{
  "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": 314,
        "ranked": true,
        "rankOf": 842,
        "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": "2026-10-09T11:46:30.653783864Z",
          "lastOk": true,
          "lastStatus": 200,
          "lastMs": 257,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 255,
          "p95ms24h": 300,
          "samples24h": 44,
          "samples30d": 44,
          "days": [
            {
              "date": "2026-10-09",
              "probes": 44,
              "ok": 44
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.huggingface.co",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-09T07:58:03.654181492Z"
        },
        "updatedAt": "2026-10-09T11:46:30.653783864Z"
      }
    },
    "answer": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Thunder Compute's 56.1 (C), and leads in 5 of 7 scored categories.",
    "b": {
      "slug": "thunder-compute",
      "name": "Thunder Compute",
      "vendor": "Thunder Compute",
      "vendorUrl": "https://www.thundercompute.com",
      "kind": "http-api",
      "category": "gpu-compute",
      "summary": "Thunder Compute is a US GPU cloud renting RTX A6000, L40, A100 and H100 instances by the minute and GPU sandboxes by the second. Agents use its REST API, a hosted MCP server with OAuth, or the `tnr` CLI.",
      "url": "https://www.anchorterminal.com/tools/thunder-compute",
      "markdownUrl": "https://www.anchorterminal.com/tools/thunder-compute.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/thunder-compute.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/thunder-compute.json",
      "repo": "https://github.com/Thunder-Compute/thunder-cli",
      "license": "Proprietary service under Thunder Compute's Terms and Conditions. The `tnr` CLI on GitHub is MIT",
      "transports": [
        "http",
        "streamable-http"
      ],
      "remoteUrl": "https://api.thundercompute.com:8443/v1",
      "packages": [
        {
          "registry": "go",
          "name": "github.com/Thunder-Compute/thunder-cli"
        },
        {
          "registry": "pypi",
          "name": "thunder-sandbox"
        }
      ],
      "auth": "mixed",
      "authNotes": "Self-serve. The hosted MCP server uses OAuth 2.0 with discovery. The first connection opens a browser to sign in and approve, tokens refresh, and the scopes are `instances:read`, `instances:write`, `snapshots:read`, `snapshots:write`, `sandboxes:read`, `sandboxes:write`, `billing:read` and `org:read`. The REST API takes a named API token as a Bearer header. Tokens are created and revoked one at a time in the console, or with the MCP `create_token` tool, and no token scopes were found. The CLI and the sandbox SDK read `TNR_API_TOKEN` for headless use. Price, specification, availability and template endpoints need no token.",
      "pricing": "usage",
      "pricingNotes": "No general free tier. Instances are billed by the minute while they run, paid by saved card or preloaded credit that is non-refundable. Per GPU an hour on 9 October 2026, RTX A6000 is $0.35, L40 $0.79, A100 80 GB $1.09 and H100 $3.20. Sandboxes are billed by the second and need access enabled by the vendor. Students with a US university email get $20 of credit for A6000 and L40 GPUs. Reserved capacity is by quote (https://www.thundercompute.com/pricing).",
      "priceSummary": "$0.04 / vCPU-hr",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the docs corpus, the OpenAPI document or the pricing page (checked 2026-10-09).",
        "endpoints": []
      },
      "toolCount": 28,
      "popularity": {
        "githubStars": 34,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-09"
      },
      "docsUrl": "https://www.thundercompute.com/docs",
      "llmsTxt": "https://www.thundercompute.com/docs/llms.txt",
      "openapi": "https://api.thundercompute.com:8443/openapi.json",
      "registryName": "io.github.Thunder-Compute/thunder-compute",
      "capabilities": [
        "compute.gpu",
        "compute.containers"
      ],
      "tags": [
        "hosted",
        "usage-priced",
        "openapi",
        "llms-txt",
        "mcp",
        "cli",
        "oauth",
        "api-key",
        "python",
        "go",
        "status-page",
        "card-required",
        "closed-source"
      ],
      "lastRelease": "2026-09-16",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 56.1,
        "grade": "C",
        "agentReady": false,
        "rank": 576,
        "ranked": true,
        "rankOf": 842,
        "categoryRank": 10,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 48,
          "maintenance": 79,
          "payments": 20,
          "reliability": 65,
          "schema": 70,
          "security": 51,
          "transparency": 64
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-09"
        },
        "negative": 0,
        "verdict": "The hosted MCP server signs in with OAuth and separate read and write scopes, and the REST API has a public OpenAPI 3.1 document with keyless price and availability endpoints. No rate limits, SLA or API changelog were found, instance creation has no idempotency key, and instances cannot be stopped, only deleted.",
        "bestFor": "Agents in coding tools that rent a single persistent GPU machine for development, fine-tuning or a model server, at low hourly prices and over MCP.",
        "strengths": [
          "Hosted MCP server at `https://www.thundercompute.com/mcp` with OAuth and ten scopes that separate read from write for instances, snapshots and sandboxes",
          "Public OpenAPI 3.1 document with 41 operations, plus `llms.txt`, `llms-full.txt` and a Markdown copy of every docs page",
          "`GET /v2/pricing`, `GET /v2/specs` and `GET /v2/status` return prices, configurations and live availability without a token",
          "Section 28 of the terms, dated 28 September 2026, permits access by AI agents, scripts and SDKs through the account holder's own credentials",
          "The status page lists no incidents for July to October 2026 on its Website, API and Instances components"
        ],
        "weaknesses": [
          "No rate limits, 429 guidance or SLA were found in the reviewed documentation, and the terms disclaim availability",
          "`POST /instances/create` has no idempotency key, so a retried launch can start a second billed instance",
          "Instances cannot be stopped. Pausing means taking a snapshot, deleting the instance and restoring later",
          "No general free tier. The $20 credit is limited to students with a US university email",
          "No security.txt or disclosure policy was found, and the SOC 2 Type II claim in `llms.txt` has no report or trust page linked",
          "The sub-processor list, last updated 27 August 2025, names Firebase for sign-in while the MCP docs name Stytch"
        ],
        "agentNotes": [
          "Call `GET /v2/status` or the `get_availability` tool before creating an instance. Availability can change before launch, and creation fails when a type is sold out.",
          "List instances before retrying a failed create, because the call has no idempotency key.",
          "Pass `public_key` on create. If omitted, the response carries a generated private key that is returned once.",
          "To pause work, create a snapshot, delete the instance and later create a new instance from the snapshot. Snapshot storage keeps billing until deleted.",
          "For headless use set `TNR_API_TOKEN` to a token from the console. The MCP server needs a browser sign-in on first connection."
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 56.1
          }
        ],
        "editorialScores": {
          "ergonomics": 48,
          "maintenance": 79,
          "payments": 20,
          "reliability": 65,
          "schema": 70,
          "security": 51,
          "transparency": 51
        },
        "provenanceScore": 77
      },
      "connect": {
        "install": "curl -fsSL https://raw.githubusercontent.com/Thunder-Compute/thunder-cli/main/scripts/install.sh | bash",
        "http": "curl https://api.thundercompute.com:8443/v2/pricing",
        "claudeCode": "claude mcp add --transport http thunder-compute https://www.thundercompute.com/mcp",
        "config": {
          "mcpServers": {
            "thunder-compute": {
              "url": "https://www.thundercompute.com/mcp"
            }
          }
        }
      },
      "letme": {
        "capability": "https://letme.dev/compute.gpu",
        "tool": "https://letme.dev/thunder-compute"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "RTX A6000 48 GB instance",
          "unit": "gpu-hour",
          "usd": 0.35,
          "note": "Billed per minute. One GPU per instance"
        },
        {
          "item": "L40 48 GB instance",
          "unit": "gpu-hour",
          "usd": 0.79,
          "note": "Billed per minute"
        },
        {
          "item": "A100 80 GB instance",
          "unit": "gpu-hour",
          "usd": 1.09,
          "note": "Billed per minute. 4 and 8 GPU shapes cost $1.49 a GPU per the price endpoint"
        },
        {
          "item": "H100 80 GB instance",
          "unit": "gpu-hour",
          "usd": 3.2,
          "note": "Billed per minute"
        },
        {
          "item": "H100 80 GB sandbox",
          "unit": "gpu-hour",
          "usd": 2.95,
          "note": "Billed per second, plus vCPU and memory. Access on request"
        },
        {
          "item": "A100 80 GB sandbox",
          "unit": "gpu-hour",
          "usd": 1.95,
          "note": "Billed per second, plus vCPU and memory. Access on request"
        },
        {
          "item": "Extra instance vCPU",
          "unit": "vcpu-hour",
          "usd": 0.04,
          "note": "Above the vCPUs included with each GPU"
        },
        {
          "item": "Sandbox vCPU",
          "unit": "vcpu-hour",
          "usd": 0.051,
          "note": "Memory is $0.016 per GiB an hour"
        },
        {
          "item": "Instance disk above 100 GB per GPU",
          "unit": "gb-month",
          "usd": 0.219,
          "note": "Billed only while the instance runs"
        },
        {
          "item": "Snapshot storage",
          "unit": "gb-month",
          "usd": 0.05,
          "note": "Kept until deleted"
        }
      ],
      "provenance": {
        "legalEntity": "Thunder GPU, Inc.",
        "domain": "thundercompute.com",
        "domainRegistered": "2024-02-29",
        "endpointOnVendorDomain": true,
        "terms": "https://www.thundercompute.com/terms-and-conditions",
        "privacy": "https://www.thundercompute.com/privacy-policy",
        "statusPage": "https://status.thundercompute.com",
        "changelog": "https://github.com/Thunder-Compute/thunder-cli/blob/main/CHANGELOG.md",
        "securityTxt": "none",
        "checked": "2026-10-09",
        "notes": [
          "The Terms and Conditions, last updated 28 September 2026, name Thunder GPU, Inc., doing business as Thunder Compute, a Delaware company, and apply Delaware law. They cover the site and the services, with sections on automated access, usage billing and instance data deletion.",
          "The privacy policy, last updated 28 September 2026, covers the website and the GPU platform, including access by AI agents.",
          "The API answers at api.thundercompute.com on port 8443, and the MCP server at www.thundercompute.com/mcp, both on the vendor domain.",
          "/.well-known/security.txt answers 404.",
          "RDAP for thundercompute.com gives a registration date of 2024-02-29.",
          "The changelog linked is the CLI's. No API changelog was found.",
          "A Data Processing Addendum is published in the docs and a sub-processor list on the site, last updated 27 August 2025."
        ],
        "score": 77
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/thunder-compute.json",
      "live": {
        "slug": "thunder-compute",
        "probe": {
          "target": "https://api.thundercompute.com:8443/v1",
          "method": "get",
          "lastAt": "2026-10-09T11:46:42.843121353Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 255,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 603,
          "p95ms24h": 730,
          "samples24h": 44,
          "samples30d": 44,
          "days": [
            {
              "date": "2026-10-09",
              "probes": 44,
              "ok": 44
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.thundercompute.com",
          "indicator": "none",
          "summary": "All Systems Operational",
          "checkedAt": "2026-10-09T11:41:06.351340196Z"
        },
        "updatedAt": "2026-10-09T11:46:42.843121353Z"
      }
    },
    "facts": [
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        "a": "HTTP API",
        "b": "HTTP API",
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        "a": "Hugging Face, Inc.",
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      {
        "a": "OAuth or key",
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        "a": "Pay per use",
        "b": "Pay per use",
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        "b": "$0.219 per GB per month",
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        "a": "no",
        "b": "no",
        "name": "x402"
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      {
        "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 Thunder Compute's Terms and Conditions. The `tnr` CLI on GitHub is MIT",
        "name": "Licence"
      },
      {
        "a": "19",
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        "name": "Tools exposed"
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      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
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      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
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        "b": "2026-09-28",
        "name": "Privacy policy last updated"
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        "a": "not found in the text",
        "b": "not found in the text",
        "name": "Customer content may train models"
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        "a": "not found in the text",
        "b": "not found in the text",
        "name": "Terms restrict automated access"
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        "a": "not found in the text",
        "b": "yes",
        "name": "Terms restrict benchmarking"
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        "a": "yes",
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        "name": "Terms or service can change without notice"
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        "b": "yes",
        "name": "Arbitration or class-action waiver"
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        "a": "60M PyPI/wk",
        "b": "34 stars",
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    ],
    "faq": [
      {
        "answer": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Thunder Compute's 56.1 (C), and leads in 5 of 7 scored categories.",
        "question": "Which is better for AI agents, Hugging Face Inference Endpoints or Thunder Compute?"
      },
      {
        "answer": "Both take an API key or an OAuth sign-in.",
        "question": "Do Hugging Face Inference Endpoints and Thunder Compute need an API key?"
      },
      {
        "answer": "Yes. Hugging Face Inference Endpoints has a hosted endpoint at https://api.endpoints.huggingface.cloud and Thunder Compute at https://api.thundercompute.com:8443/v1.",
        "question": "Can an agent call Hugging Face Inference Endpoints and Thunder Compute without installing anything?"
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    "goodFor": [
      {
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          "Agent ergonomics, 62 against 48",
          "Security \u0026 auth, 83 against 51"
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        "json": "https://www.anchorterminal.com/compare/beam-vs-hugging-face-inference-endpoints.json",
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        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/cerebrium-vs-thunder-compute.json",
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        "url": "https://www.anchorterminal.com/compare/cerebrium-vs-thunder-compute"
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      {
        "json": "https://www.anchorterminal.com/compare/coreweave-vs-hugging-face-inference-endpoints.json",
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      {
        "json": "https://www.anchorterminal.com/compare/coreweave-vs-thunder-compute.json",
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        "url": "https://www.anchorterminal.com/compare/coreweave-vs-thunder-compute"
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      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-hyperbolic.json",
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        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-hyperbolic"
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      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-koyeb.json",
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        "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",
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        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-modal.json",
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      },
      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-northflank.json",
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        "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-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",
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        "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-verda"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hyperbolic-vs-thunder-compute.json",
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        "url": "https://www.anchorterminal.com/compare/hyperbolic-vs-thunder-compute"
      },
      {
        "json": "https://www.anchorterminal.com/compare/koyeb-vs-thunder-compute.json",
        "title": "Koyeb vs Thunder Compute",
        "url": "https://www.anchorterminal.com/compare/koyeb-vs-thunder-compute"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lambda-vs-thunder-compute.json",
        "title": "Lambda Cloud vs Thunder Compute",
        "url": "https://www.anchorterminal.com/compare/lambda-vs-thunder-compute"
      },
      {
        "json": "https://www.anchorterminal.com/compare/modal-vs-thunder-compute.json",
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        "url": "https://www.anchorterminal.com/compare/modal-vs-thunder-compute"
      },
      {
        "json": "https://www.anchorterminal.com/compare/nebius-ai-cloud-vs-thunder-compute.json",
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        "url": "https://www.anchorterminal.com/compare/nebius-ai-cloud-vs-thunder-compute"
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        "json": "https://www.anchorterminal.com/compare/northflank-vs-thunder-compute.json",
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      },
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        "title": "Runpod vs Thunder Compute",
        "url": "https://www.anchorterminal.com/compare/runpod-vs-thunder-compute"
      },
      {
        "json": "https://www.anchorterminal.com/compare/thunder-compute-vs-vast-ai.json",
        "title": "Thunder Compute vs Vast.ai",
        "url": "https://www.anchorterminal.com/compare/thunder-compute-vs-vast-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/thunder-compute-vs-verda.json",
        "title": "Thunder Compute vs Verda",
        "url": "https://www.anchorterminal.com/compare/thunder-compute-vs-verda"
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    ],
    "scores": [
      {
        "by": 2,
        "edge": "thunder-compute",
        "hugging-face-inference-endpoints": 63,
        "key": "reliability",
        "name": "Reliability",
        "thunder-compute": 65,
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 3,
        "edge": "hugging-face-inference-endpoints",
        "hugging-face-inference-endpoints": 73,
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "thunder-compute": 70,
        "weight": 13
      },
      {
        "by": 14,
        "edge": "hugging-face-inference-endpoints",
        "hugging-face-inference-endpoints": 62,
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "thunder-compute": 48,
        "weight": 13
      },
      {
        "by": 32,
        "edge": "hugging-face-inference-endpoints",
        "hugging-face-inference-endpoints": 83,
        "key": "security",
        "name": "Security \u0026 auth",
        "thunder-compute": 51,
        "weight": 14
      },
      {
        "by": 0,
        "edge": "",
        "hugging-face-inference-endpoints": 20,
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "thunder-compute": 20,
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 1,
        "edge": "hugging-face-inference-endpoints",
        "hugging-face-inference-endpoints": 80,
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "thunder-compute": 79,
        "weight": 7
      },
      {
        "by": 4,
        "edge": "hugging-face-inference-endpoints",
        "hugging-face-inference-endpoints": 68,
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "thunder-compute": 64,
        "weight": 7
      }
    ],
    "summary": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Thunder Compute's 56.1 (C), and leads in 5 of 7 scored categories. Both do compute gpu.",
    "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.",
      "thunder-compute": "The hosted MCP server signs in with OAuth and separate read and write scopes, and the REST API has a public OpenAPI 3.1 document with keyless price and availability endpoints. No rate limits, SLA or API changelog were found, instance creation has no idempotency key, and instances cannot be stopped, only deleted."
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  "markdown": "Hugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Thunder Compute's 56.1 (C), and leads in 5 of 7 scored categories. Both do compute gpu.\n\n- Hugging Face Inference Endpoints: grade B, 64.5/100, rank #314 of 842. 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- Thunder Compute: grade C, 56.1/100, rank #576 of 842. Markdown https://www.anchorterminal.com/tools/thunder-compute.md · JSON https://www.anchorterminal.com/api/v1/tools/thunder-compute.json\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- Agent ergonomics, 62 against 48\n- Security \u0026 auth, 83 against 51\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### Thunder Compute (C)\n\nGood for: Agents in coding tools that rent a single persistent GPU machine for development, fine-tuning or a model server, at low hourly prices and over MCP.\n\nWatch for: No rate limits, 429 guidance or SLA were found in the reviewed documentation, and the terms disclaim availability\n\n\n## Score by category\n\n| Category | Weight | Hugging Face Inference Endpoints | Thunder Compute | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 63 | 65 | Thunder Compute +2 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 73 | 70 | Hugging Face Inference Endpoints +3 |\n| Agent ergonomics | 13% (16.2 this run) | 62 | 48 | Hugging Face Inference Endpoints +14 |\n| Security \u0026 auth | 14% (17.5 this run) | 83 | 51 | Hugging Face Inference Endpoints +32 |\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 | 79 | Hugging Face Inference Endpoints +1 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 68 | 64 | Hugging Face Inference Endpoints +4 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **64.5 · B** | **56.1 · C** | |\n\n## Facts side by side\n\n| Fact | Hugging Face Inference Endpoints | Thunder Compute |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Hugging Face, Inc. | Thunder Compute |\n| Hosted endpoint | `https://api.endpoints.huggingface.cloud` | `https://api.thundercompute.com:8443/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 compute gpu | not published | $0.219 per GB per month |\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 Thunder Compute's Terms and Conditions. The `tnr` CLI on GitHub is MIT |\n| Tools exposed | 19 | 28 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| MCP registry | not listed | `io.github.Thunder-Compute/thunder-compute` |\n| Last release | 2026-10-08 | 2026-09-16 |\n| Terms last updated | 2022-09-15 | 2026-09-28 |\n| Privacy policy last updated | 2023-03-28 | 2026-09-28 |\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 | yes |\n| Terms or service can change without notice | yes | yes |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | 60M PyPI/wk | 34 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**Thunder Compute.** The hosted MCP server signs in with OAuth and separate read and write scopes, and the REST API has a public OpenAPI 3.1 document with keyless price and availability endpoints. No rate limits, SLA or API changelog were found, instance creation has no idempotency key, and instances cannot be stopped, only deleted.\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### Thunder Compute\n\n1. Call `GET /v2/status` or the `get_availability` tool before creating an instance. Availability can change before launch, and creation fails when a type is sold out.\n2. List instances before retrying a failed create, because the call has no idempotency key.\n3. Pass `public_key` on create. If omitted, the response carries a generated private key that is returned once.\n4. To pause work, create a snapshot, delete the instance and later create a new instance from the snapshot. Snapshot storage keeps billing until deleted.\n5. For headless use set `TNR_API_TOKEN` to a token from the console. The MCP server needs a browser sign-in on first connection.\n\n## Questions\n\n### Which is better for AI agents, Hugging Face Inference Endpoints or Thunder Compute?\n\nHugging Face Inference Endpoints scores 64.5 (B) on agent readiness against Thunder Compute's 56.1 (C), and leads in 5 of 7 scored categories.\n\n### Do Hugging Face Inference Endpoints and Thunder 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 Thunder Compute without installing anything?\n\nYes. Hugging Face Inference Endpoints has a hosted endpoint at https://api.endpoints.huggingface.cloud and Thunder Compute at https://api.thundercompute.com:8443/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-thunder-compute.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-thunder-compute.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"hugging-face-inference-endpoints\", \"b\": \"thunder-compute\"}`. From a terminal: `anchor compare hugging-face-inference-endpoints thunder-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/thunder-compute.json\n\n## Other comparisons with Hugging Face Inference Endpoints or Thunder Compute\n\n- [Baseten vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/baseten-vs-hugging-face-inference-endpoints.md)\n- [Baseten vs Thunder Compute](https://www.anchorterminal.com/compare/baseten-vs-thunder-compute.md)\n- [Beam vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/beam-vs-hugging-face-inference-endpoints.md)\n- [Beam vs Thunder Compute](https://www.anchorterminal.com/compare/beam-vs-thunder-compute.md)\n- [Cerebrium vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/cerebrium-vs-hugging-face-inference-endpoints.md)\n- [Cerebrium vs Thunder Compute](https://www.anchorterminal.com/compare/cerebrium-vs-thunder-compute.md)\n- [CoreWeave vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/coreweave-vs-hugging-face-inference-endpoints.md)\n- [CoreWeave vs Thunder Compute](https://www.anchorterminal.com/compare/coreweave-vs-thunder-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 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 Thunder Compute](https://www.anchorterminal.com/compare/hyperbolic-vs-thunder-compute.md)\n- [Koyeb vs Thunder Compute](https://www.anchorterminal.com/compare/koyeb-vs-thunder-compute.md)\n- [Lambda Cloud vs Thunder Compute](https://www.anchorterminal.com/compare/lambda-vs-thunder-compute.md)\n- [Modal vs Thunder Compute](https://www.anchorterminal.com/compare/modal-vs-thunder-compute.md)\n- [Nebius AI Cloud vs Thunder Compute](https://www.anchorterminal.com/compare/nebius-ai-cloud-vs-thunder-compute.md)\n- [Northflank vs Thunder Compute](https://www.anchorterminal.com/compare/northflank-vs-thunder-compute.md)\n- [Replicate Deployments vs Thunder Compute](https://www.anchorterminal.com/compare/replicate-deploy-vs-thunder-compute.md)\n- [Runpod vs Thunder Compute](https://www.anchorterminal.com/compare/runpod-vs-thunder-compute.md)\n- [Thunder Compute vs Vast.ai](https://www.anchorterminal.com/compare/thunder-compute-vs-vast-ai.md)\n- [Thunder Compute vs Verda](https://www.anchorterminal.com/compare/thunder-compute-vs-verda.md)\n",
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