{ "data": { "a": { "slug": "hugging-face-inference-providers", "name": "Hugging Face Inference Providers", "vendor": "Hugging Face, Inc.", "vendorUrl": "https://huggingface.co", "kind": "router", "category": "inference", "summary": "Hugging Face's serverless router that sends model calls to partner inference providers such as Groq, Cerebras, Together and Fireworks through one Hugging Face token, with an OpenAI-compatible API at router.huggingface.co/v1 and Python and JavaScript clients.", "url": "https://www.anchorterminal.com/tools/hugging-face-inference-providers", "markdownUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-providers.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-providers.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-providers.json", "dns": "hugging-face-inference-providers.grade.anchorterminal.com", "repo": "https://github.com/huggingface/huggingface_hub", "license": "Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT", "transports": [ "http" ], "remoteUrl": "https://router.huggingface.co/v1", "packages": [ { "registry": "pypi", "name": "huggingface_hub" }, { "registry": "npm", "name": "@huggingface/inference" } ], "auth": "api-key", "authNotes": "Hugging Face user access token sent as `Authorization: Bearer $HF_TOKEN`. The docs recommend a fine-grained token with only the `Make calls to Inference Providers` permission. Tokens are made in account settings in a browser, can be rotated and revoked, and a leaked token can be revoked by anyone through `POST /api/credentials/revoke`. A provider's own key can be stored in settings instead, and Hugging Face swaps it in when routing.", "pricing": "usage", "pricingNotes": "Pay as you go at each provider's own per-token rates with no Hugging Face markup, drawn from prepaid credits on the Hugging Face account. Free users get no included credits since 7 October 2026 and must buy credits. PRO users and Team or Enterprise seats get $2.00 a month of compute credits. Requests with a custom provider key are billed by the provider (https://huggingface.co/docs/inference-providers/pricing, checked 2026-11-06).", "priceSummary": "$2 / mo", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the Inference Providers docs, llms.txt or the router's model list. Calls draw on prepaid Hugging Face credits bought in the account's billing settings (checked 2026-11-06).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 483470, "pypiWeekly": 71518708, "asOf": "2026-11-06" }, "docsUrl": "https://huggingface.co/docs/inference-providers/index", "llmsTxt": "https://huggingface.co/docs/inference-providers/llms.txt", "capabilities": [ "inference.router", "inference.open-weights", "inference.llm" ], "tags": [ "hosted", "router", "usage", "prepaid", "openai-compatible", "llms-txt", "python", "javascript", "status-page", "soc2" ], "lastRelease": "2026-10-29", "graded": true, "anchor": { "graded": true, "score": 54, "grade": "C", "agentReady": false, "rank": 926, "ranked": true, "rankOf": 1510, "categoryRank": 28, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 58, "maintenance": 80, "payments": 20, "reliability": 25, "schema": 62, "security": 79, "transparency": 71 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "One Hugging Face token reaches open models on 18 partner providers at the providers' own prices, with a public model list that shows each provider's price, context and tool support. Router rate limits, error responses and its own status component were not found in the reviewed documentation, and free accounts have had no included credits since 7 October 2026.", "bestFor": "Agents and developers who want open-weight models from several hosts on one token and one bill, with a public price and capability list per provider.", "strengths": [ "router.huggingface.co/v1/models lists every routed model with each provider's price, context, tool support, latency and throughput, without a token", "Provider choice by suffix (`:fastest`, `:cheapest`, `:preferred` or a provider name) on an OpenAI-compatible endpoint", "Fine-grained tokens can be limited to the `Make calls to Inference Providers` permission and revoked at once", "No markup on provider rates, and request bodies and responses are not stored when routed", "Official clients in Python (`huggingface_hub` 2.4.0, 29 October 2026) and JavaScript (`@huggingface/inference` 4.13.32)" ], "weaknesses": [ "No rate limits, 429 behaviour or error responses documented for the router", "status.huggingface.co has no component for Inference Providers or the router", "Free users have had no included credits since 7 October 2026, and buying credits needs a person in the account settings", "No OpenAPI document for the router, no batch API, and the Responses API is beta", "Data handling past the router depends on each provider's own policy" ], "agentNotes": [ "Read https://router.huggingface.co/v1/models before choosing a provider; it shows price, context and `supports_tools` per provider", "Pin a provider with `model:\u003cprovider\u003e` when tool calling or structured output matters, since support varies by provider", "Use a fine-grained token with only the Inference Providers permission, and send `X-HF-Bill-To` to bill an organisation", "Back off on 429 without assuming a Retry-After header, since none is documented for the router" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 54 } ], "editorialScores": { "ergonomics": 58, "maintenance": 80, "payments": 20, "reliability": 25, "schema": 62, "security": 79, "transparency": 58 }, "provenanceScore": 84, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install huggingface_hub # or: pip install openai, with base_url https://router.huggingface.co/v1", "http": "curl https://router.huggingface.co/v1/chat/completions \\\n -H \"Authorization: Bearer $HF_TOKEN\" -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"openai/gpt-oss-120b:fastest\",\"messages\":[{\"role\":\"user\",\"content\":\"How many Gs in huggingface?\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.router", "tool": "https://letme.dev/hugging-face-inference-providers" }, "sameCompany": [ "hugging-face-inference-endpoints", "smolagents", "carbon-x", "smollm3-3b" ], "area": "models", "unitPrices": [ { "item": "openai/gpt-oss-120b input, cheapest provider listed (DeepInfra)", "unit": "1m-tokens", "usd": 0.037, "note": "Output $0.17. Groq lists $0.15/$0.75 and Cerebras $0.35/$0.75, per the router's model list of 6 November 2026" }, { "item": "PRO monthly compute credits", "unit": "month", "usd": 2, "note": "Also $2.00 per seat for Team and Enterprise organisations" } ], "provenance": { "legalEntity": "Hugging Face, Inc.", "domain": "huggingface.co", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://huggingface.co/terms-of-service", "privacy": "https://huggingface.co/privacy", "statusPage": "https://status.huggingface.co", "changelog": "https://huggingface.co/changelog", "securityTxt": "valid", "checked": "2026-11-06", "notes": [ "The Terms of Service (effective 15 September 2022) name Hugging Face, Inc. and define Inference Providers as a hosted service for running inference through an API on Hub models.", "huggingface.co/robots.txt and router.huggingface.co/robots.txt allow all. status.huggingface.co serves an empty robots.txt.", "status.huggingface.co is a Better Stack page with components for the Hub, git hosting, Inference Endpoints, Spaces, the CDNs and Jobs, and none for Inference Providers or the router.", "huggingface.co/changelog covers the whole Hub and had no Inference Providers entry on its first page on 6 November 2026. Dated changes to the docs are in the hub-docs repository's history.", "security.txt, privacy policy and subprocessor list as recorded on the Inference Endpoints listing (checked 8 October and 2 November 2026); not re-read for this listing." ], "score": 84 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-providers.json", "live": { "slug": "hugging-face-inference-providers", "probe": { "target": "https://router.huggingface.co/v1", "method": "get", "lastAt": "2026-11-07T19:22:12.474650545Z", "lastOk": true, "lastStatus": 404, "lastMs": 145, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 109, "p95ms24h": 196, "samples24h": 210, "samples30d": 210, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 197, "ok": 197 } ] }, "vendorStatus": { "page": "https://status.huggingface.co", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-07T04:47:55.542550557Z" }, "versions": [ { "registry": "github", "name": "huggingface/huggingface_hub", "version": "v2.4.0", "released": "2026-10-29", "seenAt": "2026-11-06T23:33:27.894225298Z" }, { "registry": "npm", "name": "@huggingface/inference", "version": "4.13.32", "seenAt": "2026-11-06T23:33:27.102558197Z" }, { "registry": "pypi", "name": "huggingface_hub", "version": "2.4.0", "released": "2026-10-29", "seenAt": "2026-11-06T23:33:26.910773744Z" } ], "githubStars": 4034, "npmWeekly": 483470, "pypiWeekly": 71518708, "securityTxt": { "url": "https://huggingface.co/.well-known/security.txt", "state": "valid", "expires": "2030-07-01T08:42:00.000Z", "checkedAt": "2026-11-07T16:00:00.493446773Z" }, "llmsTxt": { "url": "https://huggingface.co/docs/inference-providers/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:32:44.910268229Z" }, "pages": [ { "url": "https://huggingface.co/docs/inference-providers/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-11-07T14:11:37.221950067Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "2cbe821ca9d2" } ], "updatedAt": "2026-11-07T19:22:12.474650545Z" } }, "answer": "MiniMax API scores 55.3 (C) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 3 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth, maintenance \u0026 community and transparency \u0026 trust.", "b": { "slug": "minimax-api", "name": "MiniMax API", "vendor": "MiniMax", "vendorUrl": "https://www.minimax.io", "kind": "model", "category": "inference", "summary": "MiniMax's API for its M-series text models, M3.1 Flash and M3, in the Anthropic Messages, OpenAI Chat Completions and OpenAI Responses formats, with 1M-token context and automatic prompt caching.", "url": "https://www.anchorterminal.com/tools/minimax-api", "markdownUrl": "https://www.anchorterminal.com/tools/minimax-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/minimax-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/minimax-api.json", "dns": "minimax-api.grade.anchorterminal.com", "repo": "https://github.com/MiniMax-AI/MiniMax-M3", "license": "Proprietary API under MiniMax's platform terms. MiniMax-M3 and MiniMax-M3.1-Flash weights are on Hugging Face under the MiniMax community licence", "transports": [ "http" ], "remoteUrl": "https://api.minimax.io", "packages": [], "auth": "api-key", "authNotes": "Bearer key from platform.minimax.io, charged to a prepaid balance. M Plan subscribers get a separate Subscription Key that draws on the plan's usage windows, and the two kinds of key can't be swapped. Mainland China accounts use api.minimaxi.com with a separate key. MiniMax says it may disable a key that leaks publicly.", "pricing": "usage", "pricingNotes": "Prepaid balance, pay as you go. MiniMax-M3.1-Flash is $0.15 per million input tokens, $0.60 per million output tokens and $0.015 per million cache-read tokens at any input length. MiniMax-M3 is $0.30 in and $1.20 out up to 512K input tokens and $0.60 and $2.40 above, with cache reads at $0.06 and $0.12, and a Priority tier at 1.5 times that M3.1 Flash doesn't take. Caching is automatic. The web_search server tool (beta) is $0.01 a request. M Plan subscriptions for coding tools are Go $22, Explore $55 and Build $132 a month, and annual billing pays for 10 months (https://platform.minimax.io/docs/pricing/overview, https://platform.minimax.io/docs/m-plan/monthly-offer, checked 19 October 2026).", "priceSummary": "from $0.15 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs, llms.txt or pricing page. Prepaid balance top-up or an M Plan subscription (checked 2026-10-19).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 493, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-19" }, "docsUrl": "https://platform.minimax.io/docs/guides/text-generation", "rateLimitsUrl": "https://platform.minimax.io/docs/guides/rate-limits", "llmsTxt": "https://platform.minimax.io/docs/llms.txt", "openapi": "https://platform.minimax.io/docs/api-reference/text/api/openapi-chat-anthropic.json", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "hosted", "model", "open-weights", "prepaid", "openapi", "llms-txt" ], "lastRelease": "2026-10-19", "graded": true, "anchor": { "graded": true, "score": 55.3, "grade": "C", "agentReady": false, "rank": 877, "ranked": true, "rankOf": 1510, "categoryRank": 26, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 59, "maintenance": 45, "payments": 20, "reliability": 75, "schema": 82, "security": 30, "transparency": 65 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-04" }, "negative": 0, "verdict": "M3.1 Flash costs $0.15 in and $0.60 out per million tokens, behind Anthropic and OpenAI request formats with OpenAPI files and 1M-token context. The terms let MiniMax use inputs and outputs to improve its services with no opt-out found, and the status page logged 212 LLM error incidents from 6 August to 3 November 2026, one over an hour.", "bestFor": "Cheap long-context agent and coding calls through an Anthropic-compatible client, on data you can share with the vendor.", "strengths": [ "M3.1 Flash at $0.15 in, $0.60 out and $0.015 for cache reads per million tokens, flat at any input length", "Anthropic Messages, OpenAI Chat Completions and OpenAI Responses formats, each with an OpenAPI 3.1 file", "1M-token context and up to 524,288 output tokens on M3.1 Flash and M3", "Automatic prompt caching and a token-count endpoint", "MiniMax-M3 and, since 23 October 2026, MiniMax-M3.1-Flash weights on Hugging Face under the MiniMax community licence" ], "weaknesses": [ "The terms let MiniMax use inputs and outputs to develop and improve its services, and no opt-out was found", "No free tier, SLA, batch API, JSON Schema output mode or security.txt", "212 'Elevated errors' incidents on the LLM component from 6 August to 3 November 2026, one of 65 minutes and the rest under an hour", "M2.5 and M2.7 retire on 18 November 2026, 30 days after new users lost them, and plan requests to them already go to M3.1 Flash", "The model list calls M2.5 and M2.7 retired while the notice on the same page gives 18 November 2026" ], "agentNotes": [ "Use the Anthropic-format base URL `https://api.minimax.io/anthropic` for tool calls. The OpenAI-format schema has no `tool_choice` or `response_format`", "Set `output_config.effort` (or `reasoning_effort`) below `max` for routine calls. M3.1 Flash defaults to max, can't turn thinking off, and counts thinking against `max_tokens`", "Don't rely on `stop_sequences` or `top_k`. The Anthropic-format endpoint ignores them", "Back off on 429, 529 and the retry-later codes (1002, 2064) yourself. No Retry-After header is documented", "Use a pay-as-you-go key for production. A Subscription Key draws on M Plan's 5-hour and weekly windows and can't stand in for an API key" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 2.8, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 55.3 } ], "editorialScores": { "ergonomics": 59, "maintenance": 45, "payments": 20, "reliability": 75, "schema": 82, "security": 30, "transparency": 47 }, "provenanceScore": 82, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-10-28", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl https://api.minimax.io/anthropic/v1/messages \\\n -H \"Authorization: Bearer $MINIMAX_API_KEY\" -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"MiniMax-M3.1-Flash\",\"output_config\":{\"effort\":\"low\"},\"max_tokens\":4096,\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/minimax-api" }, "sameCompany": [ "minimax-video", "minimax-stt", "minimax-speech", "minimax-voice-cloning", "minimax-code", "minimax-m2-5", "minimax-m2-7", "minimax-m3-1-flash" ], "area": "models", "unitPrices": [ { "item": "web_search server tool (beta)", "unit": "1k-requests", "usd": 10 }, { "item": "M Plan Go", "unit": "month", "usd": 22, "note": "M3.1 Flash, image and audio, no video. Annual billing pays for 10 months" }, { "item": "M Plan Explore", "unit": "month", "usd": 55, "note": "3 times Go's usage, adds H3 video" }, { "item": "M Plan Build", "unit": "month", "usd": 132, "note": "7.5 times Go's usage, adds H3 video" } ], "provenance": { "legalEntity": "Nanonoble Pte. Ltd.", "domain": "minimax.io", "domainRegistered": "2021-03-27", "endpointOnVendorDomain": true, "terms": "https://platform.minimax.io/protocol/terms-of-service", "privacy": "https://platform.minimax.io/protocol/privacy-policy", "statusPage": "https://status.minimax.io", "changelog": "https://platform.minimax.io/docs/release-notes/models", "securityTxt": "none", "checked": "2026-11-04", "notes": [ "Nanonoble Pte. Ltd., 152 Beach Road, #14-02 Gateway East, Singapore, is named in the terms (effective 30 March 2026) and the privacy policy (updated 30 March 2026), read on 19 October and again on 4 November 2026 from the document text the pages carry for the browser. The policy reader recorded both pages as unreadable on 8 October, and that reading is kept.", "RDAP for minimax.io gives a registration date of 2021-03-27 and a transfer on 2025-01-31, as recorded on the MiniMax Video API listing.", "platform.minimax.io answers 404 for /.well-known/security.txt (4 November 2026). api.minimax.io answered 404 and www.minimax.io redirected it to the home page on 19 October.", "The API release notes page has no entry after 28 October 2025. Model releases are dated on a separate page, whose newest entry on 4 November 2026 is 19 October 2026." ], "score": 82 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/minimax-api.json", "live": { "slug": "minimax-api", "probe": { "target": "https://api.minimax.io", "method": "get", "lastAt": "2026-11-07T19:22:20.084767005Z", "lastOk": true, "lastStatus": 404, "lastMs": 504, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 273, "p95ms24h": 521, "samples24h": 238, "samples30d": 4716, "days": [ { "date": "2026-10-19", "probes": 93, "ok": 93 }, { "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.minimax.io", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-07T19:22:27.843622669Z" }, "githubStars": 500, "securityTxt": { "url": "https://minimax.io/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:00:57.120551174Z" }, "llmsTxt": { "url": "https://platform.minimax.io/docs/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:33:02.70243541Z" }, "domain": { "domain": "minimax.io", "checkedAt": "2026-11-01T14:11:19.440143188Z" }, "pages": [ { "url": "https://platform.minimax.io/docs/faq/models", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:16:45.419468064Z", "changedAt": "2026-11-06T13:38:25.889680746Z", "fingerprint": "8abebc4199ab" }, { "url": "https://platform.minimax.io/docs/release-notes/models", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:16:51.927185731Z", "changedAt": "2026-11-05T12:39:38.489181558Z", "fingerprint": "3b7661f72594" }, { "url": "https://platform.minimax.io/docs/pricing/overview", "kind": "pricing", "status": 200, "checkedAt": "2026-11-07T14:16:47.780533353Z", "changedAt": "2026-11-06T13:38:28.215329328Z", "fingerprint": "cfd940115e2f" }, { "url": "https://platform.minimax.io/protocol/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:16:53.708283926Z", "changedAt": "2026-10-31T06:18:23.585835081Z", "fingerprint": "1ae59257a3a9" }, { "url": "https://platform.minimax.io/protocol/terms-of-service", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:16:57.419839523Z", "changedAt": "2026-10-31T06:18:25.544630345Z", "fingerprint": "f98c6c8b7950" } ], "github": { "repo": "minimax-ai/minimax-m3", "checkedAt": "2026-11-02T08:26:01.986494652Z", "stars": 498, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-26T07:05:04Z", "openIssues": 29, "openPRs": 0, "issuesOpened90d": 8, "issuesClosed90d": 0, "prsMerged90d": 1, "replies": { "sampled": 25, "unanswered": 23, "medianDays": 8.8 } }, "updatedAt": "2026-11-07T19:22:20.084767005Z" } }, "edges": [ { "by": 50, "category": "reliability", "leads": "minimax-api", "name": "Reliability", "reasons": { "a": "Hosted lines. status.huggingface.co is a Better Stack page with 90-day component history for the Hub, Inference Endpoints, Spaces, the CDNs and Jobs, but no component for Inference Providers or the router (10 of 20). With no component, there is no readable incident history for the surface agents call, and the feed's 23 items from 10 June to 7 October 2026 don't name it (5). No rate limits for the router were found; the Hub rate-limits page gives numbers for Hub APIs, resolvers and pages only (0). No 429 or overload guidance for the router was found (0). No SLA found (0). Chat completions on the router is generally available; the Responses API is labelled beta (10). Routing between providers with `:fastest` or `:cheapest` softens a single provider's outage, which this checklist doesn't score.", "b": "Atlassian Statuspage at status.minimax.io with Large Language Models, Text-to-Speech and Video Generation components (20). Its history pages, re-read on 4 November, now cover the whole 90 days from 6 August. They list 212 incidents on the LLM component, every one titled 'Elevated errors on Large Language Models (LLM)' and labelled major, and none states a full outage. The longest ran 65 minutes (01:15 to 02:20 UTC on 20 October, 'We are currently investigating this issue' and then resolved), and the rest closed within the hour. This run reads elevated errors with no fuller scope as partial, so minor only, frequent as they are (20). The rate-limits page publishes 200 requests and 10,000,000 tokens a minute for M3.1 Flash and M3 (15). The Anthropic-format OpenAPI file documents 429 for rate limits and 529 as an overload that can be retried, and the error-code page says to retry later on 1002, 2064 and other codes, with no Retry-After header or backoff schedule found (10). No SLA found (0). M3.1 Flash and M3 are generally available (10). Total 75." }, "scores": { "a": 25, "b": 75 } }, { "by": 49, "category": "security", "leads": "hugging-face-inference-providers", "name": "Security \u0026 auth", "reasons": { "a": "Model reading. Fine-grained user access tokens that can be limited to the `Make calls to Inference Providers` permission, rotated and revoked, plus a public revocation endpoint for leaked tokens, and organisation approval of fine-grained tokens on paid plans (30). Hugging Face says it doesn't store user data for training, but data handling past the router follows each provider's policy, with no per-request filter to exclude providers that train or retain (12 of 20). Request bodies and responses aren't stored when routed and debug logs are kept up to 30 days without user data or tokens, with provider retention outside that statement (10 of 15). Usage by model and provider in account settings, an Enterprise usage API, and Team and Enterprise admins can disable providers and set a spending limit (13 of 15). SOC 2 Type 2 for the Hub, of which the docs say Inference Providers is a feature, and security.txt valid to 2030 per the Inference Endpoints check; no bug bounty found (14 of 20).", "b": "Model reading (credential, training, retention, operator visibility, programme). One bearer key per account on the pay-as-you-go side and a separate Subscription Key for M Plan, with no scopes found. MiniMax says it may disable keys that leak publicly (20 of 30). The terms, effective 30 March 2026 and unchanged on 4 November, say MiniMax may use input and generated content to provide, maintain, develop and improve its services, and no opt-out was found. The privacy policy says only that personal data isn't used for training to profile or target consumers (0 of 20). Data is kept as long as necessary for its purpose, with no period stated and no zero-retention route (5 of 15). A usage page and balance alerts, no audit log found (5 of 15). No security.txt on platform.minimax.io (404 again on 4 November) or api.minimax.io (per the 19 October check), and no bug bounty or certification found (0 of 20). Total 30." }, "scores": { "a": 79, "b": 30 } }, { "by": 35, "category": "maintenance", "leads": "hugging-face-inference-providers", "name": "Maintenance \u0026 community", "reasons": { "a": "Model reading. huggingface_hub 2.4.0 tagged on 29 October 2026 and the Inference Providers docs updated daily by an automated job, last on 6 November (30). huggingface_hub 2.2.0, 2.3.0 and 2.4.0 and @huggingface/inference 4.13.28 to 4.13.32 in the 90 days (20). No dedicated changelog; the Hub has a forum and Discord, and GitHub issue replies were not read (8 of 15). Current official SDKs in Python and JavaScript (15). The Python client supports Python 3.10 and later, per the Inference Endpoints check; CI not read (7 of 10).", "b": "Model reading. MiniMax-M3.1-Flash shipped on 19 October 2026, dated on the model release page, which has no newer entry on 4 November (16 days, 30). No stated notice policy. The M2.5 and M2.7 families closed to new users on 19 October and retire on 18 November, 30 days later, and from 19 October M Plan and Token Plan requests to them are served by M3.1 Flash under the old names. We couldn't find when that notice was first posted, and the page carries the same notice on 4 November (3 of 12). Churn is high. M2.5 (February 2026) and M2.7 (March 2026) retire within nine months of release, M2.1 and M2 are already retired, and the model list still calls M2.5 and M2.7 retired on 4 November while the notice on the same page gives 18 November (2 of 8). A dated release page, support email addresses on the contact and model pages, a Discord server and GitHub issues on the model repositories. We didn't test whether they answer (10 of 15). No official SDK (0 of 15, 0 of 10). Total 45." }, "scores": { "a": 80, "b": 45 } }, { "by": 20, "category": "schema", "leads": "minimax-api", "name": "Schema \u0026 documentation", "reasons": { "a": "No OpenAPI document for the router (openapi.json paths answer 404). The task reference pages are generated from typed JSON Schema specs in huggingface.js, and the router's /v1/models gives a machine-readable catalogue, so 12 of 25. llms.txt for the Inference Providers docs and a Markdown twin of every page via `.md` (10). Guides say what each task and policy is for, with a quick setup page for coding agents (14 of 20). Parameter tables with types for chat completion, though `response_format` and `tool_choice` show as unknown types (9 of 15). Examples in Python, JavaScript and curl on every task page, but no documented error responses for the router (9 of 15). No changelog of its own; the Hub changelog doesn't cover it and dated changes are only in the hub-docs history (8 of 15).", "b": "OpenAPI 3.1 files for the Anthropic Messages, OpenAI Chat Completions and OpenAI Responses endpoints, each listing MiniMax-M3.1-Flash and MiniMax-M3 (25). llms.txt indexes the docs, and each page is served as Markdown (10). Field descriptions say which model each setting applies to, such as `service_tier` not being supported on M3.1 Flash and `thinking: disabled` returning 400 there, and a compatibility table marks `top_k`, `stop_sequences`, `mcp_servers` and `container` as ignored (15 of 20). Enums for model, `effort`, `service_tier` and thinking type, with required fields marked. The OpenAI-format schema has no `tool_choice` or `response_format` (11 of 15). The Anthropic-format file documents typed errors for 400, 401, 403, 404, 413, 429, 500 and 529 with example bodies, and a page lists 45 error codes with a fix for each (the 19 October note counted 23; 2069, model no longer available, is among them on 4 November), but the OpenAI and Responses files document only 200 (11 of 15). A dated model release page with the 19 October entry as its newest on 4 November, while the API release notes still stop at 28 October 2025 (10 of 15). Total 82." }, "scores": { "a": 62, "b": 82 } }, { "by": 6, "category": "transparency", "leads": "hugging-face-inference-providers", "name": "Transparency \u0026 trust", "reasons": { "a": "Closed service under Terms of Service that name Inference Providers, with an Apache-2.0 Python client and an MIT JavaScript client (20). The security page and the docs agree on no training, no stored bodies and 30-day logs, but the privacy policy dates from 28 March 2023 and each provider's own data policy governs the rest (18 of 30). No deprecation policy found. Provider support changes and the 7 October removal of free credits are dated only in the docs repository history (5 of 20). The privacy policy lists 11 subprocessors with countries per the Inference Endpoints check, and the docs name every provider a request can reach, though not where each runs (15 of 20).", "b": "Closed service with clear terms under Singapore law and SIAC arbitration. MiniMax-M3's weights, and since 23 October 2026 MiniMax-M3.1-Flash's, are on Hugging Face under the MiniMax community licence, which isn't an OSI licence and doesn't change the hosted service (15). The terms and privacy policy, both still dated 30 March 2026 on 4 November, agree on the contracting entity, that inputs and outputs are processed and may be used to improve services, and that data sits in a United States data centre, but give no retention period and no DPA was read (10 of 30). A dated retirement notice for M2.5 and M2.7 and a retired-models table, undercut by the table contradicting the notice and API release notes a year stale (12 of 20). Data location stated as the United States and an EU representative named, with third parties named only by category (10 of 20). MiniMax publishes an EU AI Act training-data summary for M3. Total 47." }, "scores": { "a": 71, "b": 65 } } ], "facts": [ { "a": "Model router", "b": "Model API", "name": "Kind" }, { "a": "Hugging Face, Inc.", "b": "MiniMax", "name": "Vendor" }, { "a": "https://router.huggingface.co/v1", "b": "https://api.minimax.io", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT", "b": "Proprietary API under MiniMax's platform terms. MiniMax-M3 and MiniMax-M3.1-Flash weights are on Hugging Face under the MiniMax community licence", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-29", "b": "2026-10-19", "name": "Last release" }, { "a": "2022-09-15", "b": "couldn't be read", "name": "Terms last updated" }, { "a": "2023-03-28", "b": "couldn't be read", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "couldn't be read", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "couldn't be read", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "couldn't be read", "name": "Terms restrict benchmarking" }, { "a": "yes", "b": "couldn't be read", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "couldn't be read", "name": "Arbitration or class-action waiver" }, { "a": "483k npm/wk, 71.5M PyPI/wk", "b": "493 stars", "name": "Popularity" }, { "a": "none", "b": "2.8/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "MiniMax API scores 55.3 (C) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 3 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth, maintenance \u0026 community and transparency \u0026 trust.", "question": "Which is better for AI agents, Hugging Face Inference Providers or MiniMax API?" }, { "answer": "Both need an API key.", "question": "Do Hugging Face Inference Providers and MiniMax API need an API key?" }, { "answer": "Yes. Hugging Face Inference Providers has a hosted endpoint at https://router.huggingface.co/v1 and MiniMax API at https://api.minimax.io.", "question": "Can an agent call Hugging Face Inference Providers and MiniMax API without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Security \u0026 auth, 79 against 30", "Maintenance \u0026 community, 80 against 45", "Transparency \u0026 trust, 71 against 65" ], "also": null, "goodFor": "Agents and developers who want open-weight models from several hosts on one token and one bill, with a public price and capability list per provider.", "slug": "hugging-face-inference-providers", "watchFor": "No rate limits, 429 behaviour or error responses documented for the router" }, { "aheadOn": [ "Reliability, 75 against 25", "Schema \u0026 documentation, 82 against 62" ], "also": null, "goodFor": "Cheap long-context agent and coding calls through an Anthropic-compatible client, on data you can share with the vendor.", "slug": "minimax-api", "watchFor": "The terms let MiniMax use inputs and outputs to develop and improve its services, and no opt-out was found" } ], "history": { "hugging-face-inference-providers": null, "minimax-api": [ { "causes": [ "method" ], "date": "2026-10-28", "delta": 0.1, "from": 55.2, "fromGrade": "C", "to": 55.3, "toGrade": "C" } ] }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers.json", "title": "Amazon Bedrock vs Hugging Face Inference Providers", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-minimax-api.json", "title": "Amazon Bedrock vs MiniMax API", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-hugging-face-inference-providers.json", 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(Grok)", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-hugging-face-inference-providers.json", "title": "Antseed vs Hugging Face Inference Providers", "url": "https://www.anchorterminal.com/compare/antseed-vs-hugging-face-inference-providers" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-hugging-face-inference-providers.json", "title": "Eden AI vs Hugging Face Inference Providers", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-hugging-face-inference-providers" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-litellm.json", "title": "Hugging Face Inference Providers vs LiteLLM", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-litellm" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openrouter.json", "title": "Hugging Face Inference Providers vs OpenRouter", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router.json", "title": "Hugging Face Inference Providers vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-routerplus.json", "title": "Hugging Face Inference Providers vs RouterPlus", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-tencent-tokenhub.json", "title": "Hugging Face Inference Providers vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway.json", "title": "Hugging Face Inference Providers vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-nemotron-3-5-super-vl.json", "title": "Hugging Face Inference Providers vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference.json", "title": "Hugging Face Inference Providers vs Prism Inference", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference" } ], "panel": null, "scores": [ { "by": 50, "edge": "minimax-api", "hugging-face-inference-providers": 25, "key": "reliability", "minimax-api": 75, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 20, "edge": "minimax-api", "hugging-face-inference-providers": 62, "key": "schema", "minimax-api": 82, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 1, "edge": "minimax-api", "hugging-face-inference-providers": 58, "key": "ergonomics", "minimax-api": 59, "name": "Agent ergonomics", "weight": 13 }, { "by": 49, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 79, "key": "security", "minimax-api": 30, "name": "Security \u0026 auth", "weight": 14 }, { "by": 0, "edge": "", "hugging-face-inference-providers": 20, "key": "payments", "minimax-api": 20, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 35, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 80, "key": "maintenance", "minimax-api": 45, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 6, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 71, "key": "transparency", "minimax-api": 65, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "MiniMax API scores 55.3 (C) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 3 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth, maintenance \u0026 community and transparency \u0026 trust. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "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.", "minimax-api": "M3.1 Flash costs $0.15 in and $0.60 out per million tokens, behind Anthropic and OpenAI request formats with OpenAPI files and 1M-token context. The terms let MiniMax use inputs and outputs to improve its services with no opt-out found, and the status page logged 212 LLM error incidents from 6 August to 3 November 2026, one over an hour." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-minimax-api", "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-minimax-api.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-minimax-api.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-minimax-api.min.md" }, "markdown": "MiniMax API scores 55.3 (C) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 3 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth, maintenance \u0026 community and transparency \u0026 trust. Both do llm inference.\n\n- 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- MiniMax API: grade C, 55.3/100, rank #877 of 1510. Markdown https://www.anchorterminal.com/tools/minimax-api.md · JSON https://www.anchorterminal.com/api/v1/tools/minimax-api.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 830 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Hugging Face Inference Providers (C)\n\nGood for: Agents and developers who want open-weight models from several hosts on one token and one bill, with a public price and capability list per provider.\n\nAhead on:\n- Security \u0026 auth, 79 against 30\n- Maintenance \u0026 community, 80 against 45\n- Transparency \u0026 trust, 71 against 65\n\nWatch for: No rate limits, 429 behaviour or error responses documented for the router\n\n### MiniMax API (C)\n\nGood for: Cheap long-context agent and coding calls through an Anthropic-compatible client, on data you can share with the vendor.\n\nAhead on:\n- Reliability, 75 against 25\n- Schema \u0026 documentation, 82 against 62\n\nWatch for: The terms let MiniMax use inputs and outputs to develop and improve its services, and no opt-out was found\n\n\n## Why the edge\n\n### Reliability: MiniMax API +50\n\n- Hugging Face Inference Providers (25): Hosted lines. status.huggingface.co is a Better Stack page with 90-day component history for the Hub, Inference Endpoints, Spaces, the CDNs and Jobs, but no component for Inference Providers or the router (10 of 20). With no component, there is no readable incident history for the surface agents call, and the feed's 23 items from 10 June to 7 October 2026 don't name it (5). No rate limits for the router were found; the Hub rate-limits page gives numbers for Hub APIs, resolvers and pages only (0). No 429 or overload guidance for the router was found (0). No SLA found (0). Chat completions on the router is generally available; the Responses API is labelled beta (10). Routing between providers with `:fastest` or `:cheapest` softens a single provider's outage, which this checklist doesn't score.\n- MiniMax API (75): Atlassian Statuspage at status.minimax.io with Large Language Models, Text-to-Speech and Video Generation components (20). Its history pages, re-read on 4 November, now cover the whole 90 days from 6 August. They list 212 incidents on the LLM component, every one titled 'Elevated errors on Large Language Models (LLM)' and labelled major, and none states a full outage. The longest ran 65 minutes (01:15 to 02:20 UTC on 20 October, 'We are currently investigating this issue' and then resolved), and the rest closed within the hour. This run reads elevated errors with no fuller scope as partial, so minor only, frequent as they are (20). The rate-limits page publishes 200 requests and 10,000,000 tokens a minute for M3.1 Flash and M3 (15). The Anthropic-format OpenAPI file documents 429 for rate limits and 529 as an overload that can be retried, and the error-code page says to retry later on 1002, 2064 and other codes, with no Retry-After header or backoff schedule found (10). No SLA found (0). M3.1 Flash and M3 are generally available (10). Total 75.\n\n### Security \u0026 auth: Hugging Face Inference Providers +49\n\n- Hugging Face Inference Providers (79): Model reading. Fine-grained user access tokens that can be limited to the `Make calls to Inference Providers` permission, rotated and revoked, plus a public revocation endpoint for leaked tokens, and organisation approval of fine-grained tokens on paid plans (30). Hugging Face says it doesn't store user data for training, but data handling past the router follows each provider's policy, with no per-request filter to exclude providers that train or retain (12 of 20). Request bodies and responses aren't stored when routed and debug logs are kept up to 30 days without user data or tokens, with provider retention outside that statement (10 of 15). Usage by model and provider in account settings, an Enterprise usage API, and Team and Enterprise admins can disable providers and set a spending limit (13 of 15). SOC 2 Type 2 for the Hub, of which the docs say Inference Providers is a feature, and security.txt valid to 2030 per the Inference Endpoints check; no bug bounty found (14 of 20).\n- MiniMax API (30): Model reading (credential, training, retention, operator visibility, programme). One bearer key per account on the pay-as-you-go side and a separate Subscription Key for M Plan, with no scopes found. MiniMax says it may disable keys that leak publicly (20 of 30). The terms, effective 30 March 2026 and unchanged on 4 November, say MiniMax may use input and generated content to provide, maintain, develop and improve its services, and no opt-out was found. The privacy policy says only that personal data isn't used for training to profile or target consumers (0 of 20). Data is kept as long as necessary for its purpose, with no period stated and no zero-retention route (5 of 15). A usage page and balance alerts, no audit log found (5 of 15). No security.txt on platform.minimax.io (404 again on 4 November) or api.minimax.io (per the 19 October check), and no bug bounty or certification found (0 of 20). Total 30.\n\n### Maintenance \u0026 community: Hugging Face Inference Providers +35\n\n- Hugging Face Inference Providers (80): Model reading. huggingface_hub 2.4.0 tagged on 29 October 2026 and the Inference Providers docs updated daily by an automated job, last on 6 November (30). huggingface_hub 2.2.0, 2.3.0 and 2.4.0 and @huggingface/inference 4.13.28 to 4.13.32 in the 90 days (20). No dedicated changelog; the Hub has a forum and Discord, and GitHub issue replies were not read (8 of 15). Current official SDKs in Python and JavaScript (15). The Python client supports Python 3.10 and later, per the Inference Endpoints check; CI not read (7 of 10).\n- MiniMax API (45): Model reading. MiniMax-M3.1-Flash shipped on 19 October 2026, dated on the model release page, which has no newer entry on 4 November (16 days, 30). No stated notice policy. The M2.5 and M2.7 families closed to new users on 19 October and retire on 18 November, 30 days later, and from 19 October M Plan and Token Plan requests to them are served by M3.1 Flash under the old names. We couldn't find when that notice was first posted, and the page carries the same notice on 4 November (3 of 12). Churn is high. M2.5 (February 2026) and M2.7 (March 2026) retire within nine months of release, M2.1 and M2 are already retired, and the model list still calls M2.5 and M2.7 retired on 4 November while the notice on the same page gives 18 November (2 of 8). A dated release page, support email addresses on the contact and model pages, a Discord server and GitHub issues on the model repositories. We didn't test whether they answer (10 of 15). No official SDK (0 of 15, 0 of 10). Total 45.\n\n### Schema \u0026 documentation: MiniMax API +20\n\n- Hugging Face Inference Providers (62): No OpenAPI document for the router (openapi.json paths answer 404). The task reference pages are generated from typed JSON Schema specs in huggingface.js, and the router's /v1/models gives a machine-readable catalogue, so 12 of 25. llms.txt for the Inference Providers docs and a Markdown twin of every page via `.md` (10). Guides say what each task and policy is for, with a quick setup page for coding agents (14 of 20). Parameter tables with types for chat completion, though `response_format` and `tool_choice` show as unknown types (9 of 15). Examples in Python, JavaScript and curl on every task page, but no documented error responses for the router (9 of 15). No changelog of its own; the Hub changelog doesn't cover it and dated changes are only in the hub-docs history (8 of 15).\n- MiniMax API (82): OpenAPI 3.1 files for the Anthropic Messages, OpenAI Chat Completions and OpenAI Responses endpoints, each listing MiniMax-M3.1-Flash and MiniMax-M3 (25). llms.txt indexes the docs, and each page is served as Markdown (10). Field descriptions say which model each setting applies to, such as `service_tier` not being supported on M3.1 Flash and `thinking: disabled` returning 400 there, and a compatibility table marks `top_k`, `stop_sequences`, `mcp_servers` and `container` as ignored (15 of 20). Enums for model, `effort`, `service_tier` and thinking type, with required fields marked. The OpenAI-format schema has no `tool_choice` or `response_format` (11 of 15). The Anthropic-format file documents typed errors for 400, 401, 403, 404, 413, 429, 500 and 529 with example bodies, and a page lists 45 error codes with a fix for each (the 19 October note counted 23; 2069, model no longer available, is among them on 4 November), but the OpenAI and Responses files document only 200 (11 of 15). A dated model release page with the 19 October entry as its newest on 4 November, while the API release notes still stop at 28 October 2025 (10 of 15). Total 82.\n\n### Transparency \u0026 trust: Hugging Face Inference Providers +6\n\n- Hugging Face Inference Providers (71): Closed service under Terms of Service that name Inference Providers, with an Apache-2.0 Python client and an MIT JavaScript client (20). The security page and the docs agree on no training, no stored bodies and 30-day logs, but the privacy policy dates from 28 March 2023 and each provider's own data policy governs the rest (18 of 30). No deprecation policy found. Provider support changes and the 7 October removal of free credits are dated only in the docs repository history (5 of 20). The privacy policy lists 11 subprocessors with countries per the Inference Endpoints check, and the docs name every provider a request can reach, though not where each runs (15 of 20).\n- MiniMax API (65): Closed service with clear terms under Singapore law and SIAC arbitration. MiniMax-M3's weights, and since 23 October 2026 MiniMax-M3.1-Flash's, are on Hugging Face under the MiniMax community licence, which isn't an OSI licence and doesn't change the hosted service (15). The terms and privacy policy, both still dated 30 March 2026 on 4 November, agree on the contracting entity, that inputs and outputs are processed and may be used to improve services, and that data sits in a United States data centre, but give no retention period and no DPA was read (10 of 30). A dated retirement notice for M2.5 and M2.7 and a retired-models table, undercut by the table contradicting the notice and API release notes a year stale (12 of 20). Data location stated as the United States and an EU representative named, with third parties named only by category (10 of 20). MiniMax publishes an EU AI Act training-data summary for M3. Total 47.\n\n## Score by category\n\n| Category | Weight | Hugging Face Inference Providers | MiniMax API | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 25 | 75 | MiniMax API +50 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 62 | 82 | MiniMax API +20 |\n| Agent ergonomics | 13% (16.2 this run) | 58 | 59 | MiniMax API +1 |\n| Security \u0026 auth | 14% (17.5 this run) | 79 | 30 | Hugging Face Inference Providers +49 |\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) | 80 | 45 | Hugging Face Inference Providers +35 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 71 | 65 | Hugging Face Inference Providers +6 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **54 · C** | **55.3 · C** | |\n\n## Facts side by side\n\n| Fact | Hugging Face Inference Providers | MiniMax API |\n| --- | --- | --- |\n| Kind | Model router | Model API |\n| Vendor | Hugging Face, Inc. | MiniMax |\n| Hosted endpoint | `https://router.huggingface.co/v1` | `https://api.minimax.io` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT | Proprietary API under MiniMax's platform terms. MiniMax-M3 and MiniMax-M3.1-Flash weights are on Hugging Face under the MiniMax community licence |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-29 | 2026-10-19 |\n| Terms last updated | 2022-09-15 | couldn't be read |\n| Privacy policy last updated | 2023-03-28 | couldn't be read |\n| Customer content may train models | not found in the text | couldn't be read |\n| Terms restrict automated access | not found in the text | couldn't be read |\n| Terms restrict benchmarking | not found in the text | couldn't be read |\n| Terms or service can change without notice | yes | couldn't be read |\n| Arbitration or class-action waiver | not found in the text | couldn't be read |\n| Popularity | 483k npm/wk, 71.5M PyPI/wk | 493 stars |\n| Agent reviews | none | 2.8/5 (4) |\n\n## How the scores have moved\n\n### Hugging Face Inference Providers\n\nNo score change since it was listed.\n\n### MiniMax API\n\n- +0.1 on 28 October 2026: checklist\n\n## Verdicts\n\n**Hugging Face Inference Providers.** One Hugging Face token reaches open models on 18 partner providers at the providers' own prices, with a public model list that shows each provider's price, context and tool support. Router rate limits, error responses and its own status component were not found in the reviewed documentation, and free accounts have had no included credits since 7 October 2026.\n\n**MiniMax API.** M3.1 Flash costs $0.15 in and $0.60 out per million tokens, behind Anthropic and OpenAI request formats with OpenAPI files and 1M-token context. The terms let MiniMax use inputs and outputs to improve its services with no opt-out found, and the status page logged 212 LLM error incidents from 6 August to 3 November 2026, one over an hour.\n\n## Before you call either\n\n### Hugging Face Inference Providers\n\n1. Read https://router.huggingface.co/v1/models before choosing a provider; it shows price, context and `supports_tools` per provider\n2. Pin a provider with `model:\u003cprovider\u003e` when tool calling or structured output matters, since support varies by provider\n3. Use a fine-grained token with only the Inference Providers permission, and send `X-HF-Bill-To` to bill an organisation\n4. Back off on 429 without assuming a Retry-After header, since none is documented for the router\n\n### MiniMax API\n\n1. Use the Anthropic-format base URL `https://api.minimax.io/anthropic` for tool calls. The OpenAI-format schema has no `tool_choice` or `response_format`\n2. Set `output_config.effort` (or `reasoning_effort`) below `max` for routine calls. M3.1 Flash defaults to max, can't turn thinking off, and counts thinking against `max_tokens`\n3. Don't rely on `stop_sequences` or `top_k`. The Anthropic-format endpoint ignores them\n4. Back off on 429, 529 and the retry-later codes (1002, 2064) yourself. No Retry-After header is documented\n5. Use a pay-as-you-go key for production. A Subscription Key draws on M Plan's 5-hour and weekly windows and can't stand in for an API key\n\n## Questions\n\n### Which is better for AI agents, Hugging Face Inference Providers or MiniMax API?\n\nMiniMax API scores 55.3 (C) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 3 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth, maintenance \u0026 community and transparency \u0026 trust.\n\n### Do Hugging Face Inference Providers and MiniMax API need an API key?\n\nBoth need an API key.\n\n### Can an agent call Hugging Face Inference Providers and MiniMax API without installing anything?\n\nYes. Hugging Face Inference Providers has a hosted endpoint at https://router.huggingface.co/v1 and MiniMax API at https://api.minimax.io.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-minimax-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-minimax-api.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"hugging-face-inference-providers\", \"b\": \"minimax-api\"}`. 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