOC 2 Type 2 for the Hub, of which the docs say Inference Providers is a feature, and security.txt valid to 2030 per the Inference Endpoints check; no bug bounty found (14 of 20)." }, "scores": { "a": 50, "b": 79 } }, { "by": 23, "category": "schema", "leads": "gemini-api", "name": "Schema \u0026 documentation", "reasons": { "a": "A keyless Discovery document at generativelanguage.googleapis.com/$discovery/rest?version=v1beta (revision 20261101, re-read on 1 November) types 86 methods and 225 schemas for GenerateContent, files, batches, caching and models, but not the Interactions API the guides now lead with (20 of 25). llms.txt at ai.google.dev/gemini-api/docs/llms.txt, with Markdown twins of each page (10). Reference not read in full, and the changelog and latest-model guide name the recommended models (15 of 20). Structured output accepts JSON Schema with enums, `minimum`, `maximum`, `prefixItems` and `$ref`, but the server ignores `minLength`, `maxLength`, `minProperties`, `maxProperties` and `uniqueItems`, per the structured output page re-read on 1 November (10 of 15). Examples on every guide and an API errors page with HTTP, blocked and content codes (15). Dated changelog and model versions (15).", "b": "No OpenAPI document for the router (openapi.json paths answer 404). The task reference pages are generated from typed JSON Schema specs in huggingface.js, and the router's /v1/models gives a machine-readable catalogue, so 12 of 25. llms.txt for the Inference Providers docs and a Markdown twin of every page via `.md` (10). Guides say what each task and policy is for, with a quick setup page for coding agents (14 of 20). Parameter tables with types for chat completion, though `response_format` and `tool_choice` show as unknown types (9 of 15). Examples in Python, JavaScript and curl on every task page, but no documented error responses for the router (9 of 15). No changelog of its own; the Hub changelog doesn't cover it and dated changes are only in the hub-docs history (8 of 15)." }, "scores": { "a": 85, "b": 62 } }, { "by": 20, "category": "reliability", "leads": "gemini-api", "name": "Reliability", "reasons": { "a": "Status page at aistudio.google.com/status (robots.txt allows it), but on 1 November it still returned a script shell titled Google AI Studio with no components or history, so 10 of 20, and 5 of 30 for the incident line with no readable record, as the Gemini Live and Gemini Embedding listings read the same page. Google Cloud's status dashboard covers Vertex AI products, not this endpoint. Per-model RPM and TPM live in AI Studio. The public rate-limits page, re-read on 1 November, publishes tier rules, spend-based limits of $10, $50 and $200 per 10 minutes for Tiers 1 to 3, and batch queue limits (5 of 15). The troubleshooting page, re-read on 1 November, gives exponential backoff with jitter for 429 RESOURCE_EXHAUSTED and 503 UNAVAILABLE, says to retry 429, 408 and 5xx and not 400, 402 or 403, and says the Python SDK retries transient errors up to four times (15). No SLA found for the Developer API (0). The flagship `gemini-4-argon` went GA on 13 October 2026 and the default 3.8 Flash is GA, and the Interactions API the guides lead with has been Generally Available since June 2026. The listing's example and the SDKs default to the `v1beta` path, which Google labels beta, but the API versions page, read on 1 November, says the stable `v1` path carries the Interactions API, generateContent, function calling and structured output and supports every model, so the surface is available as GA, the reading Gemini Embedding takes on the same endpoint. Gemini Live keeps a deduction because the Live API runs on `v1beta` only (10). Before 13 October the only Pro model was `gemini-3.1-pro-preview` (5 of 10).", "b": "Hosted lines. status.huggingface.co is a Better Stack page with 90-day component history for the Hub, Inference Endpoints, Spaces, the CDNs and Jobs, but no component for Inference Providers or the router (10 of 20). With no component, there is no readable incident history for the surface agents call, and the feed's 23 items from 10 June to 7 October 2026 don't name it (5). No rate limits for the router were found; the Hub rate-limits page gives numbers for Hub APIs, resolvers and pages only (0). No 429 or overload guidance for the router was found (0). No SLA found (0). Chat completions on the router is generally available; the Responses API is labelled beta (10). Routing between providers with `:fastest` or `:cheapest` softens a single provider's outage, which this checklist doesn't score." }, "scores": { "a": 45, "b": 25 } }, { "by": 20, "category": "payments", "leads": "gemini-api", "name": "Payments \u0026 pricing", "reasons": { "a": "No machine payment protocol (0). Per-token prices published without a login, re-read on 1 November (20). Free tier on 3.8 Flash, 3.6 Flash, 3.5 Flash-Lite and 3.1 Flash-Lite, not on `gemini-4-argon` or 3.1 Pro preview, and the rate-limits page needs only an active project for the free tier and a linked billing account from Tier 1, so the free tier needs no card (20). A Google account and AI Studio are needed for a key (0).", "b": "No x402, MPP or L402 (0). Per-token prices for every model and provider published without a login in the router's /v1/models and on model pages (20). No free tier since 7 October 2026, when free users lost their included monthly credits; PRO's $2.00 of credits needs a subscription (0). Sign-up, token creation and credit purchase are browser steps (0)." }, "scores": { "a": 40, "b": 20 } } ], "facts": [ { "a": "Model API", "b": "Model router", "name": "Kind" }, { "a": "Google", "b": "Hugging Face, Inc.", "name": "Vendor" }, { "a": "https://generativelanguage.googleapis.com/v1beta", "b": "https://router.huggingface.co/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Freemium", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0 (SDKs)", "b": "Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-30", "b": "2026-10-29", "name": "Last release" }, { "a": "2026-04-28", "b": "2022-09-15", "name": "Terms last updated" }, { "a": "2026-10-01", "b": "2023-03-28", "name": "Privacy policy last updated" }, { "a": "yes", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "yes", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "yes", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "yes", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "4k stars", "b": "483k npm/wk, 71.5M PyPI/wk", "name": "Popularity" }, { "a": "3.5/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Gemini Developer API scores 62.2 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 6 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth.", "question": "Which is better for AI agents, Gemini Developer API or Hugging Face Inference Providers?" }, { "answer": "Both need an API key.", "question": "Do Gemini Developer API and Hugging Face Inference Providers need an API key?" }, { "answer": "Yes. Gemini Developer API has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and Hugging Face Inference Providers at https://router.huggingface.co/v1.", "question": "Can an agent call Gemini Developer API and Hugging Face Inference Providers without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 45 against 25", "Schema \u0026 documentation, 85 against 62", "Agent ergonomics, 93 against 58", "Payments \u0026 pricing, 40 against 20" ], "also": [ "Free to start without a card" ], "goodFor": "Cheap, long-context Flash calls for prototypes, public data and agents that need to start without a card, and Gemini 4 Argon for long reasoning on the paid tier.", "slug": "gemini-api", "watchFor": "Free-tier prompts and responses improve Google products and may be read by human reviewers" }, { "aheadOn": [ "Security \u0026 auth, 79 against 50" ], "also": [ "No incidents deducted, where Gemini Developer 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": { "gemini-api": [ { "causes": [ "product", "evidence", "correction" ], "date": "2026-11-01", "delta": -3.3, "from": 65.5, "fromGrade": "B", "to": 62.2, "toGrade": "B" }, { "causes": [ "correction" ], "date": "2026-10-28", "delta": -0.1, "from": 65.6, "fromGrade": "B", "to": 65.5, "toGrade": "B" }, { "causes": [ "method" ], "date": "2026-10-28", "delta": 0.1, "from": 65.5, "fromGrade": "B", "to": 65.6, "toGrade": "B" } ], "hugging-face-inference-providers": null }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-gemini-api.json", "title": "Amazon Bedrock vs Gemini Developer API", "url": 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"https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router.json", "title": "Hugging Face Inference Providers vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-routerplus.json", "title": "Hugging Face Inference Providers vs RouterPlus", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-tencent-tokenhub.json", "title": "Hugging Face Inference Providers vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway.json", "title": "Hugging Face Inference Providers vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-nemotron-3-5-super-vl.json", "title": "Hugging Face Inference Providers vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference.json", "title": "Hugging Face Inference Providers vs Prism Inference", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference" } ], "panel": null, "scores": [ { "by": 20, "edge": "gemini-api", "gemini-api": 45, "hugging-face-inference-providers": 25, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 23, "edge": "gemini-api", "gemini-api": 85, "hugging-face-inference-providers": 62, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 35, "edge": "gemini-api", "gemini-api": 93, "hugging-face-inference-providers": 58, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "by": 29, "edge": "hugging-face-inference-providers", "gemini-api": 50, "hugging-face-inference-providers": 79, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "by": 20, "edge": "gemini-api", "gemini-api": 40, "hugging-face-inference-providers": 20, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 3, "edge": "gemini-api", "gemini-api": 83, "hugging-face-inference-providers": 80, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 1, "edge": "gemini-api", "gemini-api": 72, "hugging-face-inference-providers": 71, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Gemini Developer API scores 62.2 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 6 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "gemini-api": "Free tier on 3.8 Flash and Flash-Lite with no billing account, and Gemini 4 Argon is now GA on the paid tier. Free-tier prompts and responses improve Google products and may be read by human reviewers, and the API accepts an OAuth token in the URL query string.", "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/gemini-api-vs-hugging-face-inference-providers", "json": "https://www.anchorterminal.com/compare/gemini-api-vs-hugging-face-inference-providers.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/gemini-api-vs-hugging-face-inference-providers.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/gemini-api-vs-hugging-face-inference-providers.min.md" }, "markdown": "Gemini Developer API scores 62.2 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 6 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth. Both do llm inference.\n\n- Gemini Developer API: grade B, 62.2/100, rank #568 of 1510. Markdown https://www.anchorterminal.com/tools/gemini-api.md · JSON https://www.anchorterminal.com/api/v1/tools/gemini-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### Gemini Developer API (B)\n\nGood for: Cheap, long-context Flash calls for prototypes, public data and agents that need to start without a card, and Gemini 4 Argon for long reasoning on the paid tier.\n\nAhead on:\n- Reliability, 45 against 25\n- Schema \u0026 documentation, 85 against 62\n- Agent ergonomics, 93 against 58\n- Payments \u0026 pricing, 40 against 20\n\nAlso in its favour:\n- Free to start without a card\n\nWatch for: Free-tier prompts and responses improve Google products and may be read by human reviewers\n\n### Hugging Face Inference Providers (C)\n\nGood for: Agents and developers who want open-weight models from several hosts on one token and one bill, with a public price and capability list per provider.\n\nAhead on:\n- Security \u0026 auth, 79 against 50\n\nAlso in its favour:\n- No incidents deducted, where Gemini Developer 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### Agent ergonomics: Gemini Developer API +35\n\n- Gemini Developer API (93): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling documented, and `FunctionCallingConfig` mode `ANY` with `allowedFunctionNames` forces a call to a named tool, with a `VALIDATED` mode that checks calls by constrained decoding (20 of 20). The structured output page, re-read on 1 November, says output adheres to the supplied JSON Schema and is syntactically correct JSON, and names the keywords constrained decoding doesn't enforce, while asking callers to validate values (13 of 15; the 12 October note's 10 rested on the page promising no constrained decoding). Context caching at 0.1x input, $0.075 per million on 3.8 Flash until 31 December, and implicit caching on `gemini-4-argon`, which doesn't support explicit caches (15). 1,048,576-token context on the default and flagship models (15). Batch half price (10). Official SDKs for Python and JavaScript (10). Documented error codes with backoff guidance (10 of 15, because 400, 402 and 403 are flagged as not retryable but recovery advice per code sits on a separate page we only skimmed).\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### Security \u0026 auth: Hugging Face Inference Providers +29\n\n- Gemini Developer API (50): Model reading. Keys live in a Cloud project. Since 28 May 2026 new keys are authorisation keys bound to a service account and restricted to the Gemini API, keys can be limited by IP or origin, unrestricted standard keys are rejected, and the docs give a leak checklist, per the API key page re-read on 1 November. No permission scopes, so 25 of 30, less 10 because the API reads a token from the URL. The Discovery document (revision 20261101) lists `access_token`, `oauth_token` and `key` as query parameters, and on 1 November a generateContent request with no credential answered 403 'Method doesn't allow unregistered callers' while one with a made-up `?access_token=` answered 401 'Request had invalid authentication credentials' (ACCESS_TOKEN_TYPE_UNSUPPORTED), the deduction Google APIs took on 17 October and 1 November and Gemini Embedding and Gemini Live carry (15 of 30). Terms (effective 23 March 2026, re-read 1 November) say free-tier prompts and responses are used to improve Google products and human reviewers may read them, paid tier isn't used (10 of 20). Abuse monitoring on paid services is kept 'a limited period' with no number, grounding data 30 days, and since 26 October new paid projects store Generate Content requests by default unless `store=false`. No zero-retention route on this API was found (5 of 15). Request logs in AI Studio for billed projects (15). security.txt on google.com valid to 2030-04-01 with a vulnerability reward programme, re-read on 1 November. No certification naming the Developer API found, the reading Gemini Embedding takes (5 of 20).\n- Hugging Face Inference Providers (79): Model reading. Fine-grained user access tokens that can be limited to the `Make calls to Inference Providers` permission, rotated and revoked, plus a public revocation endpoint for leaked tokens, and organisation approval of fine-grained tokens on paid plans (30). Hugging Face says it doesn't store user data for training, but data handling past the router follows each provider's policy, with no per-request filter to exclude providers that train or retain (12 of 20). Request bodies and responses aren't stored when routed and debug logs are kept up to 30 days without user data or tokens, with provider retention outside that statement (10 of 15). Usage by model and provider in account settings, an Enterprise usage API, and Team and Enterprise admins can disable providers and set a spending limit (13 of 15). SOC 2 Type 2 for the Hub, of which the docs say Inference Providers is a feature, and security.txt valid to 2030 per the Inference Endpoints check; no bug bounty found (14 of 20).\n\n### Schema \u0026 documentation: Gemini Developer API +23\n\n- Gemini Developer API (85): A keyless Discovery document at generativelanguage.googleapis.com/$discovery/rest?version=v1beta (revision 20261101, re-read on 1 November) types 86 methods and 225 schemas for GenerateContent, files, batches, caching and models, but not the Interactions API the guides now lead with (20 of 25). llms.txt at ai.google.dev/gemini-api/docs/llms.txt, with Markdown twins of each page (10). Reference not read in full, and the changelog and latest-model guide name the recommended models (15 of 20). Structured output accepts JSON Schema with enums, `minimum`, `maximum`, `prefixItems` and `$ref`, but the server ignores `minLength`, `maxLength`, `minProperties`, `maxProperties` and `uniqueItems`, per the structured output page re-read on 1 November (10 of 15). Examples on every guide and an API errors page with HTTP, blocked and content codes (15). Dated changelog and model versions (15).\n- Hugging Face Inference Providers (62): No OpenAPI document for the router (openapi.json paths answer 404). The task reference pages are generated from typed JSON Schema specs in huggingface.js, and the router's /v1/models gives a machine-readable catalogue, so 12 of 25. llms.txt for the Inference Providers docs and a Markdown twin of every page via `.md` (10). Guides say what each task and policy is for, with a quick setup page for coding agents (14 of 20). Parameter tables with types for chat completion, though `response_format` and `tool_choice` show as unknown types (9 of 15). Examples in Python, JavaScript and curl on every task page, but no documented error responses for the router (9 of 15). No changelog of its own; the Hub changelog doesn't cover it and dated changes are only in the hub-docs history (8 of 15).\n\n### Reliability: Gemini Developer API +20\n\n- Gemini Developer API (45): Status page at aistudio.google.com/status (robots.txt allows it), but on 1 November it still returned a script shell titled Google AI Studio with no components or history, so 10 of 20, and 5 of 30 for the incident line with no readable record, as the Gemini Live and Gemini Embedding listings read the same page. Google Cloud's status dashboard covers Vertex AI products, not this endpoint. Per-model RPM and TPM live in AI Studio. The public rate-limits page, re-read on 1 November, publishes tier rules, spend-based limits of $10, $50 and $200 per 10 minutes for Tiers 1 to 3, and batch queue limits (5 of 15). The troubleshooting page, re-read on 1 November, gives exponential backoff with jitter for 429 RESOURCE_EXHAUSTED and 503 UNAVAILABLE, says to retry 429, 408 and 5xx and not 400, 402 or 403, and says the Python SDK retries transient errors up to four times (15). No SLA found for the Developer API (0). The flagship `gemini-4-argon` went GA on 13 October 2026 and the default 3.8 Flash is GA, and the Interactions API the guides lead with has been Generally Available since June 2026. The listing's example and the SDKs default to the `v1beta` path, which Google labels beta, but the API versions page, read on 1 November, says the stable `v1` path carries the Interactions API, generateContent, function calling and structured output and supports every model, so the surface is available as GA, the reading Gemini Embedding takes on the same endpoint. Gemini Live keeps a deduction because the Live API runs on `v1beta` only (10). Before 13 October the only Pro model was `gemini-3.1-pro-preview` (5 of 10).\n- Hugging Face Inference Providers (25): Hosted lines. status.huggingface.co is a Better Stack page with 90-day component history for the Hub, Inference Endpoints, Spaces, the CDNs and Jobs, but no component for Inference Providers or the router (10 of 20). With no component, there is no readable incident history for the surface agents call, and the feed's 23 items from 10 June to 7 October 2026 don't name it (5). No rate limits for the router were found; the Hub rate-limits page gives numbers for Hub APIs, resolvers and pages only (0). No 429 or overload guidance for the router was found (0). No SLA found (0). Chat completions on the router is generally available; the Responses API is labelled beta (10). Routing between providers with `:fastest` or `:cheapest` softens a single provider's outage, which this checklist doesn't score.\n\n### Payments \u0026 pricing: Gemini Developer API +20\n\n- Gemini Developer API (40): No machine payment protocol (0). Per-token prices published without a login, re-read on 1 November (20). Free tier on 3.8 Flash, 3.6 Flash, 3.5 Flash-Lite and 3.1 Flash-Lite, not on `gemini-4-argon` or 3.1 Pro preview, and the rate-limits page needs only an active project for the free tier and a linked billing account from Tier 1, so the free tier needs no card (20). A Google account and AI Studio are needed for a key (0).\n- Hugging Face Inference Providers (20): No x402, MPP or L402 (0). Per-token prices for every model and provider published without a login in the router's /v1/models and on model pages (20). No free tier since 7 October 2026, when free users lost their included monthly credits; PRO's $2.00 of credits needs a subscription (0). Sign-up, token creation and credit purchase are browser steps (0).\n\n## Score by category\n\n| Category | Weight | Gemini Developer API | Hugging Face Inference Providers | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 45 | 25 | Gemini Developer API +20 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 85 | 62 | Gemini Developer API +23 |\n| Agent ergonomics | 13% (16.2 this run) | 93 | 58 | Gemini Developer API +35 |\n| Security \u0026 auth | 14% (17.5 this run) | 50 | 79 | Hugging Face Inference Providers +29 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 20 | Gemini Developer API +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 80 | Gemini Developer API +3 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 72 | 71 | Gemini Developer API +1 |\n| Negative events | ≤15 | -3 | 0 | |\n| **Total** | | **62.2 · B** | **54 · C** | |\n\n## Facts side by side\n\n| Fact | Gemini Developer API | Hugging Face Inference Providers |\n| --- | --- | --- |\n| Kind | Model API | Model router |\n| Vendor | Google | Hugging Face, Inc. |\n| Hosted endpoint | `https://generativelanguage.googleapis.com/v1beta` | `https://router.huggingface.co/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Freemium | Pay per use |\n| x402 | no | no |\n| Licence | Apache-2.0 (SDKs) | Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-30 | 2026-10-29 |\n| Terms last updated | 2026-04-28 | 2022-09-15 |\n| Privacy policy last updated | 2026-10-01 | 2023-03-28 |\n| Customer content may train models | yes | not found in the text |\n| Terms restrict automated access | yes | not found in the text |\n| Terms restrict benchmarking | yes | not found in the text |\n| Terms or service can change without notice | not found in the text | yes |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Popularity | 4k stars | 483k npm/wk, 71.5M PyPI/wk |\n| Agent reviews | 3.5/5 (2) | none |\n\n## How the scores have moved\n\n### Gemini Developer API\n\n- -3.3 on 1 November 2026: product, new evidence, correction\n- -0.1 on 28 October 2026: correction\n- +0.1 on 28 October 2026: checklist\n\n### Hugging Face Inference Providers\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Gemini Developer API.** Free tier on 3.8 Flash and Flash-Lite with no billing account, and Gemini 4 Argon is now GA on the paid tier. Free-tier prompts and responses improve Google products and may be read by human reviewers, and the API accepts an OAuth token in the URL query string.\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### Gemini Developer API\n\n1. Never send customer data through a free-tier key. Link billing first\n2. Send keys in the `x-goog-api-key` header, never as `key` or `access_token` in the URL\n3. Back off exponentially on 429 RESOURCE_EXHAUSTED and 503, and don't retry 400, 402 or 403\n4. Remove temperature, top_p and top_k. Gemini 4 and 3.6+ ignore them and a future release returns 400\n5. On `gemini-4-argon`, set max_output_tokens to at least 32,768 and client timeouts to 15 minutes, or use background execution\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, Gemini Developer API or Hugging Face Inference Providers?\n\nGemini Developer API scores 62.2 (B) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 6 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth.\n\n### Do Gemini Developer API and Hugging Face Inference Providers need an API key?\n\nBoth need an API key.\n\n### Can an agent call Gemini Developer API and Hugging Face Inference Providers without installing anything?\n\nYes. Gemini Developer API has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta 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/gemini-api-vs-hugging-face-inference-providers.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemini-api-vs-hugging-face-inference-providers.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"gemini-api\", \"b\": \"hugging-face-inference-providers\"}`. 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Developer scores 62.2 (B) to Hugging Face Inference Providers's 54 (C) for llm inference. 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