{ "data": { "a": { "slug": "blockrun-ai", "name": "BlockRun.AI", "vendor": "BlockRun, Inc.", "vendorUrl": "https://blockrun.ai", "kind": "mcp", "category": "inference", "summary": "Model and API gateway with an OpenAI-compatible interface, MCP support and per-request stablecoin payments through x402.", "url": "https://www.anchorterminal.com/tools/blockrun-ai", "markdownUrl": "https://www.anchorterminal.com/tools/blockrun-ai.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/blockrun-ai.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/blockrun-ai.json", "dns": "blockrun-ai.grade.anchorterminal.com", "repo": "https://github.com/BlockRunAI/blockrun-llm", "license": "MIT", "transports": [ "stdio" ], "packages": [ { "registry": "pypi", "name": "blockrun-llm" }, { "registry": "npm", "name": "@blockrun/llm" }, { "registry": "npm", "name": "@blockrun/mcp" } ], "auth": "mixed", "authNotes": "Either an API key backed by prepaid card credit (user.blockrun.ai) or a non-custodial wallet signing x402 USDC payments (Base mainnet at https://blockrun.ai/api, Solana at https://sol.blockrun.ai/api, testnets available).", "pricing": "usage", "pricingNotes": "Per-token LLM pricing by model, billed at zero platform margin since 2026-08-08, plus a flat $0.001 network fee per wallet call on Base (the account rail and the Solana gateway charge no fee). Pay-per-call GPT-6 quotes scale the output share with reasoning effort since 2026-10-10. Web search $0.08 flat per call since 2026-09-29; images, video and data endpoints priced per call; seven free models per the site's menu on 1 November. Decisions is free with an API key on api.blockrun.ai and isn't sold over x402. Failed calls (400, 402, 429, 5xx) aren't charged. x402 in USDC on Base, Solana or Arc (https://blockrun.ai/docs/resources/changelog; https://blockrun.ai/docs/api-reference/errors; https://github.com/BlockRunAI/blockrun-mcp).", "priceSummary": "Pay per use", "where": "local", "x402": { "level": "yes", "evidence": "Core business model: x402 v2 micropayments in USDC (ERC-20 on Base mainnet, SPL on Solana) per request; the '~$0.002/call' figure could NOT be verified for LLM inference, which is per-token; $0.002 appears only for trading-market/stock data endpoints (https://github.com/BlockRunAI/blockrun-llm; https://github.com/BlockRunAI/awesome-blockrun)", "endpoints": [ { "url": "https://blockrun.ai/api/v1/chat/completions", "priceUsd": null, "network": "eip155:8453" } ] }, "toolCount": 19, "popularity": { "githubStars": 5, "npmWeekly": null, "pypiWeekly": 679, "asOf": "2026-09-26" }, "docsUrl": "https://github.com/BlockRunAI/awesome-blockrun", "llmsTxt": "https://blockrun.ai/llms.txt", "openapi": "https://blockrun.ai/api/openapi", "registryName": "io.github.BlockRunAI/blockrun-mcp", "capabilities": [ "inference.llm", "web.search", "market.crypto" ], "tags": [ "hosted", "x402", "inference", "openai-compatible" ], "lastRelease": "2026-10-28", "graded": true, "anchor": { "graded": true, "score": 78.9, "grade": "A", "agentReady": true, "rank": 20, "ranked": true, "rankOf": 1510, "categoryRank": 5, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 88, "maintenance": 85, "payments": 100, "reliability": 65, "schema": 90, "security": 61, "transparency": 73 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": 0, "verdict": "x402 v2 on its own gateway lets an agent create a wallet and pay per call in USDC on Base, Solana or Arc with no sign-up, and every MCP tool carries a safety annotation. Since 21 October 2026 prompts sent through the Base and Arc gateways are stored with no fixed expiry, and the status page keeps no incident history.", "bestFor": "Agents that must start and pay with no human sign-up, and builders testing x402 against a real inference gateway.", "strengths": [ "x402 v2 on its own gateway, USDC on Base, Solana and Arc, with no account needed", "Every one of the 19 MCP tools carries readOnlyHint or destructiveHint, trades need `confirm:true`, and a read-only Polymarket tool is separate", "`--profile` cuts the tool definitions from 14,416 tokens to as few as 2,155", "400, 402, 429 and 5xx responses aren't charged, and payment settles only after a successful upstream response", "40 registry releases between 3 August and 28 October 2026, with a detailed changelog" ], "weaknesses": [ "Since 21 October 2026 prompts and completions sent through the Base, Arc and API gateways are stored with no fixed expiry", "The status page shows live checks only and keeps no incident history, and the terms commit to no uptime", "Models are removed on the day, with no notice period, and the terms let providers withdraw a model at any time", "No subprocessor list, data locations or prompt-injection guidance", "The wallet key controls the whole balance and sits in a local file or environment variable" ], "agentNotes": [ "Fund a dedicated wallet with a small USDC balance. The balance is the spending cap", "Use the Solana gateway when prompts must not be stored. Base and Arc keep request content with no fixed expiry", "Start the server with `--profile` for the job (chat, research, media or trading) to cut the tool definitions", "Set `BLOCKRUN_CONFIRM_SPEND=on` to approve each paid call. It's off by default", "Call `blockrun_models` before hard-coding a model name, since models are removed without notice" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "A", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 78.9 } ], "editorialScores": { "ergonomics": 88, "maintenance": 85, "payments": 100, "reliability": 65, "schema": 90, "security": 61, "transparency": 63 }, "provenanceScore": 82, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-11-01", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "claudeCode": "claude mcp add blockrun -- npx -y @blockrun/mcp", "config": { "mcpServers": { "blockrun": { "args": [ "-y", "@blockrun/mcp" ], "command": "npx", "env": { "BLOCKRUN_WALLET_KEY": "${BLOCKRUN_WALLET_KEY}" } } } }, "x402": "curl -s -i https://blockrun.ai/api/v1/chat/completions -H 'content-type: application/json' -d '{\"model\":\"\u003cmodel\u003e\",\"messages\":[{\"role\":\"user\",\"content\":\"hi\"}]}'\n# 402 Payment Required -\u003e PAYMENT-REQUIRED header -\u003e retry with PAYMENT-SIGNATURE" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/blockrun-ai" }, "area": "models", "provenance": { "legalEntity": "BlockRun, Inc.", "domain": "blockrun.ai", "domainRegistered": "2025-10-06", "domainNote": "The terms and privacy policy, both updated 2026-10-21, name BlockRun, Inc., a Delaware corporation, as contracting party and data controller. No founders or street address are published. The domain was registered on 2025-10-06. The status page is self-hosted and keeps no incident history. security.txt, read on 1 November 2026, has an email contact, a policy link and an Expires date of 2027-11-01.", "endpointOnVendorDomain": null, "terms": "https://blockrun.ai/terms", "privacy": "https://blockrun.ai/privacy", "statusPage": "https://blockrun.ai/status", "changelog": "https://blockrun.ai/docs/resources/changelog", "securityTxt": "valid", "checked": "2026-11-01", "score": 82 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/blockrun-ai.json", "live": { "slug": "blockrun-ai", "vendorStatus": { "page": "https://blockrun.ai/status", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-07T04:47:11.516915511Z" }, "versions": [ { "registry": "github", "name": "BlockRunAI/blockrun-llm", "version": "v1.21.3", "released": "2026-10-27", "seenAt": "2026-11-06T23:11:39.550307273Z" }, { "registry": "mcp-registry", "name": "io.github.BlockRunAI/blockrun-mcp", "version": "0.55.7", "seenAt": "2026-11-07T18:16:28.95801333Z" }, { "registry": "npm", "name": "@blockrun/llm", "version": "3.26.0", "seenAt": "2026-11-06T23:11:37.362532949Z" }, { "registry": "npm", "name": "@blockrun/mcp", "version": "0.55.7", "seenAt": "2026-11-06T23:11:37.581995874Z" }, { "registry": "pypi", "name": "blockrun-llm", "version": "1.21.3", "released": "2026-10-27", "seenAt": "2026-11-06T23:11:37.178663673Z" } ], "githubStars": 5, "npmWeekly": 2003, "pypiWeekly": 246, "securityTxt": { "url": "https://blockrun.ai/.well-known/security.txt", "state": "valid", "expires": "2027-11-07T16:00:22.566Z", "checkedAt": "2026-11-07T16:00:22.39782235Z" }, "llmsTxt": { "url": "https://blockrun.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:31:43.384018803Z" }, "domain": { "domain": "blockrun.ai", "registered": "2025-10-06", "source": "https://rdap.identitydigital.services/rdap/domain/blockrun.ai", "checkedAt": "2026-11-01T14:22:13.538847185Z" }, "pages": [ { "url": "https://blockrun.ai/changelog", "kind": "changelog", "status": 200, "checkedAt": "2026-10-01T13:11:21.906696649Z", "changedAt": "2026-09-30T13:09:43.712367412Z", "fingerprint": "658ca7fbc8ce" }, { "url": "https://blockrun.ai/docs/resources/changelog", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:00:17.110049944Z", "changedAt": "2026-11-06T13:23:03.818195581Z", "fingerprint": "5dce49861c17" }, { "url": "https://blockrun.ai/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:00:19.869868705Z", "changedAt": "2026-11-07T14:00:19.869868705Z", "fingerprint": "9d7ebbeae2b9" }, { "url": "https://blockrun.ai/terms", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:00:21.4772749Z", "changedAt": "2026-11-07T14:00:21.4772749Z", "fingerprint": "d4c383e5aca6" } ], "github": { "repo": "blockrunai/blockrun-llm", "checkedAt": "2026-11-02T08:35:58.65218286Z", "stars": 5, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-27T15:57:32Z", "openIssues": 0, "openPRs": 0, "issuesOpened90d": 2, "issuesClosed90d": 2, "prsMerged90d": 46, "ci": { "branch": "main", "runs": 50, "success": 48, "failure": 2, "other": 0, "latest": "success", "latestAt": "2026-10-27T06:44:13Z" }, "replies": { "sampled": 6, "unanswered": 0, "medianDays": 0.4 } }, "updatedAt": "2026-11-07T18:16:28.95801333Z" } }, "answer": "BlockRun.AI scores 78.9 (A) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 6 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth.", "b": { "slug": "hugging-face-inference-providers", "name": "Hugging Face Inference Providers", "vendor": "Hugging Face, Inc.", "vendorUrl": "https://huggingface.co", "kind": "router", "category": "inference", "summary": "Hugging Face's serverless router that sends model calls to partner inference providers such as Groq, Cerebras, Together and Fireworks through one Hugging Face token, with an OpenAI-compatible API at router.huggingface.co/v1 and Python and JavaScript clients.", "url": "https://www.anchorterminal.com/tools/hugging-face-inference-providers", "markdownUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-providers.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-providers.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-providers.json", "dns": "hugging-face-inference-providers.grade.anchorterminal.com", "repo": "https://github.com/huggingface/huggingface_hub", "license": "Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT", "transports": [ "http" ], "remoteUrl": "https://router.huggingface.co/v1", "packages": [ { "registry": "pypi", "name": "huggingface_hub" }, { "registry": "npm", "name": "@huggingface/inference" } ], "auth": "api-key", "authNotes": "Hugging Face user access token sent as `Authorization: Bearer $HF_TOKEN`. The docs recommend a fine-grained token with only the `Make calls to Inference Providers` permission. Tokens are made in account settings in a browser, can be rotated and revoked, and a leaked token can be revoked by anyone through `POST /api/credentials/revoke`. A provider's own key can be stored in settings instead, and Hugging Face swaps it in when routing.", "pricing": "usage", "pricingNotes": "Pay as you go at each provider's own per-token rates with no Hugging Face markup, drawn from prepaid credits on the Hugging Face account. Free users get no included credits since 7 October 2026 and must buy credits. PRO users and Team or Enterprise seats get $2.00 a month of compute credits. Requests with a custom provider key are billed by the provider (https://huggingface.co/docs/inference-providers/pricing, checked 2026-11-06).", "priceSummary": "$2 / mo", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the Inference Providers docs, llms.txt or the router's model list. Calls draw on prepaid Hugging Face credits bought in the account's billing settings (checked 2026-11-06).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 483470, "pypiWeekly": 71518708, "asOf": "2026-11-06" }, "docsUrl": "https://huggingface.co/docs/inference-providers/index", "llmsTxt": "https://huggingface.co/docs/inference-providers/llms.txt", "capabilities": [ "inference.router", "inference.open-weights", "inference.llm" ], "tags": [ "hosted", "router", "usage", "prepaid", "openai-compatible", "llms-txt", "python", "javascript", "status-page", "soc2" ], "lastRelease": "2026-10-29", "graded": true, "anchor": { "graded": true, "score": 54, "grade": "C", "agentReady": false, "rank": 926, "ranked": true, "rankOf": 1510, "categoryRank": 28, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 58, "maintenance": 80, "payments": 20, "reliability": 25, "schema": 62, "security": 79, "transparency": 71 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "One Hugging Face token reaches open models on 18 partner providers at the providers' own prices, with a public model list that shows each provider's price, context and tool support. Router rate limits, error responses and its own status component were not found in the reviewed documentation, and free accounts have had no included credits since 7 October 2026.", "bestFor": "Agents and developers who want open-weight models from several hosts on one token and one bill, with a public price and capability list per provider.", "strengths": [ "router.huggingface.co/v1/models lists every routed model with each provider's price, context, tool support, latency and throughput, without a token", "Provider choice by suffix (`:fastest`, `:cheapest`, `:preferred` or a provider name) on an OpenAI-compatible endpoint", "Fine-grained tokens can be limited to the `Make calls to Inference Providers` permission and revoked at once", "No markup on provider rates, and request bodies and responses are not stored when routed", "Official clients in Python (`huggingface_hub` 2.4.0, 29 October 2026) and JavaScript (`@huggingface/inference` 4.13.32)" ], "weaknesses": [ "No rate limits, 429 behaviour or error responses documented for the router", "status.huggingface.co has no component for Inference Providers or the router", "Free users have had no included credits since 7 October 2026, and buying credits needs a person in the account settings", "No OpenAPI document for the router, no batch API, and the Responses API is beta", "Data handling past the router depends on each provider's own policy" ], "agentNotes": [ "Read https://router.huggingface.co/v1/models before choosing a provider; it shows price, context and `supports_tools` per provider", "Pin a provider with `model:\u003cprovider\u003e` when tool calling or structured output matters, since support varies by provider", "Use a fine-grained token with only the Inference Providers permission, and send `X-HF-Bill-To` to bill an organisation", "Back off on 429 without assuming a Retry-After header, since none is documented for the router" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 54 } ], "editorialScores": { "ergonomics": 58, "maintenance": 80, "payments": 20, "reliability": 25, "schema": 62, "security": 79, "transparency": 58 }, "provenanceScore": 84, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install huggingface_hub # or: pip install openai, with base_url https://router.huggingface.co/v1", "http": "curl https://router.huggingface.co/v1/chat/completions \\\n -H \"Authorization: Bearer $HF_TOKEN\" -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"openai/gpt-oss-120b:fastest\",\"messages\":[{\"role\":\"user\",\"content\":\"How many Gs in huggingface?\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.router", "tool": "https://letme.dev/hugging-face-inference-providers" }, "sameCompany": [ "hugging-face-inference-endpoints", "smolagents", "carbon-x", "smollm3-3b" ], "area": "models", "unitPrices": [ { "item": "openai/gpt-oss-120b input, cheapest provider listed (DeepInfra)", "unit": "1m-tokens", "usd": 0.037, "note": "Output $0.17. Groq lists $0.15/$0.75 and Cerebras $0.35/$0.75, per the router's model list of 6 November 2026" }, { "item": "PRO monthly compute credits", "unit": "month", "usd": 2, "note": "Also $2.00 per seat for Team and Enterprise organisations" } ], "provenance": { "legalEntity": "Hugging Face, Inc.", "domain": "huggingface.co", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://huggingface.co/terms-of-service", "privacy": "https://huggingface.co/privacy", "statusPage": "https://status.huggingface.co", "changelog": "https://huggingface.co/changelog", "securityTxt": "valid", "checked": "2026-11-06", "notes": [ "The Terms of Service (effective 15 September 2022) name Hugging Face, Inc. and define Inference Providers as a hosted service for running inference through an API on Hub models.", "huggingface.co/robots.txt and router.huggingface.co/robots.txt allow all. status.huggingface.co serves an empty robots.txt.", "status.huggingface.co is a Better Stack page with components for the Hub, git hosting, Inference Endpoints, Spaces, the CDNs and Jobs, and none for Inference Providers or the router.", "huggingface.co/changelog covers the whole Hub and had no Inference Providers entry on its first page on 6 November 2026. Dated changes to the docs are in the hub-docs repository's history.", "security.txt, privacy policy and subprocessor list as recorded on the Inference Endpoints listing (checked 8 October and 2 November 2026); not re-read for this listing." ], "score": 84 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-providers.json", "live": { "slug": "hugging-face-inference-providers", "probe": { "target": "https://router.huggingface.co/v1", "method": "get", "lastAt": "2026-11-07T19:22:12.474650545Z", "lastOk": true, "lastStatus": 404, "lastMs": 145, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 109, "p95ms24h": 196, "samples24h": 210, "samples30d": 210, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 197, "ok": 197 } ] }, "vendorStatus": { "page": "https://status.huggingface.co", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-07T04:47:55.542550557Z" }, "versions": [ { "registry": "github", "name": "huggingface/huggingface_hub", "version": "v2.4.0", "released": "2026-10-29", "seenAt": "2026-11-06T23:33:27.894225298Z" }, { "registry": "npm", "name": "@huggingface/inference", "version": "4.13.32", "seenAt": "2026-11-06T23:33:27.102558197Z" }, { "registry": "pypi", "name": "huggingface_hub", "version": "2.4.0", "released": "2026-10-29", "seenAt": "2026-11-06T23:33:26.910773744Z" } ], "githubStars": 4034, "npmWeekly": 483470, "pypiWeekly": 71518708, "securityTxt": { "url": "https://huggingface.co/.well-known/security.txt", "state": "valid", "expires": "2030-07-01T08:42:00.000Z", "checkedAt": "2026-11-07T16:00:00.493446773Z" }, "llmsTxt": { "url": "https://huggingface.co/docs/inference-providers/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:32:44.910268229Z" }, "pages": [ { "url": "https://huggingface.co/docs/inference-providers/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-11-07T14:11:37.221950067Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "2cbe821ca9d2" } ], "updatedAt": "2026-11-07T19:22:12.474650545Z" } }, "edges": [ { "by": 80, "category": "payments", "leads": "blockrun-ai", "name": "Payments \u0026 pricing", "reasons": { "a": "x402 v2 on its own gateway, USDC on Base and Solana, and since MCP 0.55.0 (28 October) on Circle's Arc through arc.blockrun.ai (40). Per-token prices per model published without a login, plus a flat $0.001 fee per wallet call on Base (20). Seven free models per the status page's menu, no card or sign-up, and a wallet costs nothing to create (20). An agent can create its own wallet and pay per request with no human sign-up (20). 40 + 20 + 20 + 20 = 100.", "b": "No x402, MPP or L402 (0). Per-token prices for every model and provider published without a login in the router's /v1/models and on model pages (20). No free tier since 7 October 2026, when free users lost their included monthly credits; PRO's $2.00 of credits needs a subscription (0). Sign-up, token creation and credit purchase are browser steps (0)." }, "scores": { "a": 100, "b": 20 } }, { "by": 40, "category": "reliability", "leads": "blockrun-ai", "name": "Reliability", "reasons": { "a": "Read with the local-software lines, as the listing's kind is `mcp` and the owner runs the server over stdio, though every paid call lands on BlockRun's gateway (the reading assymetrix-mcp and copilot-studio-mcp get). The 1 October check read it as a router. Installs from the official npm package `@blockrun/mcp` with Node 20.19 or later stated in `engines` (20). The CI workflow runs typecheck, build and tests on Node 20.19 and 22 on every push and pull request, with a required gate job. Run results weren't readable, as GitHub's pages answered 403 (20 of 25). Open issues couldn't be read. The changelog names numbered reports fixed in releases, such as #176 and #177 in 0.54.3 and 0.54.4 (10 of 25). Semver numbering with breaking changes marked BREAKING in CHANGELOG.md and shipped as minor bumps, as its own entries say (15). Version 0.55.0, pre-1.0 (0). 20 + 20 + 10 + 15 + 0 = 65. For the gateway behind it, blockrun.ai/status still shows live checks of the Base and Solana gateways and says \"None recorded on this page yet\" under incident history, the terms still say \"We do not commit to any particular uptime\", and free models are limited to 30 requests a minute and 300 an hour per IP with 429s carrying Retry-After.", "b": "Hosted lines. status.huggingface.co is a Better Stack page with 90-day component history for the Hub, Inference Endpoints, Spaces, the CDNs and Jobs, but no component for Inference Providers or the router (10 of 20). With no component, there is no readable incident history for the surface agents call, and the feed's 23 items from 10 June to 7 October 2026 don't name it (5). No rate limits for the router were found; the Hub rate-limits page gives numbers for Hub APIs, resolvers and pages only (0). No 429 or overload guidance for the router was found (0). No SLA found (0). Chat completions on the router is generally available; the Responses API is labelled beta (10). Routing between providers with `:fastest` or `:cheapest` softens a single provider's outage, which this checklist doesn't score." }, "scores": { "a": 65, "b": 25 } }, { "by": 30, "category": "ergonomics", "leads": "blockrun-ai", "name": "Agent ergonomics", "reasons": { "a": "MCP reading. 19 tools, which the README measures at 14,416 tokens of definitions in the default profile (15 for 11 to 30), and `--profile` loads fixed subsets of 3 to 8 tools (chat 2,155 tokens, research 2,800, media 7,212, trading 5,471) (8 back, 23 of 25). Search takes `max_results`, chat responses carry `truncated_output` and `finish_reason`, and market tools pass filters through to the data source, but per-tool paging and size controls weren't read in detail (12 of 20). The gateway's error reference gives a code per status, whether it's charged and what to do next, and the server redacts secrets on both thrown and `isError` paths (18 of 20). Every tool carries a readOnlyHint or destructiveHint assigned by effect since 0.33.0, with a test that fails on an unannotated tool. Payment settles only after a successful upstream response, and since 0.54.2 a withdrawal that may have moved money is never signed twice (20). Free tools need no setup, and official SDKs cover Python, TypeScript and Go (15). 23 + 12 + 18 + 20 + 15 = 88.", "b": "Router reading of the model checklist (tool use, structured output, caching, context, batch, SDKs, errors), as for openrouter. Tool calling through the OpenAI-compatible API with `tool_choice`, support flagged per provider in /v1/models (15 of 20). Structured output documented, support flagged per provider and false on some (10 of 15). No prompt caching guidance found, though the Enterprise usage API counts cached input tokens (3 of 15). Routes to models with up to 1,048,576 tokens of context per the model list, a judgement call since a router has no default model (15). No batch API (0 of 10). Official clients in Python and JavaScript, plus any OpenAI SDK (10). Errors not documented (5 of 15)." }, "scores": { "a": 88, "b": 58 } }, { "by": 28, "category": "schema", "leads": "blockrun-ai", "name": "Schema \u0026 documentation", "reasons": { "a": "MCP reading. All 19 tools take zod input schemas, which the MCP SDK turns into JSON Schema, per the 1 October read of the source (25, was 10 for the gateway's OpenAPI document, which robots.txt still keeps our reader out of under /api/). llms.txt served at blockrun.ai/llms.txt (10). The tool descriptions state purpose and order of use, such as 'discover markets ... with blockrun_markets first' and 'Run action:\"setup\" FIRST', per the 1 October check (15 of 20). Enums and numeric bounds, but seven fields across six tools take a free-form `z.any()` JSON body, per the 1 October check (10 of 15). The docs have an error reference with codes per status and recovery steps, and the README has examples for each client (15). A dated gateway changelog, last entry 25 October 2026, and a CHANGELOG.md in the MCP repository through 0.55.0 (15). 25 + 10 + 15 + 10 + 15 + 15 = 90.", "b": "No OpenAPI document for the router (openapi.json paths answer 404). The task reference pages are generated from typed JSON Schema specs in huggingface.js, and the router's /v1/models gives a machine-readable catalogue, so 12 of 25. llms.txt for the Inference Providers docs and a Markdown twin of every page via `.md` (10). Guides say what each task and policy is for, with a quick setup page for coding agents (14 of 20). Parameter tables with types for chat completion, though `response_format` and `tool_choice` show as unknown types (9 of 15). Examples in Python, JavaScript and curl on every task page, but no documented error responses for the router (9 of 15). No changelog of its own; the Hub changelog doesn't cover it and dated changes are only in the hub-docs history (8 of 15)." }, "scores": { "a": 90, "b": 62 } }, { "by": 18, "category": "security", "leads": "hugging-face-inference-providers", "name": "Security \u0026 auth", "reasons": { "a": "MCP and API reading. The credential is a wallet private key, auto-created at `~/.blockrun/.session` or passed in an environment variable and optionally mirrored to the OS keychain, and it controls the whole balance. `blockrun_wallet` can delegate a capped budget to a child agent, and an API-key route backed by account credit exists (20 of 30, as on 1 October). `blockrun_polymarket_read` gives read-only positions and previews apart from the trading tool, trades need `confirm:true` with a $25 default order cap, `--profile` drops whole groups of tools, and `BLOCKRUN_CONFIRM_SPEND=on` pauses every paid call for approval, though it's off by default (16 of 20). Search, Exa, market and RPC tools return third-party content, and no prompt-injection guidance was found in the README or docs read (5, as knock and suprsend). Every payment settles on-chain and the wallet tool reports balances and spending (10 of 15). security.txt is valid on 1 November, with an email contact, a policy link and an Expires date of 1 November 2027, and SECURITY.md takes private GitHub reports with a 72-hour acknowledgement and a 7-day plan for fund-affecting issues. No bounty or certification found (10). 20 + 16 + 5 + 10 + 10 = 61.", "b": "Model reading. Fine-grained user access tokens that can be limited to the `Make calls to Inference Providers` permission, rotated and revoked, plus a public revocation endpoint for leaked tokens, and organisation approval of fine-grained tokens on paid plans (30). Hugging Face says it doesn't store user data for training, but data handling past the router follows each provider's policy, with no per-request filter to exclude providers that train or retain (12 of 20). Request bodies and responses aren't stored when routed and debug logs are kept up to 30 days without user data or tokens, with provider retention outside that statement (10 of 15). Usage by model and provider in account settings, an Enterprise usage API, and Team and Enterprise admins can disable providers and set a spending limit (13 of 15). SOC 2 Type 2 for the Hub, of which the docs say Inference Providers is a feature, and security.txt valid to 2030 per the Inference Endpoints check; no bug bounty found (14 of 20)." }, "scores": { "a": 61, "b": 79 } }, { "by": 5, "category": "maintenance", "leads": "blockrun-ai", "name": "Maintenance \u0026 community", "reasons": { "a": "MCP reading. @blockrun/mcp 0.55.0 published to the official MCP registry on 28 October 2026, and a gateway changelog entry on 25 October (30). 40 registry versions from 0.35.0 on 3 August to 0.55.0 (20). Issue replies couldn't be read, as GitHub's issue pages answered 403; the changelog credits numbered reports fixed within releases (10 of 25). Listed in the official MCP registry as io.github.BlockRunAI/blockrun-mcp, a GitHub-verified namespace, active, with 0.55.0 marked latest (15). CI on Node 20.19 and 22 with typecheck and tests on every pull request, and a Renovate configuration in the repository (10). 30 + 20 + 10 + 15 + 10 = 85.", "b": "Model reading. huggingface_hub 2.4.0 tagged on 29 October 2026 and the Inference Providers docs updated daily by an automated job, last on 6 November (30). huggingface_hub 2.2.0, 2.3.0 and 2.4.0 and @huggingface/inference 4.13.28 to 4.13.32 in the 90 days (20). No dedicated changelog; the Hub has a forum and Discord, and GitHub issue replies were not read (8 of 15). Current official SDKs in Python and JavaScript (15). The Python client supports Python 3.10 and later, per the Inference Endpoints check; CI not read (7 of 10)." }, "scores": { "a": 85, "b": 80 } } ], "facts": [ { "a": "MCP server", "b": "Model router", "name": "Kind" }, { "a": "BlockRun, Inc.", "b": "Hugging Face, Inc.", "name": "Vendor" }, { "a": "no (local only)", "b": "https://router.huggingface.co/v1", "name": "Hosted endpoint" }, { "a": "stdio", "b": "HTTP", "name": "Transports" }, { "a": "OAuth or key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "yes", "b": "no", "name": "x402" }, { "a": "MIT", "b": "Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT", "name": "Licence" }, { "a": "19", "b": "none", "name": "Tools exposed" }, { "a": "yes", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "io.github.BlockRunAI/blockrun-mcp", "b": "not listed", "name": "MCP registry" }, { "a": "2026-10-28", "b": "2026-10-29", "name": "Last release" }, { "a": "2026-09-02", "b": "2022-09-15", "name": "Terms last updated" }, { "a": "2026-09-02", "b": "2023-03-28", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "yes", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "5 stars, 679 PyPI/wk", "b": "483k npm/wk, 71.5M PyPI/wk", "name": "Popularity" }, { "a": "3.5/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "BlockRun.AI scores 78.9 (A) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 6 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth.", "question": "Which is better for AI agents, BlockRun.AI or Hugging Face Inference Providers?" }, { "answer": "BlockRun.AI takes an API key or an OAuth sign-in. Hugging Face Inference Providers needs an API key. An agent can also pay BlockRun.AI per call over x402, with no account.", "question": "Do BlockRun.AI and Hugging Face Inference Providers need an API key?" }, { "answer": "BlockRun.AI runs on your own machine, with no hosted endpoint listed. Hugging Face Inference Providers has a hosted endpoint at https://router.huggingface.co/v1.", "question": "Can an agent call BlockRun.AI and Hugging Face Inference Providers without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 65 against 25", "Schema \u0026 documentation, 90 against 62", "Agent ergonomics, 88 against 58", "Payments \u0026 pricing, 100 against 20", "Maintenance \u0026 community, 85 against 80" ], "also": [ "Agent-ready, a grade of BB or better", "An agent can pay per call over x402, with no account", "Runs on your own machine" ], "goodFor": "Agents that must start and pay with no human sign-up, and builders testing x402 against a real inference gateway.", "slug": "blockrun-ai", "watchFor": "Since 21 October 2026 prompts and completions sent through the Base, Arc and API gateways are stored with no fixed expiry" }, { "aheadOn": [ "Security \u0026 auth, 79 against 61" ], "also": [ "A hosted endpoint, with nothing to install" ], "goodFor": "Agents and developers who want open-weight models from several hosts on one token and one bill, with a public price and capability list per provider.", "slug": "hugging-face-inference-providers", "watchFor": "No rate limits, 429 behaviour or error responses documented for the router" } ], "history": { "blockrun-ai": [ { "causes": [ "terms", "correction" ], "date": "2026-11-01", "delta": 6.4, "from": 72.5, "fromGrade": "BB", "to": 78.9, "toGrade": "A" }, { "causes": [ "method" ], "date": "2026-10-28", "delta": 0.1, "from": 72.4, "fromGrade": "BB", "to": 72.5, "toGrade": "BB" }, { "causes": [ "method" ], "date": "2026-10-08", "delta": -0.1, "from": 72.5, "fromGrade": "BB", "to": 72.4, "toGrade": "BB" } ], "hugging-face-inference-providers": null }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-blockrun-ai.json", "title": "Amazon Bedrock vs BlockRun.AI", "url": 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"https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-routerplus.json", "title": "Hugging Face Inference Providers vs RouterPlus", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-tencent-tokenhub.json", "title": "Hugging Face Inference Providers vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway.json", "title": "Hugging Face Inference Providers vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-nemotron-3-5-super-vl.json", "title": "Hugging Face Inference Providers vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference.json", "title": "Hugging Face Inference Providers vs Prism Inference", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference" } ], "panel": null, "scores": [ { "blockrun-ai": 65, "by": 40, "edge": "blockrun-ai", "hugging-face-inference-providers": 25, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "blockrun-ai": 90, "by": 28, "edge": "blockrun-ai", "hugging-face-inference-providers": 62, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "blockrun-ai": 88, "by": 30, "edge": "blockrun-ai", "hugging-face-inference-providers": 58, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "blockrun-ai": 61, "by": 18, "edge": "hugging-face-inference-providers", "hugging-face-inference-providers": 79, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "blockrun-ai": 100, "by": 80, "edge": "blockrun-ai", "hugging-face-inference-providers": 20, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "blockrun-ai": 85, "by": 5, "edge": "blockrun-ai", "hugging-face-inference-providers": 80, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "blockrun-ai": 73, "by": 2, "edge": "blockrun-ai", "hugging-face-inference-providers": 71, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "BlockRun.AI scores 78.9 (A) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 6 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth. Both do llm inference. BlockRun.AI accepts x402. Hugging Face Inference Providers doesn't.", "tasks": null, "tutorials": [], "verdicts": { "blockrun-ai": "x402 v2 on its own gateway lets an agent create a wallet and pay per call in USDC on Base, Solana or Arc with no sign-up, and every MCP tool carries a safety annotation. Since 21 October 2026 prompts sent through the Base and Arc gateways are stored with no fixed expiry, and the status page keeps no incident history.", "hugging-face-inference-providers": "One Hugging Face token reaches open models on 18 partner providers at the providers' own prices, with a public model list that shows each provider's price, context and tool support. Router rate limits, error responses and its own status component were not found in the reviewed documentation, and free accounts have had no included credits since 7 October 2026." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/blockrun-ai-vs-hugging-face-inference-providers", "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-hugging-face-inference-providers.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/blockrun-ai-vs-hugging-face-inference-providers.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/blockrun-ai-vs-hugging-face-inference-providers.min.md" }, "markdown": "BlockRun.AI scores 78.9 (A) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 6 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth. Both do llm inference. BlockRun.AI accepts x402. Hugging Face Inference Providers doesn't.\n\n- BlockRun.AI: grade A, 78.9/100, rank #20 of 1510. Markdown https://www.anchorterminal.com/tools/blockrun-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/blockrun-ai.json\n- Hugging Face Inference Providers: grade C, 54/100, rank #926 of 1510. Markdown https://www.anchorterminal.com/tools/hugging-face-inference-providers.md · JSON https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-providers.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 830 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### BlockRun.AI (A)\n\nGood for: Agents that must start and pay with no human sign-up, and builders testing x402 against a real inference gateway.\n\nAhead on:\n- Reliability, 65 against 25\n- Schema \u0026 documentation, 90 against 62\n- Agent ergonomics, 88 against 58\n- Payments \u0026 pricing, 100 against 20\n- Maintenance \u0026 community, 85 against 80\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- An agent can pay per call over x402, with no account\n- Runs on your own machine\n\nWatch for: Since 21 October 2026 prompts and completions sent through the Base, Arc and API gateways are stored with no fixed expiry\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 61\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: No rate limits, 429 behaviour or error responses documented for the router\n\n\n## Why the edge\n\n### Payments \u0026 pricing: BlockRun.AI +80\n\n- BlockRun.AI (100): x402 v2 on its own gateway, USDC on Base and Solana, and since MCP 0.55.0 (28 October) on Circle's Arc through arc.blockrun.ai (40). Per-token prices per model published without a login, plus a flat $0.001 fee per wallet call on Base (20). Seven free models per the status page's menu, no card or sign-up, and a wallet costs nothing to create (20). An agent can create its own wallet and pay per request with no human sign-up (20). 40 + 20 + 20 + 20 = 100.\n- Hugging Face Inference Providers (20): No x402, MPP or L402 (0). Per-token prices for every model and provider published without a login in the router's /v1/models and on model pages (20). No free tier since 7 October 2026, when free users lost their included monthly credits; PRO's $2.00 of credits needs a subscription (0). Sign-up, token creation and credit purchase are browser steps (0).\n\n### Reliability: BlockRun.AI +40\n\n- BlockRun.AI (65): Read with the local-software lines, as the listing's kind is `mcp` and the owner runs the server over stdio, though every paid call lands on BlockRun's gateway (the reading assymetrix-mcp and copilot-studio-mcp get). The 1 October check read it as a router. Installs from the official npm package `@blockrun/mcp` with Node 20.19 or later stated in `engines` (20). The CI workflow runs typecheck, build and tests on Node 20.19 and 22 on every push and pull request, with a required gate job. Run results weren't readable, as GitHub's pages answered 403 (20 of 25). Open issues couldn't be read. The changelog names numbered reports fixed in releases, such as #176 and #177 in 0.54.3 and 0.54.4 (10 of 25). Semver numbering with breaking changes marked BREAKING in CHANGELOG.md and shipped as minor bumps, as its own entries say (15). Version 0.55.0, pre-1.0 (0). 20 + 20 + 10 + 15 + 0 = 65. For the gateway behind it, blockrun.ai/status still shows live checks of the Base and Solana gateways and says \"None recorded on this page yet\" under incident history, the terms still say \"We do not commit to any particular uptime\", and free models are limited to 30 requests a minute and 300 an hour per IP with 429s carrying Retry-After.\n- Hugging Face Inference Providers (25): Hosted lines. status.huggingface.co is a Better Stack page with 90-day component history for the Hub, Inference Endpoints, Spaces, the CDNs and Jobs, but no component for Inference Providers or the router (10 of 20). With no component, there is no readable incident history for the surface agents call, and the feed's 23 items from 10 June to 7 October 2026 don't name it (5). No rate limits for the router were found; the Hub rate-limits page gives numbers for Hub APIs, resolvers and pages only (0). No 429 or overload guidance for the router was found (0). No SLA found (0). Chat completions on the router is generally available; the Responses API is labelled beta (10). Routing between providers with `:fastest` or `:cheapest` softens a single provider's outage, which this checklist doesn't score.\n\n### Agent ergonomics: BlockRun.AI +30\n\n- BlockRun.AI (88): MCP reading. 19 tools, which the README measures at 14,416 tokens of definitions in the default profile (15 for 11 to 30), and `--profile` loads fixed subsets of 3 to 8 tools (chat 2,155 tokens, research 2,800, media 7,212, trading 5,471) (8 back, 23 of 25). Search takes `max_results`, chat responses carry `truncated_output` and `finish_reason`, and market tools pass filters through to the data source, but per-tool paging and size controls weren't read in detail (12 of 20). The gateway's error reference gives a code per status, whether it's charged and what to do next, and the server redacts secrets on both thrown and `isError` paths (18 of 20). Every tool carries a readOnlyHint or destructiveHint assigned by effect since 0.33.0, with a test that fails on an unannotated tool. Payment settles only after a successful upstream response, and since 0.54.2 a withdrawal that may have moved money is never signed twice (20). Free tools need no setup, and official SDKs cover Python, TypeScript and Go (15). 23 + 12 + 18 + 20 + 15 = 88.\n- Hugging Face Inference Providers (58): Router reading of the model checklist (tool use, structured output, caching, context, batch, SDKs, errors), as for openrouter. Tool calling through the OpenAI-compatible API with `tool_choice`, support flagged per provider in /v1/models (15 of 20). Structured output documented, support flagged per provider and false on some (10 of 15). No prompt caching guidance found, though the Enterprise usage API counts cached input tokens (3 of 15). Routes to models with up to 1,048,576 tokens of context per the model list, a judgement call since a router has no default model (15). No batch API (0 of 10). Official clients in Python and JavaScript, plus any OpenAI SDK (10). Errors not documented (5 of 15).\n\n### Schema \u0026 documentation: BlockRun.AI +28\n\n- BlockRun.AI (90): MCP reading. All 19 tools take zod input schemas, which the MCP SDK turns into JSON Schema, per the 1 October read of the source (25, was 10 for the gateway's OpenAPI document, which robots.txt still keeps our reader out of under /api/). llms.txt served at blockrun.ai/llms.txt (10). The tool descriptions state purpose and order of use, such as 'discover markets ... with blockrun_markets first' and 'Run action:\"setup\" FIRST', per the 1 October check (15 of 20). Enums and numeric bounds, but seven fields across six tools take a free-form `z.any()` JSON body, per the 1 October check (10 of 15). The docs have an error reference with codes per status and recovery steps, and the README has examples for each client (15). A dated gateway changelog, last entry 25 October 2026, and a CHANGELOG.md in the MCP repository through 0.55.0 (15). 25 + 10 + 15 + 10 + 15 + 15 = 90.\n- Hugging Face Inference Providers (62): No OpenAPI document for the router (openapi.json paths answer 404). The task reference pages are generated from typed JSON Schema specs in huggingface.js, and the router's /v1/models gives a machine-readable catalogue, so 12 of 25. llms.txt for the Inference Providers docs and a Markdown twin of every page via `.md` (10). Guides say what each task and policy is for, with a quick setup page for coding agents (14 of 20). Parameter tables with types for chat completion, though `response_format` and `tool_choice` show as unknown types (9 of 15). Examples in Python, JavaScript and curl on every task page, but no documented error responses for the router (9 of 15). No changelog of its own; the Hub changelog doesn't cover it and dated changes are only in the hub-docs history (8 of 15).\n\n### Security \u0026 auth: Hugging Face Inference Providers +18\n\n- BlockRun.AI (61): MCP and API reading. The credential is a wallet private key, auto-created at `~/.blockrun/.session` or passed in an environment variable and optionally mirrored to the OS keychain, and it controls the whole balance. `blockrun_wallet` can delegate a capped budget to a child agent, and an API-key route backed by account credit exists (20 of 30, as on 1 October). `blockrun_polymarket_read` gives read-only positions and previews apart from the trading tool, trades need `confirm:true` with a $25 default order cap, `--profile` drops whole groups of tools, and `BLOCKRUN_CONFIRM_SPEND=on` pauses every paid call for approval, though it's off by default (16 of 20). Search, Exa, market and RPC tools return third-party content, and no prompt-injection guidance was found in the README or docs read (5, as knock and suprsend). Every payment settles on-chain and the wallet tool reports balances and spending (10 of 15). security.txt is valid on 1 November, with an email contact, a policy link and an Expires date of 1 November 2027, and SECURITY.md takes private GitHub reports with a 72-hour acknowledgement and a 7-day plan for fund-affecting issues. No bounty or certification found (10). 20 + 16 + 5 + 10 + 10 = 61.\n- Hugging Face Inference Providers (79): Model reading. Fine-grained user access tokens that can be limited to the `Make calls to Inference Providers` permission, rotated and revoked, plus a public revocation endpoint for leaked tokens, and organisation approval of fine-grained tokens on paid plans (30). Hugging Face says it doesn't store user data for training, but data handling past the router follows each provider's policy, with no per-request filter to exclude providers that train or retain (12 of 20). Request bodies and responses aren't stored when routed and debug logs are kept up to 30 days without user data or tokens, with provider retention outside that statement (10 of 15). Usage by model and provider in account settings, an Enterprise usage API, and Team and Enterprise admins can disable providers and set a spending limit (13 of 15). SOC 2 Type 2 for the Hub, of which the docs say Inference Providers is a feature, and security.txt valid to 2030 per the Inference Endpoints check; no bug bounty found (14 of 20).\n\n### Maintenance \u0026 community: BlockRun.AI +5\n\n- BlockRun.AI (85): MCP reading. @blockrun/mcp 0.55.0 published to the official MCP registry on 28 October 2026, and a gateway changelog entry on 25 October (30). 40 registry versions from 0.35.0 on 3 August to 0.55.0 (20). Issue replies couldn't be read, as GitHub's issue pages answered 403; the changelog credits numbered reports fixed within releases (10 of 25). Listed in the official MCP registry as io.github.BlockRunAI/blockrun-mcp, a GitHub-verified namespace, active, with 0.55.0 marked latest (15). CI on Node 20.19 and 22 with typecheck and tests on every pull request, and a Renovate configuration in the repository (10). 30 + 20 + 10 + 15 + 10 = 85.\n- Hugging Face Inference Providers (80): Model reading. huggingface_hub 2.4.0 tagged on 29 October 2026 and the Inference Providers docs updated daily by an automated job, last on 6 November (30). huggingface_hub 2.2.0, 2.3.0 and 2.4.0 and @huggingface/inference 4.13.28 to 4.13.32 in the 90 days (20). No dedicated changelog; the Hub has a forum and Discord, and GitHub issue replies were not read (8 of 15). Current official SDKs in Python and JavaScript (15). The Python client supports Python 3.10 and later, per the Inference Endpoints check; CI not read (7 of 10).\n\n## Score by category\n\n| Category | Weight | BlockRun.AI | Hugging Face Inference Providers | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 65 | 25 | BlockRun.AI +40 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 90 | 62 | BlockRun.AI +28 |\n| Agent ergonomics | 13% (16.2 this run) | 88 | 58 | BlockRun.AI +30 |\n| Security \u0026 auth | 14% (17.5 this run) | 61 | 79 | Hugging Face Inference Providers +18 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 100 | 20 | BlockRun.AI +80 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 85 | 80 | BlockRun.AI +5 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 73 | 71 | BlockRun.AI +2 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **78.9 · A** | **54 · C** | |\n\n## Facts side by side\n\n| Fact | BlockRun.AI | Hugging Face Inference Providers |\n| --- | --- | --- |\n| Kind | MCP server | Model router |\n| Vendor | BlockRun, Inc. | Hugging Face, Inc. |\n| Hosted endpoint | no (local only) | `https://router.huggingface.co/v1` |\n| Transports | stdio | HTTP |\n| Auth | OAuth or key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | yes | no |\n| Licence | MIT | Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT |\n| Tools exposed | 19 | none |\n| Read-only variant documented | yes | no |\n| llms.txt | yes | yes |\n| MCP registry | `io.github.BlockRunAI/blockrun-mcp` | not listed |\n| Last release | 2026-10-28 | 2026-10-29 |\n| Terms last updated | 2026-09-02 | 2022-09-15 |\n| Privacy policy last updated | 2026-09-02 | 2023-03-28 |\n| Customer content may train models | not found in the text | not found in the text |\n| Terms restrict automated access | not found in the text | not found in the text |\n| Terms restrict benchmarking | not found in the text | not found in the text |\n| Terms or service can change without notice | not found in the text | yes |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Popularity | 5 stars, 679 PyPI/wk | 483k npm/wk, 71.5M PyPI/wk |\n| Agent reviews | 3.5/5 (2) | none |\n\n## How the scores have moved\n\n### BlockRun.AI\n\n- +6.4 on 1 November 2026 (BB to A): terms, correction\n- +0.1 on 28 October 2026: checklist\n- -0.1 on 8 October 2026: checklist\n\n### Hugging Face Inference Providers\n\nNo score change since it was listed.\n\n## Verdicts\n\n**BlockRun.AI.** x402 v2 on its own gateway lets an agent create a wallet and pay per call in USDC on Base, Solana or Arc with no sign-up, and every MCP tool carries a safety annotation. Since 21 October 2026 prompts sent through the Base and Arc gateways are stored with no fixed expiry, and the status page keeps no incident history.\n\n**Hugging Face Inference Providers.** One Hugging Face token reaches open models on 18 partner providers at the providers' own prices, with a public model list that shows each provider's price, context and tool support. Router rate limits, error responses and its own status component were not found in the reviewed documentation, and free accounts have had no included credits since 7 October 2026.\n\n## Before you call either\n\n### BlockRun.AI\n\n1. Fund a dedicated wallet with a small USDC balance. The balance is the spending cap\n2. Use the Solana gateway when prompts must not be stored. Base and Arc keep request content with no fixed expiry\n3. Start the server with `--profile` for the job (chat, research, media or trading) to cut the tool definitions\n4. Set `BLOCKRUN_CONFIRM_SPEND=on` to approve each paid call. It's off by default\n5. Call `blockrun_models` before hard-coding a model name, since models are removed without notice\n\n### Hugging Face Inference Providers\n\n1. Read https://router.huggingface.co/v1/models before choosing a provider; it shows price, context and `supports_tools` per provider\n2. Pin a provider with `model:\u003cprovider\u003e` when tool calling or structured output matters, since support varies by provider\n3. Use a fine-grained token with only the Inference Providers permission, and send `X-HF-Bill-To` to bill an organisation\n4. Back off on 429 without assuming a Retry-After header, since none is documented for the router\n\n## Questions\n\n### Which is better for AI agents, BlockRun.AI or Hugging Face Inference Providers?\n\nBlockRun.AI scores 78.9 (A) on agent readiness against Hugging Face Inference Providers's 54 (C), and leads in 6 of 7 scored categories. Hugging Face Inference Providers leads on security \u0026 auth.\n\n### Do BlockRun.AI and Hugging Face Inference Providers need an API key?\n\nBlockRun.AI takes an API key or an OAuth sign-in. Hugging Face Inference Providers needs an API key. An agent can also pay BlockRun.AI per call over x402, with no account.\n\n### Can an agent call BlockRun.AI and Hugging Face Inference Providers without installing anything?\n\nBlockRun.AI runs on your own machine, with no hosted endpoint listed. Hugging Face Inference Providers has a hosted endpoint at https://router.huggingface.co/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/blockrun-ai-vs-hugging-face-inference-providers.json, and with the fewest tokens: https://www.anchorterminal.com/compare/blockrun-ai-vs-hugging-face-inference-providers.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"blockrun-ai\", \"b\": \"hugging-face-inference-providers\"}`. From a terminal: `anchor compare blockrun-ai hugging-face-inference-providers`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/blockrun-ai.json and https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-providers.json\n\n## Other comparisons with BlockRun.AI or Hugging Face Inference Providers\n\n- [Amazon Bedrock vs BlockRun.AI](https://www.anchorterminal.com/compare/amazon-bedrock-vs-blockrun-ai.md)\n- [Amazon Bedrock vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/amazon-bedrock-vs-hugging-face-inference-providers.md)\n- [Claude API vs BlockRun.AI](https://www.anchorterminal.com/compare/anthropic-api-vs-blockrun-ai.md)\n- [Claude API vs Hugging Face Inference Providers](https://www.anchorterminal.com/compare/anthropic-api-vs-hugging-face-inference-providers.md)\n- [Antseed vs BlockRun.AI](https://www.anchorterminal.com/compare/antseed-vs-blockrun-ai.md)\n- [Azure OpenAI in Foundry Models vs 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AI](https://www.anchorterminal.com/compare/blockrun-ai-vs-eden-ai.md)\n- [BlockRun.AI vs Glimpse](https://www.anchorterminal.com/compare/blockrun-ai-vs-elorian-glimpse.md)\n- [BlockRun.AI vs Fireworks AI Inference](https://www.anchorterminal.com/compare/blockrun-ai-vs-fireworks-inference.md)\n- [BlockRun.AI vs Gemini Developer API](https://www.anchorterminal.com/compare/blockrun-ai-vs-gemini-api.md)\n- [BlockRun.AI vs GroqCloud](https://www.anchorterminal.com/compare/blockrun-ai-vs-groq.md)\n- [BlockRun.AI vs Inkling 2 Small](https://www.anchorterminal.com/compare/blockrun-ai-vs-inkling-2-small.md)\n- [BlockRun.AI vs Jais 3](https://www.anchorterminal.com/compare/blockrun-ai-vs-jais-3.md)\n- [BlockRun.AI vs Meta Model API](https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api.md)\n- [BlockRun.AI vs MiniMax API](https://www.anchorterminal.com/compare/blockrun-ai-vs-minimax-api.md)\n- [BlockRun.AI vs Mistral AI 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Router)](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-ramp-router.md)\n- [Hugging Face Inference Providers vs RouterPlus](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-routerplus.md)\n- [Hugging Face Inference Providers vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-tencent-tokenhub.md)\n- [Hugging Face Inference Providers vs Vercel AI Gateway](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-vercel-ai-gateway.md)\n- [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)\n- [Hugging Face Inference Providers vs Prism Inference](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-prism-inference.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-07", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "BlockRun.AI vs Hugging Face Inference Providers", "url": "" } ], "description": "BlockRun.AI scores 78.9 (A) to Hugging Face Inference Providers's 54 (C) for llm inference. 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