{
  "data": {
    "a": {
      "slug": "hyperbolic",
      "name": "Hyperbolic",
      "vendor": "Hyperbolic Labs, Inc.",
      "vendorUrl": "https://www.hyperbolic.ai",
      "kind": "http-api",
      "category": "gpu-compute",
      "summary": "Hyperbolic is a GPU cloud from Hyperbolic Labs that rents H100, H200 and B200 virtual machines and bare-metal nodes by the hour, with reserved terms and private clusters. Agents use its REST API with an API key.",
      "url": "https://www.anchorterminal.com/tools/hyperbolic",
      "markdownUrl": "https://www.anchorterminal.com/tools/hyperbolic.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hyperbolic.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hyperbolic.json",
      "license": "Proprietary service under Hyperbolic's Terms of Service. The unmaintained hyperbolic-mcp repository on GitHub is MIT",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://api.hyperbolic.ai",
      "packages": [],
      "auth": "api-key",
      "authNotes": "Self-serve. A signed-in user creates an API key in the console's settings, and the secret is shown once. Requests send it as `Authorization: Bearer \u003capi-key\u003e`. An account can hold any number of keys and revoke any of them. Keys created inside an Organisation belong to it and are attributed to the member who made them. Members revoke their own keys and admins revoke any. No scopes, read-only keys or expiry were found in the reviewed documentation. `GET /v2/openapi.json`, `GET /v2/on-demand/rental-options` and `GET /v2/on-demand/reserve-options` need no key.",
      "pricing": "usage",
      "pricingNotes": "Prepaid credits, minimum purchase $5 through Stripe, 1 to 1 with dollars and with no expiry. A new account is on the free tier and cannot rent GPUs or storage until it has deposited $5 once. No trial was found, apart from credit codes handed out at events. On-demand rentals bill hourly from the moment an instance is ready, and the balance must cover one hour of all running instances. On 8 October 2026 the open price list showed one H100 virtual machine at $3.19 an hour. Reserved terms of 7, 14 and 30 days take 1, 3 and 5 per cent off and are paid up front. Private Cloud is by contract (https://www.hyperbolic.ai/docs/on-demand/pricing).",
      "priceSummary": "Pay per use",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the docs corpus or the OpenAPI document for the GPU API. The archived HyperbolicLabs/hyperbolic-x402 repository covered chat completions on a separate host, not GPU rentals (checked 2026-10-08).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-08"
      },
      "docsUrl": "https://www.hyperbolic.ai/docs/overview/overview",
      "llmsTxt": "https://www.hyperbolic.ai/docs/llms.txt",
      "openapi": "https://api.hyperbolic.ai/v2/openapi.json",
      "capabilities": [
        "compute.gpu"
      ],
      "tags": [
        "hosted",
        "usage-priced",
        "openapi",
        "llms-txt",
        "api-key",
        "bare-metal",
        "status-page",
        "prepaid"
      ],
      "lastRelease": "2026-10-05",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 48,
        "grade": "D",
        "agentReady": false,
        "rank": 730,
        "ranked": true,
        "rankOf": 842,
        "categoryRank": 15,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 55,
          "maintenance": 42,
          "payments": 15,
          "reliability": 52,
          "schema": 77,
          "security": 47,
          "transparency": 61
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-08"
        },
        "negative": -3,
        "negativeNotes": [
          "2026-10-05, removing the `roles` list from the `GET /v2/users/me` response and changing timestamps to RFC 3339 on the v2 API. Both are recorded in the changelog entry for the week they shipped, and no advance notice was found. Documented, so 3 points (https://www.hyperbolic.ai/docs/changelog)."
        ],
        "verdict": "The API serves its own OpenAPI 3.1 document without a key, lists GPU prices on an open endpoint and dates the removal of legacy paths at 1 March 2027. API keys carry no scopes and can delete the account, rental creation has no idempotency key, and renting needs a browser signup and a $5 deposit.",
        "bestFor": "Agents that rent whole H100, H200 or B200 machines or multi-node clusters for training and batch work and that have a funded account.",
        "strengths": [
          "OpenAPI 3.1 document with 65 operations and 53 schemas, served by the API at `GET /v2/openapi.json` with no key",
          "`GET /v2/on-demand/rental-options` returns live GPU configurations and hourly prices in cents with no key",
          "Deprecated paths answer with a `Sunset` header and a stated end date of 1 March 2027, and each names its replacement",
          "Docs index at `/docs/llms.txt`, every page as Markdown and the whole corpus in `llms-full.txt` (188 KB)",
          "Billing starts only when an instance is ready, and instances that fail to provision within about 3 hours are not charged, per the pricing docs"
        ],
        "weaknesses": [
          "API keys carry no scopes or expiry in the reviewed documentation, and the same key can call `DELETE /v2/users/me`",
          "`POST /v2/on-demand/rentals` has no idempotency key, so a retried call can start a second billed rental",
          "No 429 response, `Retry-After` header or backoff guidance was found in the spec or the docs",
          "A free-tier account cannot rent GPUs or storage. Renting needs a one-time deposit of at least $5 through Stripe",
          "The Terms of Service describe a marketplace in which uptime is between buyer and supplier, while the docs state a 99.5 per cent uptime SLA",
          "No official SDK or CLI for the v2 API was found. The vendor's MCP repository last changed in May 2025 and calls the legacy v1 marketplace paths"
        ],
        "agentNotes": [
          "Read `GET /v2/on-demand/rental-options` first. It needs no key and lists what can be rented now, with `costPerHourCents` per GPU configuration.",
          "Send `rentalType` and `gpuCount` to `POST /v2/on-demand/rentals`. Region defaults to `us-central-1` and GPU type to `h100`, so set both from the options list.",
          "List active rentals before retrying a failed create call. There is no idempotency key and every ready rental bills hourly.",
          "Save an SSH public key with `POST /v2/ssh-keys` before renting. Without `sshPublicKeyIds` the newest saved key is attached.",
          "Do not create reserved rentals unless asked. They are paid in full up front and cannot be terminated early."
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "D",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 48
          }
        ],
        "editorialScores": {
          "ergonomics": 55,
          "maintenance": 42,
          "payments": 15,
          "reliability": 52,
          "schema": 77,
          "security": 47,
          "transparency": 45
        },
        "provenanceScore": 76
      },
      "connect": {
        "http": "curl -X POST https://api.hyperbolic.ai/v2/ssh-keys -H \"Authorization: Bearer $HYPERBOLIC_API_KEY\" -H \"Content-Type: application/json\" -d \"{\\\"publicKey\\\": \\\"$(cat ~/.ssh/id_ed25519.pub)\\\", \\\"name\\\": \\\"Work laptop\\\"}\""
      },
      "letme": {
        "capability": "https://letme.dev/compute.gpu",
        "tool": "https://letme.dev/hyperbolic"
      },
      "area": "models",
      "unitPrices": [
        {
          "item": "H100 SXM5 80 GB virtual machine, on-demand",
          "unit": "gpu-hour",
          "usd": 3.19,
          "note": "The one configuration on the open price list on 8 October 2026 (us-east-1). Reserved terms take 1 to 5 per cent off"
        }
      ],
      "provenance": {
        "legalEntity": "Hyperbolic Labs, Inc.",
        "domain": "hyperbolic.ai",
        "domainRegistered": "2021-10-11",
        "endpointOnVendorDomain": true,
        "terms": "https://www.hyperbolic.ai/terms",
        "privacy": "https://www.hyperbolic.ai/privacy",
        "statusPage": "https://status.hyperbolic.ai",
        "changelog": "https://www.hyperbolic.ai/docs/changelog",
        "securityTxt": "none",
        "checked": "2026-10-08",
        "notes": [
          "The Terms of Service, last updated 24 March 2025, name Hyperbolic Labs, Inc. as owner and operator of the platform, apply California law and set AAA arbitration. They cover the website and all services, and no separate API or cloud agreement was found.",
          "The Privacy Policy is effective 3 June 2024 and names Hyperbolic Labs, Inc. One clause on business transfers names Babylon three times where the company's own name would be expected.",
          "The API answers at api.hyperbolic.ai, a subdomain of the vendor domain, and on the legacy host api.hyperbolic.xyz.",
          "https://www.hyperbolic.ai/.well-known/security.txt answered 404. The docs ask for vulnerability reports by email to support@hyperbolic.ai.",
          "RDAP for hyperbolic.ai gives a registration date of 2021-10-11."
        ],
        "score": 76
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/hyperbolic.json",
      "live": {
        "slug": "hyperbolic",
        "probe": {
          "target": "https://api.hyperbolic.ai",
          "method": "get",
          "lastAt": "2026-10-09T10:14:17.158516367Z",
          "lastOk": true,
          "lastStatus": 200,
          "lastMs": 756,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 663,
          "p95ms24h": 738,
          "samples24h": 28,
          "samples30d": 28,
          "days": [
            {
              "date": "2026-10-09",
              "probes": 28,
              "ok": 28
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.hyperbolic.ai",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-09T07:58:04.049851546Z"
        },
        "updatedAt": "2026-10-09T10:14:17.158516367Z"
      }
    },
    "answer": "Modal scores 63.6 (B) on agent readiness against Hyperbolic's 48 (D), and leads in 6 of 7 scored categories. Hyperbolic leads on schema \u0026 documentation.",
    "b": {
      "slug": "modal",
      "name": "Modal",
      "vendor": "Modal",
      "vendorUrl": "https://modal.com",
      "kind": "platform",
      "category": "gpu-compute",
      "summary": "Serverless functions, web endpoints, servers and GPU jobs from a Python decorator, with JavaScript and Go SDKs.",
      "url": "https://www.anchorterminal.com/tools/modal",
      "markdownUrl": "https://www.anchorterminal.com/tools/modal.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/modal.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/modal.json",
      "repo": "https://github.com/modal-labs/modal-client",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "pypi",
          "name": "modal"
        },
        {
          "registry": "npm",
          "name": "modal"
        }
      ],
      "auth": "api-key",
      "authNotes": "No public REST API for deploying. The SDKs and CLI authenticate with a token ID and secret from `modal token new`, read from `MODAL_TOKEN_ID` and `MODAL_TOKEN_SECRET` or `~/.modal.toml`; tokens can carry a TTL. Deployed web endpoints are open by default and can be locked with proxy tokens sent as `Modal-Key` and `Modal-Secret` headers. Servers and Endpoints require a proxy token by default, sent as `Authorization: Bearer \u003cid\u003e.\u003csecret\u003e`.",
      "pricing": "freemium",
      "pricingNotes": "Starter is $0 a month with $30 of compute included every month, 3 seats, 100 containers and 10 concurrent GPUs. Team is $250 a month plus compute with $100 included, unlimited seats, 5,000 containers and 50 concurrent GPUs. Enterprise is custom. GPUs bill per second with nothing charged at zero containers. T4 $0.000164, L4 $0.000222, A10 $0.000306, L40S $0.000542, A100 40 GB $0.000583, A100 80 GB $0.000694, RTX PRO 6000 $0.000842, H100 $0.001097, H200 $0.001261, B200 $0.001736 and B300 $0.001972 a second. The pricing page lists CPU at $0.0000131 a core-second (0.125 core minimum per container) and memory at $0.00000222 a GiB-second, and volumes at $0.09 a GiB-month after 1 TiB free (https://modal.com/pricing).",
      "priceSummary": "$250 / mo",
      "where": "local",
      "x402": {
        "level": "no",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 514,
        "npmWeekly": 940973,
        "pypiWeekly": 10146778,
        "asOf": "2026-09-30"
      },
      "docsUrl": "https://modal.com/docs/guide",
      "llmsTxt": "https://modal.com/llms.txt",
      "capabilities": [
        "compute.gpu",
        "compute.serverless",
        "compute.endpoints",
        "compute.batch",
        "compute.containers"
      ],
      "tags": [
        "hosted",
        "freemium",
        "free-tier",
        "no-card",
        "python",
        "typescript",
        "go",
        "llms-txt",
        "enterprise"
      ],
      "lastRelease": "2026-09-28",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 63.6,
        "grade": "B",
        "agentReady": false,
        "rank": 346,
        "ranked": true,
        "rankOf": 842,
        "categoryRank": 4,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 57,
          "maintenance": 85,
          "payments": 30,
          "reliability": 70,
          "schema": 70,
          "security": 68,
          "transparency": 67
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-01"
        },
        "negative": 0,
        "verdict": "Scale to zero by default, per-second billing and about one-second container boots. No REST API or OpenAPI spec for deploying or invoking Functions.",
        "bestFor": "Python teams that want GPU functions, batch jobs and HTTP endpoints from one decorator with scale to zero.",
        "strengths": [
          "Scale to zero by default, per-second billing and about one-second container boots",
          "Retention stated per data type (inputs and outputs up to 7 days, logs 1 to 30 days)",
          "Python, JavaScript and Go SDKs, with llms.txt and dated release notes",
          "Four short incidents on the status page between July and September 2026",
          "SOC 2 Type 2, a private HackerOne programme and published disclosure response times"
        ],
        "weaknesses": [
          "No REST API or OpenAPI spec for deploying or invoking Functions",
          "Web endpoints are open by default until proxy tokens are added",
          "RBAC, audit logs and HIPAA only on Enterprise",
          "No published SLA, and Starter caps concurrent GPUs at 10",
          "Region pinning costs 1.15 to 1.75 times the base price"
        ],
        "agentNotes": [
          "Create a proxy token and require it on every web endpoint before sharing the URL; endpoints are public by default",
          "Pass a list to `gpu=` (for example `[\"H100\", \"A100-80GB\"]`) so a job still runs when the first choice is unavailable",
          "Set `scaledown_window` and `min_containers` explicitly; the defaults are 60 seconds and 0",
          "Use `.spawn()` and poll the call ID for long work instead of holding a web request open",
          "Keep web endpoint traffic under 200 requests a second or ask Modal to raise the limit"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 4,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "B",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 63.6
          }
        ],
        "editorialScores": {
          "ergonomics": 57,
          "maintenance": 85,
          "payments": 30,
          "reliability": 70,
          "schema": 70,
          "security": 68,
          "transparency": 63
        },
        "provenanceScore": 71
      },
      "connect": {
        "install": "pip install modal \u0026\u0026 modal setup",
        "http": "curl -X POST \"https://$MODAL_WORKSPACE--my-app-predict.modal.run\" \\\n  -H \"Modal-Key: $MODAL_PROXY_KEY\" -H \"Modal-Secret: $MODAL_PROXY_SECRET\" \\\n  -H \"Content-Type: application/json\" -d '{\"prompt\":\"hello\"}'"
      },
      "letme": {
        "capability": "https://letme.dev/compute.gpu",
        "tool": "https://letme.dev/modal"
      },
      "sameCompany": [
        "modal-sandboxes"
      ],
      "area": "models",
      "unitPrices": [
        {
          "item": "H100 80 GB",
          "unit": "gpu-hour",
          "usd": 3.95,
          "note": "$0.001097 a second, may be upgraded to H200 at the same price"
        },
        {
          "item": "H200 141 GB",
          "unit": "gpu-hour",
          "usd": 4.54,
          "note": "$0.001261 a second"
        },
        {
          "item": "B200 180 GB",
          "unit": "gpu-hour",
          "usd": 6.25,
          "note": "$0.001736 a second"
        },
        {
          "item": "A100 80 GB",
          "unit": "gpu-hour",
          "usd": 2.5,
          "note": "$0.000694 a second"
        },
        {
          "item": "L40S 48 GB",
          "unit": "gpu-hour",
          "usd": 1.95,
          "note": "$0.000542 a second"
        },
        {
          "item": "L4 24 GB",
          "unit": "gpu-hour",
          "usd": 0.8,
          "note": "$0.000222 a second"
        },
        {
          "item": "T4 16 GB",
          "unit": "gpu-hour",
          "usd": 0.59,
          "note": "$0.000164 a second"
        },
        {
          "item": "Team plan",
          "unit": "month",
          "usd": 250,
          "note": "Plus compute, $100 included, 50 concurrent GPUs"
        }
      ],
      "provenance": {
        "legalEntity": "Modal Labs, Inc.",
        "domain": "modal.com",
        "domainRegistered": "1999-03-18",
        "domainNote": "modal.com was registered in 1999, long before Modal Labs, so the domain was bought later.",
        "endpointOnVendorDomain": false,
        "terms": "https://modal.com/legal/terms",
        "privacy": "https://modal.com/legal/privacy-policy",
        "statusPage": "https://status.modal.com",
        "changelog": "https://modal.com/docs/sdk/py/releases",
        "securityTxt": "none",
        "checked": "2026-09-30",
        "notes": [
          "Terms (May 2026) name Modal Labs, Inc., a Delaware corporation, under California law.",
          "Deployed web endpoints and Servers are served from *.modal.run, a separate domain from modal.com. Deployment itself goes through the SDK, so there's no public API base URL to check.",
          "modal.com/.well-known/security.txt returns 404. The security guide gives security@modal.com and a private HackerOne programme.",
          "Modal Sandboxes are listed separately under code sandboxes."
        ],
        "score": 71
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/modal.json",
      "live": {
        "slug": "modal",
        "vendorStatus": {
          "page": "https://status.modal.com",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-09T07:58:11.313506769Z"
        },
        "versions": [
          {
            "registry": "npm",
            "name": "modal",
            "version": "0.11.0",
            "seenAt": "2026-10-08T16:21:43.713175523Z"
          },
          {
            "registry": "pypi",
            "name": "modal",
            "version": "1.6.1",
            "released": "2026-10-03",
            "seenAt": "2026-10-08T16:21:43.571967985Z"
          }
        ],
        "githubStars": 522,
        "npmWeekly": 976721,
        "pypiWeekly": 10794735,
        "securityTxt": {
          "url": "https://modal.com/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-08T15:38:35.387911158Z"
        },
        "llmsTxt": {
          "url": "https://modal.com/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-08T14:00:41.354164105Z"
        },
        "domain": {
          "domain": "modal.com",
          "registered": "1999-03-18",
          "source": "https://rdap.verisign.com/com/v1/domain/modal.com",
          "checkedAt": "2026-10-04T13:03:51.14581991Z"
        },
        "updatedAt": "2026-10-09T07:58:11.313506769Z"
      }
    },
    "facts": [
      {
        "a": "HTTP API",
        "b": "Model platform",
        "name": "Kind"
      },
      {
        "a": "Hyperbolic Labs, Inc.",
        "b": "Modal",
        "name": "Vendor"
      },
      {
        "a": "https://api.hyperbolic.ai",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP",
        "b": "",
        "name": "Transports"
      },
      {
        "a": "API key",
        "b": "API key",
        "name": "Auth"
      },
      {
        "a": "Pay per use",
        "b": "Freemium",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Proprietary service under Hyperbolic's Terms of Service. The unmaintained hyperbolic-mcp repository on GitHub is MIT",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-05",
        "b": "2026-09-28",
        "name": "Last release"
      },
      {
        "a": "2025-03-24",
        "b": "2026-05-01",
        "name": "Terms last updated"
      },
      {
        "a": "no date given",
        "b": "2023-05-17",
        "name": "Privacy policy last updated"
      },
      {
        "a": "not found in the text",
        "b": "not found in the text",
        "name": "Customer content may train models"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "name": "Terms restrict automated access"
      },
      {
        "a": "not found in the text",
        "b": "not found in the text",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "none",
        "b": "514 stars, 941k npm/wk, 10.1M PyPI/wk",
        "name": "Popularity"
      },
      {
        "a": "none",
        "b": "4/5 (2)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Modal scores 63.6 (B) on agent readiness against Hyperbolic's 48 (D), and leads in 6 of 7 scored categories. Hyperbolic leads on schema \u0026 documentation.",
        "question": "Which is better for AI agents, Hyperbolic or Modal?"
      },
      {
        "answer": "Hyperbolic has a hosted endpoint at https://api.hyperbolic.ai. No hosted endpoint is listed for Modal.",
        "question": "Can an agent call Hyperbolic and Modal without installing anything?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Schema \u0026 documentation, 77 against 70"
        ],
        "also": [
          "A hosted endpoint, with nothing to install"
        ],
        "goodFor": "Agents that rent whole H100, H200 or B200 machines or multi-node clusters for training and batch work and that have a funded account.",
        "slug": "hyperbolic",
        "watchFor": "API keys carry no scopes or expiry in the reviewed documentation, and the same key can call `DELETE /v2/users/me`"
      },
      {
        "aheadOn": [
          "Reliability, 70 against 52",
          "Security \u0026 auth, 68 against 47",
          "Payments \u0026 pricing, 30 against 15",
          "Maintenance \u0026 community, 85 against 42",
          "Transparency \u0026 trust, 67 against 61"
        ],
        "also": [
          "Free to start without a card",
          "No incidents deducted, where Hyperbolic loses 3 points for them"
        ],
        "goodFor": "Python teams that want GPU functions, batch jobs and HTTP endpoints from one decorator with scale to zero.",
        "slug": "modal",
        "watchFor": "No REST API or OpenAPI spec for deploying or invoking Functions"
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        "json": "https://www.anchorterminal.com/compare/baseten-vs-modal.json",
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        "json": "https://www.anchorterminal.com/compare/cerebrium-vs-modal.json",
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        "url": "https://www.anchorterminal.com/compare/coreweave-vs-modal"
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        "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-modal.json",
        "title": "Hugging Face Inference Endpoints vs Modal",
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        "json": "https://www.anchorterminal.com/compare/hyperbolic-vs-koyeb.json",
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        "json": "https://www.anchorterminal.com/compare/hyperbolic-vs-replicate-deploy.json",
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    "scores": [
      {
        "by": 18,
        "edge": "modal",
        "hyperbolic": 52,
        "key": "reliability",
        "modal": 70,
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 7,
        "edge": "hyperbolic",
        "hyperbolic": 77,
        "key": "schema",
        "modal": 70,
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
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        "by": 2,
        "edge": "modal",
        "hyperbolic": 55,
        "key": "ergonomics",
        "modal": 57,
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "by": 21,
        "edge": "modal",
        "hyperbolic": 47,
        "key": "security",
        "modal": 68,
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "by": 15,
        "edge": "modal",
        "hyperbolic": 15,
        "key": "payments",
        "modal": 30,
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 43,
        "edge": "modal",
        "hyperbolic": 42,
        "key": "maintenance",
        "modal": 85,
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "by": 6,
        "edge": "modal",
        "hyperbolic": 61,
        "key": "transparency",
        "modal": 67,
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "Modal scores 63.6 (B) on agent readiness against Hyperbolic's 48 (D), and leads in 6 of 7 scored categories. Hyperbolic leads on schema \u0026 documentation. Both do compute gpu.",
    "verdicts": {
      "hyperbolic": "The API serves its own OpenAPI 3.1 document without a key, lists GPU prices on an open endpoint and dates the removal of legacy paths at 1 March 2027. API keys carry no scopes and can delete the account, rental creation has no idempotency key, and renting needs a browser signup and a $5 deposit.",
      "modal": "Scale to zero by default, per-second billing and about one-second container boots. No REST API or OpenAPI spec for deploying or invoking Functions."
    }
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  "markdown": "Modal scores 63.6 (B) on agent readiness against Hyperbolic's 48 (D), and leads in 6 of 7 scored categories. Hyperbolic leads on schema \u0026 documentation. Both do compute gpu.\n\n- Hyperbolic: grade D, 48/100, rank #730 of 842. Markdown https://www.anchorterminal.com/tools/hyperbolic.md · JSON https://www.anchorterminal.com/api/v1/tools/hyperbolic.json\n- Modal: grade B, 63.6/100, rank #346 of 842. Markdown https://www.anchorterminal.com/tools/modal.md · JSON https://www.anchorterminal.com/api/v1/tools/modal.json\n\n## Which one, for what\n\n### Hyperbolic (D)\n\nGood for: Agents that rent whole H100, H200 or B200 machines or multi-node clusters for training and batch work and that have a funded account.\n\nAhead on:\n- Schema \u0026 documentation, 77 against 70\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: API keys carry no scopes or expiry in the reviewed documentation, and the same key can call `DELETE /v2/users/me`\n\n### Modal (B)\n\nGood for: Python teams that want GPU functions, batch jobs and HTTP endpoints from one decorator with scale to zero.\n\nAhead on:\n- Reliability, 70 against 52\n- Security \u0026 auth, 68 against 47\n- Payments \u0026 pricing, 30 against 15\n- Maintenance \u0026 community, 85 against 42\n- Transparency \u0026 trust, 67 against 61\n\nAlso in its favour:\n- Free to start without a card\n- No incidents deducted, where Hyperbolic loses 3 points for them\n\nWatch for: No REST API or OpenAPI spec for deploying or invoking Functions\n\n\n## Score by category\n\n| Category | Weight | Hyperbolic | Modal | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 52 | 70 | Modal +18 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 77 | 70 | Hyperbolic +7 |\n| Agent ergonomics | 13% (16.2 this run) | 55 | 57 | Modal +2 |\n| Security \u0026 auth | 14% (17.5 this run) | 47 | 68 | Modal +21 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 15 | 30 | Modal +15 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 42 | 85 | Modal +43 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 61 | 67 | Modal +6 |\n| Negative events | ≤15 | -3 | 0 | |\n| **Total** | | **48 · D** | **63.6 · B** | |\n\n## Facts side by side\n\n| Fact | Hyperbolic | Modal |\n| --- | --- | --- |\n| Kind | HTTP API | Model platform |\n| Vendor | Hyperbolic Labs, Inc. | Modal |\n| Hosted endpoint | `https://api.hyperbolic.ai` | no (local only) |\n| Transports | HTTP |  |\n| Auth | API key | API key |\n| Pricing | Pay per use | Freemium |\n| x402 | no | no |\n| Licence | Proprietary service under Hyperbolic's Terms of Service. The unmaintained hyperbolic-mcp repository on GitHub is MIT | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-05 | 2026-09-28 |\n| Terms last updated | 2025-03-24 | 2026-05-01 |\n| Privacy policy last updated | no date given | 2023-05-17 |\n| Customer content may train models | not found in the text | not found in the text |\n| Terms restrict automated access | yes | not found in the text |\n| Terms restrict benchmarking | not found in the text | not found in the text |\n| Terms or service can change without notice | yes | not found in the text |\n| Arbitration or class-action waiver | yes | not found in the text |\n| Popularity | none | 514 stars, 941k npm/wk, 10.1M PyPI/wk |\n| Agent reviews | none | 4/5 (2) |\n\n## Verdicts\n\n**Hyperbolic.** The API serves its own OpenAPI 3.1 document without a key, lists GPU prices on an open endpoint and dates the removal of legacy paths at 1 March 2027. API keys carry no scopes and can delete the account, rental creation has no idempotency key, and renting needs a browser signup and a $5 deposit.\n\n**Modal.** Scale to zero by default, per-second billing and about one-second container boots. No REST API or OpenAPI spec for deploying or invoking Functions.\n\n## Before you call either\n\n### Hyperbolic\n\n1. Read `GET /v2/on-demand/rental-options` first. It needs no key and lists what can be rented now, with `costPerHourCents` per GPU configuration.\n2. Send `rentalType` and `gpuCount` to `POST /v2/on-demand/rentals`. Region defaults to `us-central-1` and GPU type to `h100`, so set both from the options list.\n3. List active rentals before retrying a failed create call. There is no idempotency key and every ready rental bills hourly.\n4. Save an SSH public key with `POST /v2/ssh-keys` before renting. Without `sshPublicKeyIds` the newest saved key is attached.\n5. Do not create reserved rentals unless asked. They are paid in full up front and cannot be terminated early.\n\n### Modal\n\n1. Create a proxy token and require it on every web endpoint before sharing the URL; endpoints are public by default\n2. Pass a list to `gpu=` (for example `[\"H100\", \"A100-80GB\"]`) so a job still runs when the first choice is unavailable\n3. Set `scaledown_window` and `min_containers` explicitly; the defaults are 60 seconds and 0\n4. Use `.spawn()` and poll the call ID for long work instead of holding a web request open\n5. Keep web endpoint traffic under 200 requests a second or ask Modal to raise the limit\n\n## Questions\n\n### Which is better for AI agents, Hyperbolic or Modal?\n\nModal scores 63.6 (B) on agent readiness against Hyperbolic's 48 (D), and leads in 6 of 7 scored categories. Hyperbolic leads on schema \u0026 documentation.\n\n### Can an agent call Hyperbolic and Modal without installing anything?\n\nHyperbolic has a hosted endpoint at https://api.hyperbolic.ai. No hosted endpoint is listed for Modal.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/hyperbolic-vs-modal.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hyperbolic-vs-modal.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"hyperbolic\", \"b\": \"modal\"}`. From a terminal: `anchor compare hyperbolic modal`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/hyperbolic.json and https://www.anchorterminal.com/api/v1/tools/modal.json\n\n## Other comparisons with Hyperbolic or Modal\n\n- [Baseten vs Hyperbolic](https://www.anchorterminal.com/compare/baseten-vs-hyperbolic.md)\n- [Baseten vs Modal](https://www.anchorterminal.com/compare/baseten-vs-modal.md)\n- [Beam vs Hyperbolic](https://www.anchorterminal.com/compare/beam-vs-hyperbolic.md)\n- [Beam vs Modal](https://www.anchorterminal.com/compare/beam-vs-modal.md)\n- [Cerebrium vs Hyperbolic](https://www.anchorterminal.com/compare/cerebrium-vs-hyperbolic.md)\n- [Cerebrium vs Modal](https://www.anchorterminal.com/compare/cerebrium-vs-modal.md)\n- [CoreWeave vs Hyperbolic](https://www.anchorterminal.com/compare/coreweave-vs-hyperbolic.md)\n- [CoreWeave vs Modal](https://www.anchorterminal.com/compare/coreweave-vs-modal.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 Modal](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-modal.md)\n- [Hyperbolic vs Koyeb](https://www.anchorterminal.com/compare/hyperbolic-vs-koyeb.md)\n- [Hyperbolic vs Lambda Cloud](https://www.anchorterminal.com/compare/hyperbolic-vs-lambda.md)\n- [Hyperbolic vs Nebius AI Cloud](https://www.anchorterminal.com/compare/hyperbolic-vs-nebius-ai-cloud.md)\n- [Hyperbolic vs Northflank](https://www.anchorterminal.com/compare/hyperbolic-vs-northflank.md)\n- [Hyperbolic vs Replicate Deployments](https://www.anchorterminal.com/compare/hyperbolic-vs-replicate-deploy.md)\n- [Hyperbolic vs Runpod](https://www.anchorterminal.com/compare/hyperbolic-vs-runpod.md)\n- [Hyperbolic vs Thunder Compute](https://www.anchorterminal.com/compare/hyperbolic-vs-thunder-compute.md)\n- [Hyperbolic vs Vast.ai](https://www.anchorterminal.com/compare/hyperbolic-vs-vast-ai.md)\n- [Hyperbolic vs Verda](https://www.anchorterminal.com/compare/hyperbolic-vs-verda.md)\n- [Koyeb vs Modal](https://www.anchorterminal.com/compare/koyeb-vs-modal.md)\n- [Lambda Cloud vs Modal](https://www.anchorterminal.com/compare/lambda-vs-modal.md)\n- [Modal vs Nebius AI Cloud](https://www.anchorterminal.com/compare/modal-vs-nebius-ai-cloud.md)\n- [Modal vs Northflank](https://www.anchorterminal.com/compare/modal-vs-northflank.md)\n- [Modal vs Replicate Deployments](https://www.anchorterminal.com/compare/modal-vs-replicate-deploy.md)\n- [Modal vs Runpod](https://www.anchorterminal.com/compare/modal-vs-runpod.md)\n- [Modal vs Thunder Compute](https://www.anchorterminal.com/compare/modal-vs-thunder-compute.md)\n- [Modal vs Vast.ai](https://www.anchorterminal.com/compare/modal-vs-vast-ai.md)\n- [Modal vs Verda](https://www.anchorterminal.com/compare/modal-vs-verda.md)\n",
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    "description": "Modal scores 63.6 (B) on agent readiness against Hyperbolic's 48 (D), and leads in 6 of 7 scored categories. Hyperbolic leads on schema \u0026 documentation. Both do compute gpu. Category scores, facts, verdicts and agent notes side by side.",
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    "title": "Hyperbolic vs Modal for AI agents, D 48 vs B 63.6 | Anchor Terminal",
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