{ "data": { "a": { "slug": "hugging-face-inference-endpoints", "name": "Hugging Face Inference Endpoints", "vendor": "Hugging Face, Inc.", "vendorUrl": "https://huggingface.co", "kind": "http-api", "category": "gpu-compute", "summary": "Managed Hugging Face service that deploys a Hub model as a dedicated, autoscaling HTTPS endpoint on AWS, Azure or Google Cloud, using vLLM, TGI, SGLang, llama.cpp, TEI or a custom container. Managed by REST API, Python client, CLI or MCP.", "url": "https://www.anchorterminal.com/tools/hugging-face-inference-endpoints", "markdownUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-endpoints.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-endpoints.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-endpoints.json", "repo": "https://github.com/huggingface/hf-endpoints-documentation", "license": "Proprietary service under the Hugging Face Terms of Service. The `huggingface_hub` Python client and CLI are Apache-2.0", "transports": [ "http" ], "remoteUrl": "https://api.endpoints.huggingface.cloud", "packages": [ { "registry": "pypi", "name": "huggingface_hub" } ], "auth": "mixed", "authNotes": "Hugging Face access token sent as `Authorization: Bearer $HF_TOKEN` to the management API and to each endpoint. Tokens are created in the account settings in a browser and can be fine-grained, read or write. The MCP server uses OAuth through huggingface.co (authorisation code with PKCE, device code, dynamic client registration) with `read-endpoints` and `write-endpoints` scopes. `GET /v2/provider` and the catalogue list need no token. Access is self-serve, with quota requests for larger instances.", "pricing": "usage", "pricingNotes": "Usage priced by instance hour, billed per minute while a replica is initialising or running. GPUs run from $0.50 an hour (T4) to $10 (H100 on GCP), CPUs from $0.033. No free tier or trial was found. The docs require a payment method and credits before deploying, and the pricing page says an active subscription. Paused endpoints and endpoints at zero replicas aren't billed for compute (https://huggingface.co/docs/inference-endpoints/support/pricing).", "priceSummary": "$0.033 / vCPU-hr", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the Inference Endpoints docs, the two OpenAPI documents or the pricing page (checked 2026-10-08).", "endpoints": [] }, "toolCount": 19, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": 60014944, "asOf": "2026-10-08" }, "docsUrl": "https://huggingface.co/docs/inference-endpoints/index", "llmsTxt": "https://huggingface.co/docs/inference-endpoints/llms.txt", "openapi": "https://api.endpoints.huggingface.cloud/openapi.json", "capabilities": [ "compute.gpu", "compute.endpoints", "compute.containers" ], "tags": [ "hosted", "usage-priced", "python", "cli", "mcp", "oauth", "openapi", "llms-txt", "status-page", "soc2", "enterprise" ], "lastRelease": "2026-10-08", "graded": true, "anchor": { "graded": true, "score": 64.5, "grade": "B", "agentReady": false, "rank": 349, "ranked": true, "rankOf": 950, "categoryRank": 3, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 62, "maintenance": 80, "payments": 20, "reliability": 63, "schema": 73, "security": 83, "transparency": 68 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "OAuth scopes separate reading endpoints from writing them, both OpenAPI documents are public, and the unauthenticated `/v2/provider` route lists every instance with its hourly price. An account needs a payment method and credits before the first deployment, no rate limits or SLA were found for the management API, and the docs price table disagrees with the live list in places.", "bestFor": "Teams whose models already live on the Hugging Face Hub and who want a dedicated endpoint on a named cloud and region with standard open-source engines.", "strengths": [ "Public OpenAPI 3.1 documents for the management API (46 operations) and the catalogue API (3), plus llms.txt and a Markdown twin of every docs page", "The MCP server at endpoints.huggingface.co/mcp uses OAuth with `read-endpoints` and `write-endpoints` scopes, PKCE and dynamic client registration", "`GET /v2/provider` needs no token and returns each instance type by cloud and region with status and price per hour", "The MCP `delete_endpoint` tool returns a preview and deletes only on a second call with `confirm: true`", "The Inference Endpoints API component on status.huggingface.co shows 100 per cent uptime over the 90 days to 8 October 2026" ], "weaknesses": [ "No free tier. The docs require a payment method and credits, and replicas are billed while initialising as well as running", "No rate limits, SLA or idempotency keys were found for the management API, and its OpenAPI document lists only 200 responses on 43 of 46 operations", "The docs price table and the live provider list disagree. Inferentia2 x1 is $0.75 in the docs and $1.95 in the API, and AWS H200 is listed in the docs and marked deprecated in the API", "A start from zero replicas takes minutes by the docs' own account, and the proxy answers 503 until a replica is ready", "The Hub outage of 16 July 2026 took the Inference Endpoints UI down for 1 hour 37 minutes" ], "agentNotes": [ "Call `GET https://api.endpoints.huggingface.cloud/v2/provider` first and pick an instance whose `status` is `available`. The docs table lists types the API marks deprecated or not available", "Send `X-Scale-Up-Timeout: 600` on requests to an endpoint that scales to zero, or handle 503 while the first replica starts", "Set `scaleToZeroTimeout` yourself. The docs give a default of 1 hour and the OpenAPI document says 15 minutes", "Pause or delete an endpoint when the job is done. Billing covers every minute a replica is initialising or running", "Give the agent a fine-grained token or the `read-endpoints` scope unless it must deploy. Endpoints are private by default and take the same Hugging Face token as a bearer" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 64.5 } ], "editorialScores": { "ergonomics": 62, "maintenance": 80, "payments": 20, "reliability": 63, "schema": 73, "security": 83, "transparency": 68 }, "provenanceScore": 67 }, "connect": { "install": "pip install huggingface_hub", "http": "curl \"https://api.endpoints.huggingface.cloud/v2/endpoint/$NAMESPACE\" \\\n -H \"Authorization: Bearer $HF_TOKEN\"" }, "letme": { "capability": "https://letme.dev/compute.gpu", "tool": "https://letme.dev/hugging-face-inference-endpoints" }, "area": "models", "unitPrices": [ { "item": "NVIDIA T4 16 GB x1 (AWS, GCP)", "unit": "gpu-hour", "usd": 0.5, "note": "Billed per minute while initialising or running" }, { "item": "NVIDIA L4 24 GB x1 (AWS)", "unit": "gpu-hour", "usd": 0.8, "note": "$0.70 on GCP us-east4" }, { "item": "NVIDIA A10G 24 GB x1 (AWS)", "unit": "gpu-hour", "usd": 1, "note": "us-east-1 and eu-west-1" }, { "item": "NVIDIA L40S 48 GB x1 (AWS)", "unit": "gpu-hour", "usd": 1.8, "note": "us-east-1" }, { "item": "NVIDIA A100 80 GB x1 (AWS)", "unit": "gpu-hour", "usd": 2.5, "note": "$3.60 on GCP us-east4" }, { "item": "NVIDIA RTX PRO 6000 Blackwell 96 GB x1 (AWS)", "unit": "gpu-hour", "usd": 2.75, "note": "us-east-2, in the live provider list and absent from the docs table" }, { "item": "NVIDIA H200 141 GB x1 (GCP)", "unit": "gpu-hour", "usd": 5, "note": "us-south1. The AWS H200 in us-west-2 is marked deprecated in the API" }, { "item": "NVIDIA H100 80 GB x1 (GCP)", "unit": "gpu-hour", "usd": 10, "note": "us-east4. The AWS H100 at $4.50 is deprecated from December 2025" }, { "item": "Intel Sapphire Rapids x1, 1 vCPU and 2 GB (AWS)", "unit": "vcpu-hour", "usd": 0.033, "note": "$0.050 on GCP and $0.060 on Azure Intel Xeon" } ], "provenance": { "legalEntity": "Hugging Face, Inc.", "domain": "huggingface.co", "domainRegistered": "", "endpointOnVendorDomain": false, "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": "2026-10-08", "notes": [ "The Terms of Service (effective 15 September 2022) name Hugging Face, Inc., a Delaware corporation, list Inference Endpoints among the services they cover and are governed by New York law. They link Supplemental Terms (effective 28 April 2025) as a PDF, of which our reader extracted only the first page.", "The privacy policy (effective 28 March 2023) names Hugging Face, Inc. and its EU establishment Hugging Face, SAS, 9 rue des Colonnes, 75002 Paris, and lists 11 subprocessors with countries. The Inference Endpoints security page points to it.", "The management API answers at api.endpoints.huggingface.cloud and deployed endpoints at subdomains of endpoints.huggingface.cloud, a second domain of the vendor's. The catalogue API and the MCP server are on endpoints.huggingface.co.", "huggingface.co/.well-known/security.txt gives security@huggingface.co and expires on 1 July 2030. endpoints.huggingface.co/.well-known/security.txt returns 404.", "status.huggingface.co is a Better Stack page with separate components for the Inference Endpoints UI and API.", "The changelog at huggingface.co/changelog covers the whole Hub. Inference Endpoints has no changelog of its own. Dated changes are in the docs repository's commit history.", "rdap.org returned 404 for huggingface.co, so the registration date is unrecorded." ], "score": 67 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/hugging-face-inference-endpoints.json", "live": { "slug": "hugging-face-inference-endpoints", "probe": { "target": "https://api.endpoints.huggingface.cloud", "method": "get", "lastAt": "2026-10-10T02:07:11.764959069Z", "lastOk": true, "lastStatus": 200, "lastMs": 258, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 256, "p95ms24h": 323, "samples24h": 191, "samples30d": 191, "days": [ { "date": "2026-10-09", "probes": 169, "ok": 169 }, { "date": "2026-10-10", "probes": 22, "ok": 22 } ] }, "vendorStatus": { "page": "https://status.huggingface.co", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-10T00:50:41.53884912Z" }, "versions": [ { "registry": "pypi", "name": "huggingface_hub", "version": "2.2.0", "released": "2026-10-08", "seenAt": "2026-10-09T16:58:14.645195375Z" } ], "githubStars": 27, "pypiWeekly": 59965969, "securityTxt": { "url": "https://huggingface.co/.well-known/security.txt", "state": "valid", "expires": "2030-07-01T08:42:00.000Z", "checkedAt": "2026-10-09T15:39:14.256871095Z" }, "llmsTxt": { "url": "https://huggingface.co/docs/inference-endpoints/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-09T14:02:08.794740773Z" }, "pages": [ { "url": "https://huggingface.co/changelog", "kind": "changelog", "status": 200, "checkedAt": "2026-10-09T18:40:14.422489638Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "32d7960b5be2" }, { "url": "https://huggingface.co/docs/inference-endpoints/support/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-10-09T18:40:16.589495024Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "c01bd565eb56" }, { "url": "https://huggingface.co/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-09T18:40:18.579985408Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "b905cd71bf3c" }, { "url": "https://huggingface.co/terms-of-service", "kind": "terms", "status": 200, "checkedAt": "2026-10-09T18:40:20.536865147Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "53766473827f" } ], "updatedAt": "2026-10-10T02:07:11.764959069Z" } }, "answer": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Massed Compute's 42.3 (E), and leads in 6 of 7 scored categories.", "b": { "slug": "massed-compute", "name": "Massed Compute", "vendor": "Massed Compute", "vendorUrl": "https://massedcompute.com", "kind": "http-api", "category": "gpu-compute", "summary": "Massed Compute is a US GPU cloud that rents NVIDIA GPU virtual machines by the hour from hardware it owns, with bare metal and clusters by quote. Agents use its REST API or a hosted MCP server.", "url": "https://www.anchorterminal.com/tools/massed-compute", "markdownUrl": "https://www.anchorterminal.com/tools/massed-compute.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/massed-compute.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/massed-compute.json", "repo": "https://github.com/Massed-Compute/massed-compute-mcp", "license": "Proprietary service under Massed Compute's Terms \u0026 Conditions and End User Licence Agreement. The `massed-compute-mcp` wrapper on GitHub is MIT", "transports": [ "http", "streamable-http" ], "remoteUrl": "https://vm.massedcompute.com/api/v1", "packages": [ { "registry": "npm", "name": "massed-compute-mcp" }, { "registry": "pypi", "name": "massed-compute-mcp" } ], "auth": "mixed", "authNotes": "Self-serve. The owner signs up in a browser, verifies an email address and creates a named API token at vm.massedcompute.com/settings/api, choosing Full access or Read only. The token is shown once, travels as a Bearer header and is revoked from the token table. The same token works for the REST API and the MCP server. MCP clients that send no token get a 401 with an OAuth challenge, and the owner signs in and approves full or read-only access. Grants are listed and revoked under Connected Apps. The older marketplace API on `api.massedcompute.com` issues keys only through support.", "pricing": "usage", "pricingNotes": "No free tier or trial credit was found. The owner adds a card or pays in crypto, makes a first deposit and sets an auto-recharge threshold of at least $5 before any launch. Running VMs are debited every minute at a published hourly rate. On 9 October 2026 a single A30 was $0.35 an hour, an RTX A6000 $0.57, an L40S $0.97, an A100 80 GB $1.35 and an H100 80 GB $2.73. No bandwidth charge per the pricing page. Bare metal, clusters and the marketplace API are by quote (https://vm.massedcompute.com/pricing).", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs, the two OpenAPI files, the MCP server card or the pricing page. The billing docs describe crypto top-ups made by the account owner, which is not a machine payment protocol (checked 2026-10-09).", "endpoints": [] }, "toolCount": 17, "popularity": { "githubStars": 1, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-09" }, "docsUrl": "https://vm-docs.massedcompute.com", "llmsTxt": "https://massedcompute.com/llms.txt", "openapi": "https://vm-docs.massedcompute.com/redocusaurus/plugin-redoc-0.yaml", "registryName": "io.github.Massed-Compute/mcp", "capabilities": [ "compute.gpu" ], "tags": [ "hosted", "usage-priced", "openapi", "mcp", "oauth", "api-key", "read-only-keys", "node", "python", "card-required", "crypto-payments", "closed-source" ], "lastRelease": "2026-07-24", "graded": true, "anchor": { "graded": true, "score": 42.3, "grade": "E", "agentReady": false, "rank": 896, "ranked": true, "rankOf": 950, "categoryRank": 18, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 56, "maintenance": 51, "payments": 20, "reliability": 20, "schema": 69, "security": 61, "transparency": 61 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-09" }, "negative": -5, "negativeNotes": [ "8 June 2026. The `instances_list` and `instances_get` MCP tools returned the cleartext VM password although their descriptions said it was redacted. Fixed in `massed-compute-mcp` 1.0.3 and later moved server-side, with rotation advice in the changelog. No GitHub advisory is published. Fixed and documented, so 3 points (https://github.com/Massed-Compute/massed-compute-mcp/blob/main/CHANGELOG.md).", "9 October 2026. The product page lists SDKs for Go and a Terraform provider, webhooks and per-project quotas. None appears in the docs, the OpenAPI file or the vendor's public GitHub organisation. 2 points (https://massedcompute.com/products/inventory-api/)." ], "verdict": "The hosted MCP server and REST API accept OAuth grants or API tokens in read-only and full-access tiers, and all 17 tools carry typed schemas and safety annotations in a public server card. No status page, rate limit figures or API changelog were found, a launch has no idempotency key, and the governing terms could not be read.", "bestFor": "Agents that rent whole GPU VMs by the hour for training, fine-tuning or a model server and want a small MCP tool set with a read-only mode.", "strengths": [ "API tokens and OAuth grants come in read-only and full-access tiers, and tokens are revoked one at a time in the console", "A public server card lists all 17 MCP tools with JSON Schema inputs and `readOnlyHint`, `destructiveHint` and `idempotentHint` annotations", "Hourly prices for 23 GPU configurations, from $0.35 for an A30 to $52.80 for eight B300s, are public without a login", "A public OpenAPI 3.0 file covers the 14 REST operations at `https://vm.massedcompute.com/api/v1`", "The sub-processor list names 23 processors with locations, was updated on 10 September 2026 and has an RSS feed for changes" ], "weaknesses": [ "No status page, incident history or security.txt was found on any of the vendor's hosts", "A 429 answer exists but no rate limit figures are published, and the OpenAPI file documents no error response", "`POST /instance/launch` has no idempotency key, so a retried launch can start a second billed VM", "Until a fix dated 8 June 2026, `instances_list` and `instances_get` returned the cleartext VM password although their descriptions said it was redacted", "The product page lists Go and Terraform SDKs and webhooks that the docs, the OpenAPI file and the public GitHub organisation do not show", "A stopped instance is billed at the full hourly rate. Only termination ends billing, and it deletes the data" ], "agentNotes": [ "Use `https://vm.massedcompute.com/api/v1`. The older docs at api-docs.massedcompute.com describe a separate marketplace API on `api.massedcompute.com` whose keys come from support.", "Ask the owner for a read-only token unless the task must launch or terminate. Read-only credentials cannot call launch, restart, terminate or SSH key changes.", "Call `gpu_inventory_list` and `images_list` before `instances_launch`. Product names and image IDs are free values, and SXM-only images do not run on PCIe cards.", "Expect 402 on launch until the owner has added credit and set a recharge amount and threshold. List instances before retrying a launch.", "Terminate to end billing. Stopping keeps the full hourly charge, and termination deletes the instance data." ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "E", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 42.3 } ], "editorialScores": { "ergonomics": 56, "maintenance": 51, "payments": 20, "reliability": 20, "schema": 69, "security": 61, "transparency": 53 }, "provenanceScore": 68 }, "connect": { "install": "npm install -g massed-compute-mcp", "claudeCode": "claude mcp add --transport http massed-compute https://vm.massedcompute.com/api/mcp --header \"Authorization: Bearer MC_TOKEN\"", "config": { "mcpServers": { "massed-compute": { "headers": { "Authorization": "Bearer MC_TOKEN" }, "type": "http", "url": "https://vm.massedcompute.com/api/mcp" } } } }, "letme": { "capability": "https://letme.dev/compute.gpu", "tool": "https://letme.dev/massed-compute" }, "area": "models", "unitPrices": [ { "item": "A30 24 GB VM", "unit": "gpu-hour", "usd": 0.35, "note": "Billed per minute" }, { "item": "RTX A5000 24 GB VM", "unit": "gpu-hour", "usd": 0.44, "note": "Billed per minute" }, { "item": "RTX A6000 48 GB VM", "unit": "gpu-hour", "usd": 0.57, "note": "Billed per minute. An alternative configuration is $0.55" }, { "item": "RTX 6000 Ada 48 GB VM", "unit": "gpu-hour", "usd": 0.79, "note": "Billed per minute" }, { "item": "L40 48 GB VM", "unit": "gpu-hour", "usd": 0.86, "note": "Billed per minute" }, { "item": "RTX PRO 4500 Blackwell 32 GB VM", "unit": "gpu-hour", "usd": 0.92, "note": "Billed per minute" }, { "item": "L40S 48 GB VM", "unit": "gpu-hour", "usd": 0.97, "note": "Billed per minute" }, { "item": "A100 80 GB VM", "unit": "gpu-hour", "usd": 1.35, "note": "Billed per minute. SXM4 and DGX variants are $1.38" }, { "item": "RTX PRO 6000 Blackwell 96 GB VM", "unit": "gpu-hour", "usd": 2.19, "note": "Billed per minute" }, { "item": "H100 80 GB VM", "unit": "gpu-hour", "usd": 2.73, "note": "Billed per minute. H100 NVL is $3.11 and H100 SXM5 $3.14" }, { "item": "H200 NVL 141 GB VM", "unit": "gpu-hour", "usd": 3.62, "note": "Billed per minute" }, { "item": "B200 SXM6 VM, 8 GPUs", "unit": "gpu-hour", "usd": 5.43, "note": "Sold only as eight GPUs at $43.46 an hour. Our division, rounded" }, { "item": "B300 SXM6 VM, 8 GPUs", "unit": "gpu-hour", "usd": 6.6, "note": "Sold only as eight GPUs at $52.80 an hour. Our division" } ], "provenance": { "legalEntity": "Massed Compute, Inc.", "domain": "massedcompute.com", "domainRegistered": "2021-10-28", "endpointOnVendorDomain": true, "terms": "https://massedcompute.com/legal/terms-conditions/", "privacy": "https://massedcompute.com/legal/privacy-policy/", "statusPage": "", "changelog": "https://github.com/Massed-Compute/massed-compute-mcp/blob/main/CHANGELOG.md", "securityTxt": "none", "checked": "2026-10-09", "notes": [ "The Terms \u0026 Conditions page is the document the DPA calls the Principal Agreement. Its body is an embedded Termly viewer drawn by script, and we could not read it.", "The End User Licence Agreement, last updated 15 September 2026, names Massed Compute, Inc. of Las Vegas, Nevada, and applies Nevada law. The older docs site's footer says Massed Compute LLC.", "The privacy policy, last updated 22 July 2026, covers the website, a mobile application and the Services in general.", "The REST API and the MCP server answer at vm.massedcompute.com, on the vendor domain.", "/.well-known/security.txt answers 404 on massedcompute.com and on vm.massedcompute.com.", "RDAP for massedcompute.com gives a registration date of 2021-10-28.", "No status page was found on the site, the docs or the pricing page.", "The changelog linked is the MCP wrapper's. No API changelog was found.", "A Data Processing Agreement, last modified 27 March 2026, and a sub-processor list, last updated 10 September 2026, are published." ], "score": 68 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/massed-compute.json", "live": { "slug": "massed-compute", "probe": { "target": "https://vm.massedcompute.com/api/v1", "method": "get", "lastAt": "2026-10-10T02:07:15.43079726Z", "lastOk": true, "lastStatus": 200, "lastMs": 559, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 563, "p95ms24h": 1577, "samples24h": 107, "samples30d": 107, "days": [ { "date": "2026-10-09", "probes": 85, "ok": 85 }, { "date": "2026-10-10", "probes": 22, "ok": 22 } ] }, "versions": [ { "registry": "github", "name": "Massed-Compute/massed-compute-mcp", "version": "v1.1.0", "released": "2026-07-24", "seenAt": "2026-10-09T17:04:15.605664679Z" }, { "registry": "npm", "name": "massed-compute-mcp", "version": "1.1.0", "seenAt": "2026-10-09T17:04:14.528689429Z" }, { "registry": "pypi", "name": "massed-compute-mcp", "version": "1.1.0", "released": "2026-07-24", "seenAt": "2026-10-09T17:04:15.405015566Z" } ], "githubStars": 1, "npmWeekly": 37, "pypiWeekly": 20, "pages": [ { "url": "https://raw.githubusercontent.com/Massed-Compute/massed-compute-mcp/main/CHANGELOG.md", "kind": "changelog", "status": 200, "checkedAt": "2026-10-09T18:44:33.145231849Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "7fa22cb79429" }, { "url": "https://vm.massedcompute.com/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-10-09T18:47:14.582656601Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "fb389d9be37c" }, { "url": "https://massedcompute.com/legal/privacy-policy/", "kind": "privacy", "status": 200, "checkedAt": "2026-10-09T18:41:48.306296743Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "71fd70e07907" }, { "url": "https://massedcompute.com/legal/terms-conditions/", "kind": "terms", "status": 200, "checkedAt": "2026-10-09T18:41:50.386665594Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "0a8bdfcc06c0" } ], "updatedAt": "2026-10-10T02:07:15.43079726Z" } }, "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "Hugging Face, Inc.", "b": "Massed Compute", "name": "Vendor" }, { "a": "https://api.endpoints.huggingface.cloud", "b": "https://vm.massedcompute.com/api/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP, Streamable HTTP", "name": "Transports" }, { "a": "OAuth or key", "b": "OAuth or key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "not published", "b": "$5.43 per GPU-hour", "name": "Price for gpu compute" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary service under the Hugging Face Terms of Service. The `huggingface_hub` Python client and CLI are Apache-2.0", "b": "Proprietary service under Massed Compute's Terms \u0026 Conditions and End User Licence Agreement. The `massed-compute-mcp` wrapper on GitHub is MIT", "name": "Licence" }, { "a": "19", "b": "17", "name": "Tools exposed" }, { "a": "no", "b": "yes", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "not listed", "b": "io.github.Massed-Compute/mcp", "name": "MCP registry" }, { "a": "2026-10-08", "b": "2026-07-24", "name": "Last release" }, { "a": "2022-09-15", "b": "couldn't be read", "name": "Terms last updated" }, { "a": "2023-03-28", "b": "2026-07-22", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "couldn't be read", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "couldn't be read", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "couldn't be read", "name": "Terms restrict benchmarking" }, { "a": "yes", "b": "couldn't be read", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "couldn't be read", "name": "Arbitration or class-action waiver" }, { "a": "60M PyPI/wk", "b": "1 stars", "name": "Popularity" } ], "faq": [ { "answer": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Massed Compute's 42.3 (E), and leads in 6 of 7 scored categories.", "question": "Which is better for AI agents, Hugging Face Inference Endpoints or Massed Compute?" }, { "answer": "Both take an API key or an OAuth sign-in.", "question": "Do Hugging Face Inference Endpoints and Massed Compute need an API key?" }, { "answer": "Yes. Hugging Face Inference Endpoints has a hosted endpoint at https://api.endpoints.huggingface.cloud and Massed Compute at https://vm.massedcompute.com/api/v1.", "question": "Can an agent call Hugging Face Inference Endpoints and Massed Compute without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 63 against 20", "Agent ergonomics, 62 against 56", "Security \u0026 auth, 83 against 61", "Maintenance \u0026 community, 80 against 51", "Transparency \u0026 trust, 68 against 61" ], "also": [ "No incidents deducted, where Massed Compute loses 5 points for them" ], "goodFor": "Teams whose models already live on the Hugging Face Hub and who want a dedicated endpoint on a named cloud and region with standard open-source engines.", "slug": "hugging-face-inference-endpoints", "watchFor": "No free tier. The docs require a payment method and credits, and replicas are billed while initialising as well as running" }, { "aheadOn": null, "also": null, "goodFor": "Agents that rent whole GPU VMs by the hour for training, fine-tuning or a model server and want a small MCP tool set with a read-only mode.", "slug": "massed-compute", "watchFor": "No status page, incident history or security.txt was found on any of the vendor's hosts" } ], "job": { "capability": "compute.gpu", "name": "GPU compute" }, "others": [ { "json": "https://www.anchorterminal.com/compare/baseten-vs-hugging-face-inference-endpoints.json", "title": "Baseten vs Hugging Face Inference Endpoints", "url": "https://www.anchorterminal.com/compare/baseten-vs-hugging-face-inference-endpoints" }, { "json": "https://www.anchorterminal.com/compare/baseten-vs-massed-compute.json", "title": "Baseten vs Massed Compute", "url": "https://www.anchorterminal.com/compare/baseten-vs-massed-compute" }, { "json": "https://www.anchorterminal.com/compare/beam-vs-hugging-face-inference-endpoints.json", "title": "Beam vs Hugging Face Inference Endpoints", "url": "https://www.anchorterminal.com/compare/beam-vs-hugging-face-inference-endpoints" }, { "json": "https://www.anchorterminal.com/compare/beam-vs-massed-compute.json", "title": "Beam vs Massed Compute", "url": "https://www.anchorterminal.com/compare/beam-vs-massed-compute" }, { "json": "https://www.anchorterminal.com/compare/cerebrium-vs-hugging-face-inference-endpoints.json", "title": "Cerebrium vs Hugging Face Inference Endpoints", "url": "https://www.anchorterminal.com/compare/cerebrium-vs-hugging-face-inference-endpoints" }, { "json": "https://www.anchorterminal.com/compare/cerebrium-vs-massed-compute.json", "title": "Cerebrium vs Massed Compute", "url": "https://www.anchorterminal.com/compare/cerebrium-vs-massed-compute" }, { "json": "https://www.anchorterminal.com/compare/coreweave-vs-hugging-face-inference-endpoints.json", "title": "CoreWeave vs Hugging Face Inference Endpoints", "url": "https://www.anchorterminal.com/compare/coreweave-vs-hugging-face-inference-endpoints" }, { "json": "https://www.anchorterminal.com/compare/coreweave-vs-massed-compute.json", "title": "CoreWeave vs Massed Compute", "url": "https://www.anchorterminal.com/compare/coreweave-vs-massed-compute" }, { "json": "https://www.anchorterminal.com/compare/crusoe-cloud-vs-hugging-face-inference-endpoints.json", "title": "Crusoe Cloud vs Hugging Face Inference Endpoints", "url": "https://www.anchorterminal.com/compare/crusoe-cloud-vs-hugging-face-inference-endpoints" }, { "json": "https://www.anchorterminal.com/compare/crusoe-cloud-vs-massed-compute.json", "title": "Crusoe Cloud vs Massed Compute", "url": "https://www.anchorterminal.com/compare/crusoe-cloud-vs-massed-compute" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-hyperbolic.json", "title": "Hugging Face Inference Endpoints vs Hyperbolic", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-hyperbolic" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-koyeb.json", "title": "Hugging Face Inference Endpoints vs Koyeb", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-koyeb" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-lambda.json", "title": "Hugging Face Inference Endpoints vs Lambda Cloud", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-lambda" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-modal.json", "title": "Hugging Face Inference Endpoints vs Modal", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-modal" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-nebius-ai-cloud.json", "title": "Hugging Face Inference Endpoints vs Nebius AI Cloud", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-nebius-ai-cloud" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-northflank.json", "title": "Hugging Face Inference Endpoints vs Northflank", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-northflank" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-replicate-deploy.json", "title": "Hugging Face Inference Endpoints vs Replicate Deployments", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-replicate-deploy" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-runpod.json", "title": "Hugging Face Inference Endpoints vs Runpod", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-runpod" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-thunder-compute.json", "title": "Hugging Face Inference Endpoints vs Thunder Compute", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-thunder-compute" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-vast-ai.json", "title": "Hugging Face Inference Endpoints vs Vast.ai", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-vast-ai" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-verda.json", "title": "Hugging Face Inference Endpoints vs Verda", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/hyperbolic-vs-massed-compute.json", "title": "Hyperbolic vs Massed Compute", "url": "https://www.anchorterminal.com/compare/hyperbolic-vs-massed-compute" }, { "json": "https://www.anchorterminal.com/compare/koyeb-vs-massed-compute.json", "title": "Koyeb vs Massed Compute", "url": "https://www.anchorterminal.com/compare/koyeb-vs-massed-compute" }, { "json": "https://www.anchorterminal.com/compare/lambda-vs-massed-compute.json", "title": "Lambda Cloud vs Massed Compute", "url": "https://www.anchorterminal.com/compare/lambda-vs-massed-compute" }, { "json": "https://www.anchorterminal.com/compare/massed-compute-vs-modal.json", "title": "Massed Compute vs Modal", "url": "https://www.anchorterminal.com/compare/massed-compute-vs-modal" }, { "json": "https://www.anchorterminal.com/compare/massed-compute-vs-nebius-ai-cloud.json", "title": "Massed Compute vs Nebius AI Cloud", "url": "https://www.anchorterminal.com/compare/massed-compute-vs-nebius-ai-cloud" }, { "json": "https://www.anchorterminal.com/compare/massed-compute-vs-northflank.json", "title": "Massed Compute vs Northflank", "url": "https://www.anchorterminal.com/compare/massed-compute-vs-northflank" }, { "json": "https://www.anchorterminal.com/compare/massed-compute-vs-replicate-deploy.json", "title": "Massed Compute vs Replicate Deployments", "url": "https://www.anchorterminal.com/compare/massed-compute-vs-replicate-deploy" }, { "json": "https://www.anchorterminal.com/compare/massed-compute-vs-runpod.json", "title": "Massed Compute vs Runpod", "url": "https://www.anchorterminal.com/compare/massed-compute-vs-runpod" }, { "json": "https://www.anchorterminal.com/compare/massed-compute-vs-thunder-compute.json", "title": "Massed Compute vs Thunder Compute", "url": "https://www.anchorterminal.com/compare/massed-compute-vs-thunder-compute" }, { "json": "https://www.anchorterminal.com/compare/massed-compute-vs-vast-ai.json", "title": "Massed Compute vs Vast.ai", "url": "https://www.anchorterminal.com/compare/massed-compute-vs-vast-ai" }, { "json": "https://www.anchorterminal.com/compare/massed-compute-vs-verda.json", "title": "Massed Compute vs Verda", "url": "https://www.anchorterminal.com/compare/massed-compute-vs-verda" } ], "scores": [ { "by": 43, "edge": "hugging-face-inference-endpoints", "hugging-face-inference-endpoints": 63, "key": "reliability", "massed-compute": 20, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 4, "edge": "hugging-face-inference-endpoints", "hugging-face-inference-endpoints": 73, "key": "schema", "massed-compute": 69, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 6, "edge": "hugging-face-inference-endpoints", "hugging-face-inference-endpoints": 62, "key": "ergonomics", "massed-compute": 56, "name": "Agent ergonomics", "weight": 13 }, { "by": 22, "edge": "hugging-face-inference-endpoints", "hugging-face-inference-endpoints": 83, "key": "security", "massed-compute": 61, "name": "Security \u0026 auth", "weight": 14 }, { "by": 0, "edge": "", "hugging-face-inference-endpoints": 20, "key": "payments", "massed-compute": 20, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 29, "edge": "hugging-face-inference-endpoints", "hugging-face-inference-endpoints": 80, "key": "maintenance", "massed-compute": 51, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 7, "edge": "hugging-face-inference-endpoints", "hugging-face-inference-endpoints": 68, "key": "transparency", "massed-compute": 61, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Massed Compute's 42.3 (E), and leads in 6 of 7 scored categories. Both do gpu compute.", "verdicts": { "hugging-face-inference-endpoints": "OAuth scopes separate reading endpoints from writing them, both OpenAPI documents are public, and the unauthenticated `/v2/provider` route lists every instance with its hourly price. An account needs a payment method and credits before the first deployment, no rate limits or SLA were found for the management API, and the docs price table disagrees with the live list in places.", "massed-compute": "The hosted MCP server and REST API accept OAuth grants or API tokens in read-only and full-access tiers, and all 17 tools carry typed schemas and safety annotations in a public server card. No status page, rate limit figures or API changelog were found, a launch has no idempotency key, and the governing terms could not be read." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-massed-compute", "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-massed-compute.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-massed-compute.md", "slim": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-massed-compute.min.md" }, "markdown": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Massed Compute's 42.3 (E), and leads in 6 of 7 scored categories. Both do gpu compute.\n\n- Hugging Face Inference Endpoints: grade B, 64.5/100, rank #349 of 950. Markdown https://www.anchorterminal.com/tools/hugging-face-inference-endpoints.md · JSON https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-endpoints.json\n- Massed Compute: grade E, 42.3/100, rank #896 of 950. Markdown https://www.anchorterminal.com/tools/massed-compute.md · JSON https://www.anchorterminal.com/api/v1/tools/massed-compute.json\n- Best GPU and serverless compute for AI workloads: https://www.anchorterminal.com/best/gpu-compute/index.md\n- All 167 gpu compute comparisons: https://www.anchorterminal.com/compare/gpu-compute/index.md\n\n## Which one, for what\n\n### Hugging Face Inference Endpoints (B)\n\nGood for: Teams whose models already live on the Hugging Face Hub and who want a dedicated endpoint on a named cloud and region with standard open-source engines.\n\nAhead on:\n- Reliability, 63 against 20\n- Agent ergonomics, 62 against 56\n- Security \u0026 auth, 83 against 61\n- Maintenance \u0026 community, 80 against 51\n- Transparency \u0026 trust, 68 against 61\n\nAlso in its favour:\n- No incidents deducted, where Massed Compute loses 5 points for them\n\nWatch for: No free tier. The docs require a payment method and credits, and replicas are billed while initialising as well as running\n\n### Massed Compute (E)\n\nGood for: Agents that rent whole GPU VMs by the hour for training, fine-tuning or a model server and want a small MCP tool set with a read-only mode.\n\nWatch for: No status page, incident history or security.txt was found on any of the vendor's hosts\n\n\n## Score by category\n\n| Category | Weight | Hugging Face Inference Endpoints | Massed Compute | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 63 | 20 | Hugging Face Inference Endpoints +43 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 73 | 69 | Hugging Face Inference Endpoints +4 |\n| Agent ergonomics | 13% (16.2 this run) | 62 | 56 | Hugging Face Inference Endpoints +6 |\n| Security \u0026 auth | 14% (17.5 this run) | 83 | 61 | Hugging Face Inference Endpoints +22 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 20 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 80 | 51 | Hugging Face Inference Endpoints +29 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 68 | 61 | Hugging Face Inference Endpoints +7 |\n| Negative events | ≤15 | 0 | -5 | |\n| **Total** | | **64.5 · B** | **42.3 · E** | |\n\n## Facts side by side\n\n| Fact | Hugging Face Inference Endpoints | Massed Compute |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Hugging Face, Inc. | Massed Compute |\n| Hosted endpoint | `https://api.endpoints.huggingface.cloud` | `https://vm.massedcompute.com/api/v1` |\n| Transports | HTTP | HTTP, Streamable HTTP |\n| Auth | OAuth or key | OAuth or key |\n| Pricing | Pay per use | Pay per use |\n| Price for gpu compute | not published | $5.43 per GPU-hour |\n| x402 | no | no |\n| Licence | Proprietary service under the Hugging Face Terms of Service. The `huggingface_hub` Python client and CLI are Apache-2.0 | Proprietary service under Massed Compute's Terms \u0026 Conditions and End User Licence Agreement. The `massed-compute-mcp` wrapper on GitHub is MIT |\n| Tools exposed | 19 | 17 |\n| Read-only variant documented | no | yes |\n| llms.txt | yes | yes |\n| MCP registry | not listed | `io.github.Massed-Compute/mcp` |\n| Last release | 2026-10-08 | 2026-07-24 |\n| Terms last updated | 2022-09-15 | couldn't be read |\n| Privacy policy last updated | 2023-03-28 | 2026-07-22 |\n| Customer content may train models | not found in the text | couldn't be read |\n| Terms restrict automated access | not found in the text | couldn't be read |\n| Terms restrict benchmarking | not found in the text | couldn't be read |\n| Terms or service can change without notice | yes | couldn't be read |\n| Arbitration or class-action waiver | not found in the text | couldn't be read |\n| Popularity | 60M PyPI/wk | 1 stars |\n\n## Verdicts\n\n**Hugging Face Inference Endpoints.** OAuth scopes separate reading endpoints from writing them, both OpenAPI documents are public, and the unauthenticated `/v2/provider` route lists every instance with its hourly price. An account needs a payment method and credits before the first deployment, no rate limits or SLA were found for the management API, and the docs price table disagrees with the live list in places.\n\n**Massed Compute.** The hosted MCP server and REST API accept OAuth grants or API tokens in read-only and full-access tiers, and all 17 tools carry typed schemas and safety annotations in a public server card. No status page, rate limit figures or API changelog were found, a launch has no idempotency key, and the governing terms could not be read.\n\n## Before you call either\n\n### Hugging Face Inference Endpoints\n\n1. Call `GET https://api.endpoints.huggingface.cloud/v2/provider` first and pick an instance whose `status` is `available`. The docs table lists types the API marks deprecated or not available\n2. Send `X-Scale-Up-Timeout: 600` on requests to an endpoint that scales to zero, or handle 503 while the first replica starts\n3. Set `scaleToZeroTimeout` yourself. The docs give a default of 1 hour and the OpenAPI document says 15 minutes\n4. Pause or delete an endpoint when the job is done. Billing covers every minute a replica is initialising or running\n5. Give the agent a fine-grained token or the `read-endpoints` scope unless it must deploy. Endpoints are private by default and take the same Hugging Face token as a bearer\n\n### Massed Compute\n\n1. Use `https://vm.massedcompute.com/api/v1`. The older docs at api-docs.massedcompute.com describe a separate marketplace API on `api.massedcompute.com` whose keys come from support.\n2. Ask the owner for a read-only token unless the task must launch or terminate. Read-only credentials cannot call launch, restart, terminate or SSH key changes.\n3. Call `gpu_inventory_list` and `images_list` before `instances_launch`. Product names and image IDs are free values, and SXM-only images do not run on PCIe cards.\n4. Expect 402 on launch until the owner has added credit and set a recharge amount and threshold. List instances before retrying a launch.\n5. Terminate to end billing. Stopping keeps the full hourly charge, and termination deletes the instance data.\n\n## Questions\n\n### Which is better for AI agents, Hugging Face Inference Endpoints or Massed Compute?\n\nHugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Massed Compute's 42.3 (E), and leads in 6 of 7 scored categories.\n\n### Do Hugging Face Inference Endpoints and Massed Compute need an API key?\n\nBoth take an API key or an OAuth sign-in.\n\n### Can an agent call Hugging Face Inference Endpoints and Massed Compute without installing anything?\n\nYes. Hugging Face Inference Endpoints has a hosted endpoint at https://api.endpoints.huggingface.cloud and Massed Compute at https://vm.massedcompute.com/api/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-massed-compute.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-massed-compute.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"hugging-face-inference-endpoints\", \"b\": \"massed-compute\"}`. From a terminal: `anchor compare hugging-face-inference-endpoints massed-compute`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/hugging-face-inference-endpoints.json and https://www.anchorterminal.com/api/v1/tools/massed-compute.json\n\n## Other comparisons with Hugging Face Inference Endpoints or Massed Compute\n\n- [Baseten vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/baseten-vs-hugging-face-inference-endpoints.md)\n- [Baseten vs Massed Compute](https://www.anchorterminal.com/compare/baseten-vs-massed-compute.md)\n- [Beam vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/beam-vs-hugging-face-inference-endpoints.md)\n- [Beam vs Massed Compute](https://www.anchorterminal.com/compare/beam-vs-massed-compute.md)\n- [Cerebrium vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/cerebrium-vs-hugging-face-inference-endpoints.md)\n- [Cerebrium vs Massed Compute](https://www.anchorterminal.com/compare/cerebrium-vs-massed-compute.md)\n- [CoreWeave vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/coreweave-vs-hugging-face-inference-endpoints.md)\n- [CoreWeave vs Massed Compute](https://www.anchorterminal.com/compare/coreweave-vs-massed-compute.md)\n- [Crusoe Cloud vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/crusoe-cloud-vs-hugging-face-inference-endpoints.md)\n- [Crusoe Cloud vs Massed Compute](https://www.anchorterminal.com/compare/crusoe-cloud-vs-massed-compute.md)\n- [Hugging Face Inference Endpoints vs Hyperbolic](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-hyperbolic.md)\n- [Hugging Face Inference Endpoints vs Koyeb](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-koyeb.md)\n- [Hugging Face Inference Endpoints vs Lambda Cloud](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-lambda.md)\n- [Hugging Face Inference Endpoints vs Modal](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-modal.md)\n- [Hugging Face Inference Endpoints vs Nebius AI Cloud](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-nebius-ai-cloud.md)\n- [Hugging Face Inference Endpoints vs Northflank](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-northflank.md)\n- [Hugging Face Inference Endpoints vs Replicate Deployments](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-replicate-deploy.md)\n- [Hugging Face Inference Endpoints vs Runpod](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-runpod.md)\n- [Hugging Face Inference Endpoints vs Thunder Compute](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-thunder-compute.md)\n- [Hugging Face Inference Endpoints vs Vast.ai](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-vast-ai.md)\n- [Hugging Face Inference Endpoints vs Verda](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-verda.md)\n- [Hyperbolic vs Massed Compute](https://www.anchorterminal.com/compare/hyperbolic-vs-massed-compute.md)\n- [Koyeb vs Massed Compute](https://www.anchorterminal.com/compare/koyeb-vs-massed-compute.md)\n- [Lambda Cloud vs Massed Compute](https://www.anchorterminal.com/compare/lambda-vs-massed-compute.md)\n- [Massed Compute vs Modal](https://www.anchorterminal.com/compare/massed-compute-vs-modal.md)\n- [Massed Compute vs Nebius AI Cloud](https://www.anchorterminal.com/compare/massed-compute-vs-nebius-ai-cloud.md)\n- [Massed Compute vs Northflank](https://www.anchorterminal.com/compare/massed-compute-vs-northflank.md)\n- [Massed Compute vs Replicate Deployments](https://www.anchorterminal.com/compare/massed-compute-vs-replicate-deploy.md)\n- [Massed Compute vs Runpod](https://www.anchorterminal.com/compare/massed-compute-vs-runpod.md)\n- [Massed Compute vs Thunder Compute](https://www.anchorterminal.com/compare/massed-compute-vs-thunder-compute.md)\n- [Massed Compute vs Vast.ai](https://www.anchorterminal.com/compare/massed-compute-vs-vast-ai.md)\n- [Massed Compute vs Verda](https://www.anchorterminal.com/compare/massed-compute-vs-verda.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-10", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Hugging Face Inference Endpoints vs 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Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Hugging Face Inference Endpoints B 64.5", "Massed Compute E 42.3", "scores" ], "h1": "Hugging Face Inference Endpoints vs Massed Compute", "image": "https://www.anchorterminal.com/assets/og/compare-hugging-face-inference-endpoints-vs-massed-compute.png", "path": "/compare/hugging-face-inference-endpoints-vs-massed-compute", "published": "2026-10-01", "section": "tools", "title": "Hugging Face Inference Endpoints vs Massed Compute (2026)", "toc": null, "updated": "2026-10-09", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-massed-compute" }, "tokens": { "markdown": 3150, "slim": 830 }, "version": 1 }