# Hugging Face Inference Providers > 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. - Canonical: https://www.anchorterminal.com/tools/hugging-face-inference-providers - Pricing: https://www.anchorterminal.com/tools/hugging-face-inference-providers#pricing - Reviews: https://www.anchorterminal.com/tools/hugging-face-inference-providers#reviews - Markdown: https://www.anchorterminal.com/tools/hugging-face-inference-providers.md (~10,000 tokens) - Slim: https://www.anchorterminal.com/tools/hugging-face-inference-providers.min.md (~1,730 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/tools/hugging-face-inference-providers.json (this page as data, same URL with Accept: application/json) - Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt) - API: https://www.anchorterminal.com/api/v1/index.json - MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key) - DNS: dig +short TXT hugging-face-inference-providers.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.. and .vs.. under the zone, and the same under grade.letme.dev) - Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data) - Updated: 2026-11-07 ## Overview **Grade C · 54/100 · rank #920 of 1486 · #28 in Model APIs & inference · not agent-ready · confidence medium** More from Hugging Face, Inc., listed separately because each is its own product: [Hugging Face Inference Endpoints](https://www.anchorterminal.com/tools/hugging-face-inference-endpoints.md) (GPU & serverless compute), [smolagents](https://www.anchorterminal.com/tools/smolagents.md) (Agent frameworks & SDKs), [Carbon-X](https://www.anchorterminal.com/tools/carbon-x.md) (Open-weight models), [SmolLM3-3B](https://www.anchorterminal.com/tools/smollm3-3b.md) (Open-weight models). ## Assessment 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. ## Facts | Field | Value | | --- | --- | | Vendor | Hugging Face, Inc. (https://huggingface.co) | | Kind | Model router | | Category | Model APIs & inference (https://www.anchorterminal.com/categories/inference) | | Transport | HTTP | | Endpoint | `https://router.huggingface.co/v1` | | Auth | API key · 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 | Pay per use ($2 / mo) · 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). | | x402 | No · 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). | | 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 | | Packages | pypi: `huggingface_hub`; npm: `@huggingface/inference` | | Source | https://github.com/huggingface/huggingface_hub | | Docs | https://huggingface.co/docs/inference-providers/index | | llms.txt | https://huggingface.co/docs/inference-providers/llms.txt | | Last release | 2026-10-29 | | npm downloads / week | 483,470 | | PyPI downloads / week | 71,518,708 | | Surface listed | The serverless router at router.huggingface.co/v1 (chat completions, a beta Responses API and task endpoints), the Hub API's `inference_provider` model filter and the Python and JavaScript clients, read from the docs, the router's model list and the clients' repositories on 6 November 2026. No account was made and no inference call was sent | | Not the same as Inference Endpoints | Inference Endpoints (listed as hugging-face-inference-endpoints in gpu-compute) deploys a model on dedicated instances billed by the hour. Inference Providers routes per-token calls to partner providers' shared infrastructure. They share a Hugging Face account and compute credits | | Providers | Baseten, Cerebras, Cohere, DeepInfra, fal, Featherless AI, Fireworks, Groq, HF Inference, Novita, Nscale, OVHcloud AI Endpoints, Public AI, Replicate, Scaleway, Together, WaveSpeedAI and Z.ai | | Provider selection | `:fastest` by throughput (default), `:cheapest` by output price, `:preferred` by the account's order, or a provider name. Team and Enterprise admins can disable providers and set a spending limit | | Custom provider keys | A provider key stored in Hugging Face settings is swapped in when routing, so the provider bills the call and included credits don't apply | | Data handling | Request body and response not stored when routed. Debug logs kept up to 30 days without user data or tokens. Each provider's own data policy applies | | Usage reporting | Usage by model and provider in account settings. An organisation usage API with daily requests, cost and token counts is Enterprise only | | Rate limits | None documented for the router. The Hub's own limits (1,000 API requests per 5 minutes for a free user, 2,500 for PRO) cover Hub APIs, resolvers and pages | | Capabilities | inference.router, inference.open-weights, inference.llm | | Tags | hosted, router, usage, prepaid, openai-compatible, llms-txt, python, javascript, status-page, soc2 | | JSON | https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-providers.json | ## Score breakdown (methodology v0.7, October 2026 research run) Assessed 2026-11-06 from public evidence against the published checklist (https://www.anchorterminal.com/benchmark/#checklist). Confidence: medium. Performance and Task success pending (no score, not in the total); the total is Σ(score × weight) ÷ 80 over the 7 assessed categories. "This run" is each category's share of the 100 points. | Category | Weight | This run | Score (0–100) | Points | | --- | --- | --- | --- | --- | | Reliability | 16% | 20 | 25 | 5.0 | | Performance | 10% | pending | pending | n/a | | Schema & documentation | 13% | 16.2 | 62 | 10.1 | | Agent ergonomics | 13% | 16.2 | 58 | 9.4 | | Security & auth | 14% | 17.5 | 79 | 13.8 | | Payments & pricing | 10% | 12.5 | 20 | 2.5 | | Task success | 10% | pending | pending | n/a | | Maintenance & community | 7% | 8.8 | 80 | 7.0 | | Transparency & trust (editorial 58, provenance 84) | 7% | 8.8 | 71 | 6.2 | | Negative events | up to −15 | up to −15 | none recorded | 0 | | **Total** | | | | **54 → C** | ### Why each score - Reliability 25 (checked 2026-11-06): 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. - Performance: Pending. Latency is measured per call by our probes, which haven't run yet, so this run doesn't score it. Its weight is shared across the assessed categories until the first probe window closes. - Schema & documentation 62 (checked 2026-11-06): 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). - Agent ergonomics 58 (checked 2026-11-06): 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). - Security & auth 79 (checked 2026-11-06): 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). - Payments & pricing 20 (checked 2026-11-06): 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). - Task success: Pending. Task success needs the category task suites run through each tool, which haven't run yet, so this run doesn't score it. Its weight is shared across the assessed categories until then. A data provider's data-quality score is published on its listing now and becomes half of this category when it's scored. - Maintenance & community 80 (checked 2026-11-06): 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). - Transparency & trust 71 (checked 2026-11-06): 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). Fix list, everything this grade says the listing lacks, the biggest gain first (14 items). What it covers is at https://www.anchorterminal.com/fixes/hugging-face-inference-providers.md (JSON https://www.anchorterminal.com/fixes/hugging-face-inference-providers.json). The whole list for a coding agent comes from `POST https://www.anchorterminal.com/api/v1/fix-list` with `{"listing": "hugging-face-inference-providers", "plan": "read"}`, free while the beta runs ### What we couldn't check - No rate limits, 429 behaviour or error format for router.huggingface.co were found in the docs read; the Hub rate-limits page doesn't name the router - unchecked: issue and pull-request reply times on huggingface_hub and huggingface.js; the GitHub API was rate-limited for our reader on 6 November - unchecked: the privacy policy, subprocessor list and security.txt were not re-read for this listing and rest on the Inference Endpoints checks of 8 October and 2 November 2026 - firstReleased left empty; the launch date of Inference Providers wasn't found on a page read today - PRO's subscription price is not on the Inference Providers pricing page and wasn't read ### Sources - Inference Providers overview: (seen 2026-11-06) - pricing and billing: (seen 2026-11-06) - security and compliance: (seen 2026-11-06) - Hub API for providers: (seen 2026-11-06) - llms.txt: (seen 2026-11-06) - chat completion reference: (seen 2026-11-06) - function calling guide: (seen 2026-11-06) - Responses API (beta): (seen 2026-11-06) - router model list: (seen 2026-11-06) - Hub rate limits: (seen 2026-11-06) - user access tokens: (seen 2026-11-06) - status page: (seen 2026-11-06) - status feed: (seen 2026-11-06) - terms of service: (seen 2026-11-06) - hub-docs history (free credits change): (seen 2026-11-06) - huggingface_hub tags: (seen 2026-11-06) - huggingface.js tags: (seen 2026-11-06) - huggingface_hub downloads: (seen 2026-11-06) - @huggingface/inference downloads: (seen 2026-11-06) ## Score history Every move of a score since the listing was graded, newest first, with its cause. A score can't move without an entry here. JSON: https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-providers/history.json - 2026-11-06: graded 54 C (methodology 0.7) ## Who's behind it (provenance 84/100, checked 2026-11-06) | Check | Finding | Points | | --- | --- | --- | | Legal entity named | Hugging Face, Inc. | 20/20 | | Domain age | huggingface.co, no registry record we could read | 0/15 | | Endpoint on the vendor's domain | router.huggingface.co | 15/15 | | Terms of service | read, states 6 of the 7 things a reader expects, and has 1 clause that costs points | 7.1/10 | | Privacy policy | read, states 8 of the 8 things a reader expects | 10/10 | | Status page | status.huggingface.co | 10/10 | | Changelog | published | 10/10 | | security.txt | valid | 10/10 | | People named | 3 named with their role, 3 with a public profile | 10/10 | | Support route | help pages, a community | 5/5 | 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. ### Terms and privacy, as read A reading by a fixed set of rules, each answered with the vendor's own sentence. Not legal advice. **Terms of service** (https://huggingface.co/terms-of-service), read 2026-10-08, dated 2022-09-15, states 6 of the 7 things a reader expects. - To know. Says the terms or the service can change without notice (costs points). "We may at any time modify, suspend, or discontinue, temporarily or permanently, the Services (or any part thereof) with or without notice." - To know. Says access can be ended without notice or for any reason. "We may do the same, and we reserve the right to suspend or terminate your access to the Services anytime with or without cause, and at our own discretion, with or without notice." - To know. Has not been updated for three years or more. "🗓 Effective Date: September 15, 2022" - Gives the date it was last updated. Last updated 2022-09-15. - Names the governing law or courts. The law of the State of New York. - States a limit on its liability. Capped at the fees paid in the 12 months before the claim or $50. - Says how changes to the terms are announced. Changes are posted, with no other notice named. - Not found in the text. Refers to a service level or uptime commitment. - Also in the text (2026-10-08). Each party's total liability is capped at the amount paid in the 12 months before the last claim, or 50 US dollars where the claim relates to a free service. "Either Party’s (and each Related Party’s) aggregate liability to the other Party or any third party in any circumstance will not exceed the amount that you paid us during the 12-month period immediately preceding the last claim (or $50 if relating to a free service)." - Also in the text (2026-10-08). Setting a repository public grants every user a perpetual, irrevocable licence to use, reproduce, distribute and make derivative works of its content through the services. "If you decide to set your Repository public, you grant each User a perpetual, irrevocable, worldwide, royalty-free, non-exclusive license to use, display, publish, reproduce, distribute, and make derivative works of your Content through our Services and functionalities;" - Also in the text (2026-10-08). After an account is cancelled, the vendor says it will use commercially reasonable efforts to delete the account's information and repository content within 90 days. "Upon cancellation of your Account, we will use commercially reasonable efforts to delete your information and Content of your own Repositories, whether public or private, within 90 days." **Privacy policy** (https://huggingface.co/privacy), read 2026-10-08, dated 2023-03-28, states 8 of the 8 things a reader expects. - To know. Has not been updated for three years or more. "🗓 Effective Date: March 28, 2023" - Gives the date it was last updated. Last updated 2023-03-28. - Says how long data is kept. For as long as needed, with no period named. - Says whether personal data is sold or shared for advertising. Says it does not sell personal data. - Gives a privacy contact. privacy@huggingface.co. - Also in the text (2026-10-08). Aggregated information that does not identify a user may be disclosed to advertisers and partners, with or without payment, for purposes that include targeting advertisements. "The Company may disclose Anonymous Information (with or without compensation) to third parties, including advertisers and partners, for purposes including, but not limited to, targeting advertisements." - Also in the text (2026-10-08). The company may access information a user keeps private without consent, for legitimate interests such as maintaining security or meeting legal and regulatory obligations. "The Company also reserves the right to access this information with your consent, or without your consent only for the purposes of pursuing legitimate interests such as maintaining security on its Services or complying with any legal or regulatory obligations." ## Humans behind the project (researched 2026-11-06 from public pages, not part of the grade) ### Key people - Clément Delangue, Co-founder and CEO, Hugging Face. LinkedIn: https://www.linkedin.com/in/clementdelangue. X: https://x.com/clementdelangue. GitHub: https://github.com/clmnt - Julien Chaumond, Co-founder and CTO, Hugging Face. LinkedIn: https://www.linkedin.com/in/julienchaumond. X: https://x.com/julien_c. GitHub: https://github.com/julien-c - Thomas Wolf, Co-founder and CSO, Hugging Face. LinkedIn: https://www.linkedin.com/in/thom-wolf. X: https://x.com/Thom_wolf. GitHub: https://github.com/thomwolf - Note: Hugging Face's own pages read (its blog and the founders' profiles on huggingface.co) don't call anyone a founder. Salesforce Ventures' page on its Series D investment (an investor's own page) names Clément Delangue, Julien Chaumond and Thomas Wolf as founders, and SiliconANGLE (24 August 2023) calls Delangue "Co-founder and Chief Executive Officer". The CTO and CSO titles rest on Wikipedia. Each founder's own Hugging Face profile links the LinkedIn, X and GitHub accounts on file. NVIDIA agreed in September 2026 to buy Hugging Face for about $12.9B; tech.eu (3 September 2026) says "The deal is expected to be completed in the first half of 2027." A search on 6 November 2026 found no report that it has closed, so the status stays private and the valuation stays the Series D figure. On 6 November 2026 TechCrunch and FrenchWeb sources were removed because their robots.txt disallows Claude's crawlers. Rounds now rest on Hugging Face's Series C post (May 2022, $100M led by Lux Capital), Salesforce Ventures' Series D post and SiliconANGLE's Series D report ($235M, valued at $4.5B). Seed, Series A and Series B participation and seven angels named only by TechCrunch (Richard Socher, Greg Brockman, Dev Ittycheria, Alex Wang, Aghi Marietti, Florian Douetteau, Paul St. John) were dropped, and the total raised was dropped because no allowed source states it. - Hugging Face, Inc.: LinkedIn https://www.linkedin.com/company/huggingface/ X https://x.com/huggingface GitHub https://github.com/huggingface ### Ownership and investors - Valuation: $4.5B as announced (the source doesn't say pre- or post-money), Series D, August 2023 (source https://siliconangle.com/2023/08/24/tech-giants-back-235m-round-open-source-ai-startup-hugging-face/) - Backed by: Betaworks, A.Capital Ventures, Lux Capital, Addition, Sequoia Capital, Coatue, SV Angel, AIX Ventures, Salesforce, Google, Amazon, NVIDIA, Intel, AMD, Qualcomm, IBM, Sound Ventures, Kevin Durant, Rich Kleiman, Olivier Pomel ### Getting support - Discord: https://huggingface.co/join/discord - Help: https://huggingface.co/support - Help: https://huggingface.co/docs/inference-endpoints/support/faq - Community (Forum): https://discuss.huggingface.co/ - Sources: https://huggingface.co/docs/inference-endpoints/index, https://huggingface.co/docs/inference-endpoints/support/faq, https://en.wikipedia.org/wiki/Hugging_Face, https://huggingface.co/clem, https://huggingface.co/julien-c, https://huggingface.co/thomwolf, https://huggingface.co/, https://siliconangle.com/2023/08/24/tech-giants-back-235m-round-open-source-ai-startup-hugging-face/ ## Live (updated 2026-11-07 18:20 UTC) - Right now: up, HTTP 404, 188 ms, checked 2026-11-07 18:20 UTC (get on `https://router.huggingface.co/v1`) - Uptime 24h 100.0% (200 probes) · 30 days 100.0% (200 probes) · p50 108 ms · p95 196 ms - Vendor status page: not read, no machine-readable status found - github `huggingface/huggingface_hub` v2.4.0, released 2026-10-29 - npm `@huggingface/inference` 4.13.32 - pypi `huggingface_hub` 2.4.0, released 2026-10-29 - security.txt: valid, expires 2030-07-01T08:42:00.000Z - Watching pricing - Always current: https://www.anchorterminal.com/api/v1/live/hugging-face-inference-providers.json ## Probe metrics Not measured yet. Our benchmark probes haven't run, so there's no availability, latency or error rate from a run and Performance is pending. Live uptime, where we poll the endpoint, is under Live and doesn't change the score. ## Prices | Item | Price | Unit | Note | | --- | --- | --- | --- | | openai/gpt-oss-120b input, cheapest provider listed (DeepInfra) | $0.037 | per 1M tokens | 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 | | PRO monthly compute credits | $2 | per month (plan) | Also $2.00 per seat for Team and Enterprise organisations | Across all listings: https://www.anchorterminal.com/prices/index.md ## 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 ## Before you call it (notes for agents) 1. Read https://router.huggingface.co/v1/models before choosing a provider; it shows price, context and `supports_tools` per provider 2. Pin a provider with `model:` when tool calling or structured output matters, since support varies by provider 3. Use a fine-grained token with only the Inference Providers permission, and send `X-HF-Bill-To` to bill an organisation 4. Back off on 429 without assuming a Retry-After header, since none is documented for the router ## Connect Install: ```bash pip install huggingface_hub # or: pip install openai, with base_url https://router.huggingface.co/v1 ``` First request: ```bash curl https://router.huggingface.co/v1/chat/completions \ -H "Authorization: Bearer $HF_TOKEN" -H "Content-Type: application/json" \ -d '{"model":"openai/gpt-oss-120b:fastest","messages":[{"role":"user","content":"How many Gs in huggingface?"}]}' ``` ## Similar tools Ranked by shared capabilities, then score. Same-category tools with no shared capability key are listed last. | Tool | Grade | Score | Rank | Shared capabilities | x402 | Markdown | | --- | --- | --- | --- | --- | --- | --- | | Tencent Cloud TokenHub | C | 59.5 | 700 | inference.router, inference.llm, inference.open-weights | no | https://www.anchorterminal.com/tools/tencent-tokenhub.md | | Vertex AI (Gemini Enterprise Agent Platform) | AA | 88.7 | 2 | inference.llm, inference.open-weights | no | https://www.anchorterminal.com/tools/vertex-ai.md | | Amazon Bedrock | A | 81.7 | 8 | inference.llm, inference.open-weights | no | https://www.anchorterminal.com/tools/amazon-bedrock.md | | Azure OpenAI in Foundry Models | A | 80 | 14 | inference.llm, inference.open-weights | no | https://www.anchorterminal.com/tools/azure-openai.md | | GroqCloud | BB | 74.5 | 81 | inference.llm, inference.open-weights | no | https://www.anchorterminal.com/tools/groq.md | | Fireworks AI Inference | B | 69.3 | 250 | inference.llm, inference.open-weights | no | https://www.anchorterminal.com/tools/fireworks-inference.md | ## Panel reviews (0) Reviewed by the Anchor panel (https://www.anchorterminal.com/reviewers/index.md): . Desk reviews, written from public documentation, pricing, terms, source and status history on 1 October 2026. No calls made. For a desk review, the outcome says whether the reviewer's questions could be answered from public material: success, partial or failure. How reviews work: https://www.anchorterminal.com/reviews/how-it-works.md ## Notable - router.huggingface.co/v1/models answers without a token and listed 125 chat models from 11 providers on 6 November 2026, each with per-provider status, context length, input and output price per million tokens, tool and structured-output support, first-token latency and throughput (source: ) - Appending `:fastest`, `:cheapest` or `:preferred` to a model id picks the provider by throughput, output price or the account's order, and `:` pins one; `:fastest` is the default (source: ) - The partner table lists 18 providers across chat, vision, embeddings, text to image, text to video and speech to text, among them Baseten, Cerebras, Cohere, DeepInfra, fal, Groq, Novita, Nscale, Replicate, Together and Z.ai (source: ) - Free users lost their included monthly credits on 7 October 2026, per a docs change of that day; PRO and Team or Enterprise seats keep $2.00 a month (source: ) - The security page says request bodies and responses are not stored when routed through Hugging Face, debug logs are kept up to 30 days without user data or tokens, and providers' own data policies apply (source: ) - A Responses API is documented as beta beside the GA chat completions endpoint (source: ) - #28 of 42 in Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md - All 830 models comparisons: https://www.anchorterminal.com/compare/inference/index.md ## Compare - [Amazon Bedrock vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers.md): A 81.7 vs C 54 - [Claude API vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/anthropic-api-vs-hugging-face-inference-providers.md): BB 77.3 vs C 54 - [Azure OpenAI in Foundry Models vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/azure-openai-vs-hugging-face-inference-providers.md): A 80 vs C 54 - [BlockRun.AI vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/blockrun-ai-vs-hugging-face-inference-providers.md): A 78.9 vs C 54 - [Cerebras Inference vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/cerebras-inference-vs-hugging-face-inference-providers.md): B 68.6 vs C 54 - [Cloudflare AI Gateway vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-hugging-face-inference-providers.md): B 67.8 vs C 54 - [Cloudflare Workers AI vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-hugging-face-inference-providers.md): B 69.2 vs C 54 - [Cohere Chat API (Command models) vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/cohere-chat-vs-hugging-face-inference-providers.md): B 65.6 vs C 54 - [DeepInfra vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/deepinfra-vs-hugging-face-inference-providers.md): B 63.7 vs C 54 - [DeepSeek API vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/deepseek-api-vs-hugging-face-inference-providers.md): D 46.7 vs C 54 - [Glimpse vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/elorian-glimpse-vs-hugging-face-inference-providers.md): F 35.1 vs C 54 - [Fireworks AI Inference vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/fireworks-inference-vs-hugging-face-inference-providers.md): B 69.3 vs C 54 - [Gemini Developer API vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/gemini-api-vs-hugging-face-inference-providers.md): B 62.2 vs C 54 - [GroqCloud vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/groq-vs-hugging-face-inference-providers.md): BB 74.5 vs C 54 - [Hugging Face Inference Providers vs Inkling 2 Small](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-inkling-2-small.md): C 54 vs D 52.1 - [Hugging Face Inference Providers vs Jais 3](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-jais-3.md): C 54 vs D 52.1 - [Hugging Face Inference Providers vs Meta Model API](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-meta-model-api.md): C 54 vs D 52.3 - [Hugging Face Inference Providers vs MiniMax API](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-minimax-api.md): C 54 vs C 55.3 - [Hugging Face Inference Providers vs Mistral AI API](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-mistral-api.md): C 54 vs B 65.7 - [Hugging Face Inference Providers vs Muse Spark Open](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-muse-spark-open.md): C 54 vs D 53.4 - [Hugging Face Inference Providers vs Novita AI](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-novita-ai.md): C 54 vs D 53.9 - [Hugging Face Inference Providers vs OpenAI API](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openai-api.md): C 54 vs A 83.9 - [Hugging Face Inference Providers vs Beam 1.0](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-reflection-beam.md): C 54 vs D 53.4 - [Hugging Face Inference Providers vs SambaCloud](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-sambanova.md): C 54 vs B 64.9 - [Hugging Face Inference Providers vs SiliconFlow](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-siliconflow.md): C 54 vs E 42.9 - [Hugging Face Inference Providers vs Simplismart](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-simplismart.md): C 54 vs F 29.5 - [Hugging Face Inference Providers vs StepFun API](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-stepfun-api.md): C 54 vs E 44.3 - [Hugging Face Inference Providers vs SWE-2 Flash](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-swe-2-flash.md): C 54 vs F 36.4 - [Hugging Face Inference Providers vs Together AI Inference](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-together-inference.md): C 54 vs B 67.8 - [Hugging Face Inference Providers vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vertex-ai.md): C 54 vs AA 88.7 - [Hugging Face Inference Providers vs xAI API (Grok)](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-xai-api.md): C 54 vs BB 71.7 - [Antseed vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/antseed-vs-hugging-face-inference-providers.md): C 54.1 vs C 54 - [Eden AI vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/eden-ai-vs-hugging-face-inference-providers.md): C 59.9 vs C 54 - [Hugging Face Inference Providers vs LiteLLM](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-litellm.md): C 54 vs B 62.4 - [Hugging Face Inference Providers vs OpenRouter](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-openrouter.md): C 54 vs B 66.6 - [Hugging Face Inference Providers vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router.md): C 54 vs D 53.7 - [Hugging Face Inference Providers vs RouterPlus](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-routerplus.md): C 54 vs D 50.3 - [Hugging Face Inference Providers vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-tencent-tokenhub.md): C 54 vs C 59.5 - [Hugging Face Inference Providers vs Vercel AI Gateway](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway.md): C 54 vs B 67.8 - [Hugging Face Inference Providers vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-nemotron-3-5-super-vl.md): C 54 vs C 59.3 - [Hugging Face Inference Providers vs Prism Inference](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference.md): C 54 vs C 59.6 ## Verify this listing For the vendor. 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