{ "data": { "a": { "slug": "together-gpu-clusters", "name": "Together GPU Clusters", "vendor": "Together AI", "vendorUrl": "https://www.together.ai", "kind": "http-api", "category": "gpu-compute", "summary": "Together GPU Clusters rents multi-node NVIDIA H100, H200, B200 and B300 clusters with InfiniBand and shared storage, run as Kubernetes or Slurm, by the GPU-hour. Clusters are created and scaled from the console, the tg CLI, SDKs or REST API.", "url": "https://www.anchorterminal.com/tools/together-gpu-clusters", "markdownUrl": "https://www.anchorterminal.com/tools/together-gpu-clusters.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/together-gpu-clusters.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/together-gpu-clusters.json", "dns": "together-gpu-clusters.grade.anchorterminal.com", "repo": "https://github.com/togethercomputer/together-py", "license": "Proprietary service under Together's terms of service. The Python SDK and CLI are Apache-2.0 and the OpenAPI document is MIT", "transports": [], "remoteUrl": "https://api.together.ai/v1/compute/clusters", "packages": [ { "registry": "pypi", "name": "together" }, { "registry": "npm", "name": "together-ai" } ], "auth": "api-key", "authNotes": "Bearer `TOGETHER_API_KEY`, scoped to a project, revocable and optionally expiring, the same keys as Together's other APIs. Only a project admin's key returns the cluster's admin kubeconfig. Team members can reach the Kubernetes API through OIDC with their own identity provider, and SSH uses OIDC or uploaded keys.", "pricing": "usage", "pricingNotes": "On-demand from $3.99 per GPU-hour (H100) to $9.99 (B300); reserved 3 to 180 days from $3.19 to $7.99; preemptible (preview) from $1.99. Storage per GiB-month. No ingress or egress fees. Reservations are prepaid and non-refundable, and creation needs enough credit to cover them.", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the GPU clusters docs, billing pages or OpenAPI document (checked 2026-11-06). An exhausted balance returns 402 to scale requests with no payment requirements.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-06" }, "docsUrl": "https://docs.together.ai/docs/gpu-clusters-overview", "llmsTxt": "https://docs.together.ai/llms.txt", "openapi": "https://github.com/togethercomputer/openapi", "capabilities": [ "compute.gpu", "compute.containers", "compute.batch" ], "tags": [ "hosted", "official", "usage", "prepaid", "openapi", "llms-txt", "kubernetes", "slurm", "python", "typescript", "cli", "h100", "b200" ], "lastRelease": "2026-10-22", "graded": true, "anchor": { "graded": true, "score": 58.1, "grade": "C", "agentReady": false, "rank": 768, "ranked": true, "rankOf": 1510, "categoryRank": 10, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 55, "maintenance": 75, "payments": 20, "reliability": 38, "schema": 92, "security": 68, "transparency": 65 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "Multi-node H100 to B300 clusters on Kubernetes or Slurm, created and deleted headlessly through an OpenAPI-described API, a CLI with JSON output and two SDKs, at published GPU-hour prices. Clusters take 10 minutes to an hour to provision, can't be paused, and have no status component, SLA or idempotent create.", "bestFor": "Training, fine-tuning and batch jobs that need several 8-GPU nodes with InfiniBand, run by a pipeline that creates and deletes clusters.", "strengths": [ "Public OpenAPI 3.1, llms.txt and Markdown docs, with an automation guide for CI pipelines", "Published per GPU-hour prices for on-demand, reserved and preemptible capacity, with no egress fees", "Kubernetes or Slurm on the same hardware, with InfiniBand and a persistent shared volume", "Automatic health checks and node repair, approved by hand or run automatically", "Project-scoped keys, admin-only kubeconfig and OIDC access for team members" ], "weaknesses": [ "Provisioning takes 10 minutes to an hour, and a cluster can't be paused or scaled to zero", "No status page component, SLA or published rate limits for GPU clusters", "No idempotency key on creation, so a retried create can bill a second cluster", "No free trial; reservations are prepaid and non-refundable", "Volumes bill until deleted and outlive the clusters they were attached to" ], "agentNotes": [ "Use `tg clusters`, not `tg beta clusters`, which stopped working with CLI 3.0 on 22 October 2026", "Pass `--json` and `--non-interactive`, poll `tg clusters retrieve` until status is Ready, and delete the cluster in a cleanup step", "Check for an existing cluster by name before retrying a create, since creation has no idempotency key", "Read live availability from the regions API and prices from the pricing page; the regions response has no prices", "Use a project admin's key when the task needs the kubeconfig, since other roles get none" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 58.1 } ], "editorialScores": { "ergonomics": 55, "maintenance": 75, "payments": 20, "reliability": 38, "schema": 92, "security": 68, "transparency": 46 }, "provenanceScore": 83, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "uv tool install \"together[cli]\"", "http": "curl -H \"Authorization: Bearer $TOGETHER_API_KEY\" https://api.together.ai/v1/compute/clusters" }, "letme": { "capability": "https://letme.dev/compute.gpu", "tool": "https://letme.dev/together-gpu-clusters" }, "sameCompany": [ "together-inference", "together-fine-tuning", "together-code-sandbox" ], "area": "models", "unitPrices": [ { "item": "H100 on-demand", "unit": "gpu-hour", "usd": 3.99, "note": "reserved $3.69 to $3.19, preemptible $1.99" }, { "item": "H200 on-demand", "unit": "gpu-hour", "usd": 5.99, "note": "reserved $4.99 to $3.99, preemptible $2.99" }, { "item": "B200 on-demand", "unit": "gpu-hour", "usd": 8.19, "note": "reserved $7.99 to $6.79, preemptible $4.09" }, { "item": "B300 on-demand", "unit": "gpu-hour", "usd": 9.99, "note": "preemptible $4.99, reserved by sales" } ], "provenance": { "legalEntity": "Together Computer, Inc.", "domain": "together.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://www.together.ai/terms-of-service", "privacy": "https://www.together.ai/privacy", "statusPage": "https://status.together.ai", "changelog": "https://docs.together.ai/docs/changelog", "securityTxt": "valid", "checked": "2026-11-06", "notes": [ "Legal entity, terms, privacy and security.txt as on the Together AI Inference listing, checked 1 November 2026, and not re-read for this listing.", "docs.together.ai/robots.txt disallows only /cdn-cgi/ and /_next/, with Content-Signal ai-train=yes, search=yes, ai-input=yes. www.together.ai/robots.txt allows all.", "status.together.ai has no component for GPU clusters on 6 November 2026." ], "score": 83 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/together-gpu-clusters.json", "live": { "slug": "together-gpu-clusters", "probe": { "target": "https://api.together.ai/v1/compute/clusters", "method": "get", "lastAt": "2026-11-07T19:22:40.660879578Z", "lastOk": true, "lastStatus": 401, "lastMs": 263, "lastNote": "asks for credentials", "authRequired": true, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 493, "p95ms24h": 857, "samples24h": 210, "samples30d": 210, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 197, "ok": 197 } ] }, "versions": [ { "registry": "github", "name": "togethercomputer/together-py", "version": "v3.1.1", "released": "2026-11-04", "seenAt": "2026-11-07T00:12:15.100983119Z" }, { "registry": "npm", "name": "together-ai", "version": "1.0.0", "seenAt": "2026-11-07T00:12:15.067840103Z" }, { "registry": "pypi", "name": "together", "version": "3.1.1", "released": "2026-11-04", "seenAt": "2026-11-07T00:12:14.921893617Z" } ], "githubStars": 12, "npmWeekly": 99619, "pypiWeekly": 424792, "securityTxt": { "url": "https://together.ai/.well-known/security.txt", "state": "valid", "expires": "2028-09-30T00:00:00.000Z", "checkedAt": "2026-11-07T16:00:47.073630606Z" }, "llmsTxt": { "url": "https://docs.together.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:34:12.138384896Z" }, "updatedAt": "2026-11-07T19:22:40.660879578Z" } }, "answer": "Together GPU Clusters scores 58.1 (C) on agent readiness against Verda's 53.3 (D), and leads in 1 of 7 scored categories. Verda leads on reliability, agent ergonomics, maintenance \u0026 community and transparency \u0026 trust.", "b": { "slug": "verda", "name": "Verda", "vendor": "Verda", "vendorUrl": "https://verda.com", "kind": "http-api", "category": "gpu-compute", "summary": "Verda, formerly DataCrunch, is a Finnish GPU cloud renting GPU and CPU instances, clusters, serverless containers and storage. Agents use its REST API, Python and Go SDKs, or a CLI with a built-in MCP server in beta.", "url": "https://www.anchorterminal.com/tools/verda", "markdownUrl": "https://www.anchorterminal.com/tools/verda.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/verda.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/verda.json", "dns": "verda.grade.anchorterminal.com", "repo": "https://github.com/verda-cloud/verda-cli", "license": "Proprietary service under Verda's Terms of Service. The CLI, the Python SDK and the Go SDK on GitHub are Apache-2.0", "transports": [ "http", "stdio" ], "remoteUrl": "https://api.verda.com/v1", "packages": [ { "registry": "pypi", "name": "verda" }, { "registry": "go", "name": "github.com/verda-cloud/verdacloud-sdk-go" } ], "auth": "oauth", "authNotes": "Self-serve. A signed-in user creates a Client ID and Client Secret on the console's Credentials page, and the secret is shown once. `POST /v1/oauth2/token` with the client credentials grant returns an access token valid for 3,600 seconds and a refresh token, both with the scope `cloud-api-v1`. Credentials belong to the member who created them and are deleted when that member leaves the project. The CLI and its MCP server read the same pair from `~/.verda/credentials` after `verda auth login`. A few catalogue endpoints such as `GET /v1/instance-types` need no token.", "pricing": "usage", "pricingNotes": "No free tier or trial. Accounts are prepaid by card or bank transfer, and Pay As You Go is charged in prepaid 10-minute increments with the unused part refunded. On-demand prices per GPU an hour on 2 November 2026 include H100 80 GB at $4.841, H200 at $6.313, B200 at $8.958, B300 at $11.46 and A100 80 GB at $2.27, with spot at half, up about 19 to 25 per cent in dollars from 8 October with no notice found. Dollar prices follow the euro list price (H100 €4.333) and move with the exchange rate, so part of the rise may be currency. Reserved terms take 2 to 25 per cent off, per the 8 October check. Serverless containers bill per minute of replica use. Free credits are granted only for approved blog posts or videos (https://verda.com/pricing).", "priceSummary": "Pay per use", "where": "both", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs corpus, the OpenAPI document or the pricing page (checked 2026-10-08).", "endpoints": [] }, "toolCount": 18, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": 10461, "asOf": "2026-10-08" }, "docsUrl": "https://docs.verda.com", "llmsTxt": "https://docs.verda.com/llms.txt", "openapi": "https://api.verda.com/v1/openapi.json", "capabilities": [ "compute.gpu", "compute.serverless", "compute.endpoints", "compute.batch", "compute.containers" ], "tags": [ "hosted", "usage-priced", "openapi", "llms-txt", "mcp", "cli", "oauth", "python", "go", "terraform", "status-page", "soc2", "europe" ], "lastRelease": "2026-10-28", "graded": true, "anchor": { "graded": true, "score": 53.3, "grade": "D", "agentReady": false, "rank": 952, "ranked": true, "rankOf": 1510, "categoryRank": 15, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 63, "maintenance": 83, "payments": 20, "reliability": 60, "schema": 72, "security": 68, "transparency": 76 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-02" }, "negative": -9, "negativeNotes": [ "2026-03-23, making `location_code` required on `POST /v1/instances`, `POST /v1/clusters` and `POST /v1/volumes`. Requests that had defaulted to FIN-01 began returning 400. The API changelog heads the change 23 March 2026 and records no advance notice. Documented, so 3 points (https://docs.verda.com/welcome-to-verda/release-notes/verda-api-changes/index.md).", "Released fixes with no advisory, -3. Python SDK `verda` 1.24.1 (12 August 2026) lists under Security a fixed path traversal in which a resource name containing `../` retargeted a call at another endpoint under the SDK's credentials (`containers.delete_deployment('../../v1/instances')` issued `DELETE /v1/instances`), and the API changelog of 20 March 2026 says API tokens \"could access internal endpoints not intended for external use\" before scopes were added. OSV holds no advisory for PyPI `verda` or the Go SDK on 2 November 2026. One folded term (https://github.com/verda-cloud/sdk-python/blob/master/CHANGELOG.md, https://docs.verda.com/welcome-to-verda/release-notes/verda-api-changes/index.md).", "Unreleased fix, -3. Commit 42f054d in verda-cloud/sdk-python (29 October 2026, \"security: check the inference request path\") says a path built from untrusted input could add query parameters or a fragment to a request that carries the inference key, and that `..;/` and `..%252f` passed the old check. It sits under `[Unreleased]` in the changelog, after 1.25.0 of 23 October (https://github.com/verda-cloud/sdk-python/commit/42f054d)." ], "verdict": "Verda documents its API changes in a dated changelog, publishes hourly GPU prices, and its CLI's MCP server refuses billed or destructive calls without `confirm: true`. Access needs a browser signup and a prepaid balance, credentials carry one scope, instance creation has no idempotency key, and two SDK security fixes in 2026 came without an advisory or release.", "bestFor": "Agents that rent whole GPU machines or clusters in Finland for training or batch work, or deploy scale-to-zero container endpoints, and that can run a local CLI for MCP.", "strengths": [ "`llms.txt` files on two hosts and the whole docs corpus as Markdown, with a dated API changelog of 24 entries in 2026", "Official Python and Go SDKs, a Terraform provider and a CLI, each released between 22 and 28 October 2026", "Hourly prices for every GPU type published in USD and EUR without a login, with spot at half the on-demand rate", "Audit log endpoint in CloudEvents 1.0 format covering 90 days, with the caller's IP address and origin on resource events", "The 18-tool MCP server refuses `create_vm`, `create_volume` and destructive `vm_action` calls unless `confirm: true` is passed" ], "weaknesses": [ "No free tier. Accounts are prepaid, and instances are discontinued and volumes deleted when the balance reaches zero", "Cloud API credentials carry one scope, `cloud-api-v1`, with no read-only credential found in the reviewed documentation", "`POST /v1/instances` has no idempotency key, so a retried launch can start a second billed instance", "The MCP server is marked beta and its tools carry no read-only or destructive annotations", "No SLA was found, and the terms give no warranty of uninterrupted availability", "The Python SDK fixed a path traversal in 1.24.1 and an inference-path flaw on 29 October 2026 with no advisory, the second in no release yet" ], "agentNotes": [ "Exchange the client ID and secret at `POST /v1/oauth2/token`, then send the access token as a Bearer header. It expires after 3,600 seconds, so refresh it.", "Send `location_code` on every create call. Requests without it have returned 400 since March 2026.", "Call `GET /v1/instance-availability` before launching. `POST /v1/instances` returns 503 `service_unavailable` when the location has no capacity.", "List instances before retrying a failed launch, because create has no idempotency key.", "Use the `delete` action to stop charges. `shutdown` keeps billing, and deleted volumes stay recoverable for 96 hours unless `delete_permanently` is set." ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 3.3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 53.3 } ], "editorialScores": { "ergonomics": 63, "maintenance": 83, "payments": 20, "reliability": 60, "schema": 72, "security": 68, "transparency": 57 }, "provenanceScore": 95, "checked": { "categories": { "ergonomics": "2026-11-02", "maintenance": "2026-11-02", "payments": "2026-11-02", "reliability": "2026-11-02", "schema": "2026-11-02", "security": "2026-11-02", "transparency": "2026-11-02" }, "last": "2026-11-02", "lastMoved": "2026-11-02", "oldest": "2026-11-02", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "brew install verda-cloud/tap/verda-cli", "http": "curl -X POST https://api.verda.com/v1/oauth2/token -H \"Content-Type: application/json\" -d '{\"grant_type\":\"client_credentials\",\"client_id\":\"\u003cYOUR_CLIENT_ID\u003e\",\"client_secret\":\"\u003cYOUR_CLIENT_SECRET\u003e\"}'", "config": { "mcpServers": { "verda": { "args": [ "mcp", "serve" ], "command": "verda" } } } }, "letme": { "capability": "https://letme.dev/compute.gpu", "tool": "https://letme.dev/verda" }, "area": "models", "unitPrices": [ { "item": "H100 SXM5 80 GB, on-demand", "unit": "gpu-hour", "usd": 4.841, "note": "Spot $2.421. Billed in prepaid 10-minute increments" }, { "item": "H200 SXM5 141 GB, on-demand", "unit": "gpu-hour", "usd": 6.313, "note": "Spot $3.157" }, { "item": "B200 SXM6 180 GB, on-demand", "unit": "gpu-hour", "usd": 8.958, "note": "Spot $4.479" }, { "item": "B300 SXM6 268 GB, on-demand", "unit": "gpu-hour", "usd": 11.46, "note": "Spot $5.73" }, { "item": "A100 SXM4 80 GB, on-demand", "unit": "gpu-hour", "usd": 2.27, "note": "Spot $1.135" }, { "item": "L40S 48 GB, on-demand", "unit": "gpu-hour", "usd": 1.92, "note": "Spot $0.96" }, { "item": "H100 SXM5 80 GB, serverless container", "unit": "gpu-hour", "usd": 5.33, "note": "Spot $2.66. Billed per minute of replica use" }, { "item": "NVMe block volume or shared filesystem", "unit": "gb-month", "usd": 0.2, "note": "Per GiB" } ], "provenance": { "legalEntity": "DataCrunch Oy", "domain": "verda.com", "domainRegistered": "1998-05-22", "endpointOnVendorDomain": true, "terms": "https://verda.com/terms-and-conditions", "privacy": "https://verda.com/privacy-policy", "statusPage": "https://status.verda.com", "changelog": "https://docs.verda.com/welcome-to-verda/release-notes/verda-api-changes/", "securityTxt": "valid", "checked": "2026-10-08", "notes": [ "The Terms of Service, last updated 30 September 2025, name the supplier as Verda (DataCrunch Oy), apply Finnish law and set arbitration in Helsinki. They include the data processing terms.", "The CLI source carries the copyright of Verda Cloud Oy.", "The API answers at api.verda.com, a subdomain of the vendor domain.", "security.txt expires on 31 December 2026, lists security@verda.com and a policy at https://vdp.verda.com.", "RDAP for verda.com gives a registration date of 1998-05-22. The company took the Verda name later, and verda.com/llms.txt says it was previously known as DataCrunch.", "The privacy policy covers the website and the services and shows no readable date." ], "score": 95 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/verda.json", "live": { "slug": "verda", "probe": { "target": "https://api.verda.com/v1", "method": "get", "lastAt": "2026-11-07T19:22:42.939055171Z", "lastOk": true, "lastStatus": 401, "lastMs": 84, "lastNote": "asks for credentials", "authRequired": true, "uptime24h": 100, "uptime30d": 99.93, "p50ms24h": 100, "p95ms24h": 188, "samples24h": 238, "samples30d": 7299, "days": [ { "date": "2026-10-09", "probes": 169, "ok": 169 }, { "date": "2026-10-10", "probes": 247, "ok": 247 }, { "date": "2026-10-11", "probes": 247, "ok": 247 }, { "date": "2026-10-12", "probes": 247, "ok": 247 }, { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 249 }, { "date": "2026-10-15", "probes": 253, "ok": 253 }, { "date": "2026-10-16", "probes": 252, "ok": 252 }, { "date": "2026-10-17", "probes": 253, "ok": 253 }, { "date": "2026-10-18", "probes": 256, "ok": 256 }, { "date": "2026-10-19", "probes": 255, "ok": 254 }, { "date": "2026-10-20", "probes": 252, "ok": 252 }, { "date": "2026-10-21", "probes": 253, "ok": 253 }, { "date": "2026-10-22", "probes": 253, "ok": 253 }, { "date": "2026-10-23", "probes": 248, "ok": 248 }, { "date": "2026-10-24", "probes": 251, "ok": 251 }, { "date": "2026-10-25", "probes": 250, "ok": 250 }, { "date": "2026-10-26", "probes": 252, "ok": 252 }, { "date": "2026-10-27", "probes": 249, "ok": 249 }, { "date": "2026-10-28", "probes": 250, "ok": 249 }, { "date": "2026-10-29", "probes": 249, "ok": 249 }, { "date": "2026-10-30", "probes": 249, "ok": 249 }, { "date": "2026-10-31", "probes": 251, "ok": 251 }, { "date": "2026-11-01", "probes": 249, "ok": 249 }, { "date": "2026-11-02", "probes": 250, "ok": 247 }, { "date": "2026-11-03", "probes": 248, "ok": 248 }, { "date": "2026-11-04", "probes": 246, "ok": 246 }, { "date": "2026-11-05", "probes": 185, "ok": 185 }, { "date": "2026-11-06", "probes": 241, "ok": 241 }, { "date": "2026-11-07", "probes": 197, "ok": 197 } ] }, "vendorStatus": { "page": "https://status.verda.com", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-07T04:48:56.698835616Z" }, "versions": [ { "registry": "github", "name": "verda-cloud/verda-cli", "version": "v1.10.0", "released": "2026-11-06", "seenAt": "2026-11-07T00:15:17.154297899Z" }, { "registry": "pypi", "name": "verda", "version": "1.25.0", "released": "2026-10-23", "seenAt": "2026-11-07T00:15:16.973607792Z" } ], "githubStars": 16, "pypiWeekly": 9525, "securityTxt": { "url": "https://verda.com/.well-known/security.txt", "state": "valid", "expires": "2026-12-31T11:59:00Z", "checkedAt": "2026-11-07T16:00:49.972736209Z" }, "llmsTxt": { "url": "https://docs.verda.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:34:16.894348703Z" }, "domain": { "domain": "verda.com", "registered": "1998-05-22", "source": "https://rdap.verisign.com/com/v1/domain/verda.com", "checkedAt": "2026-11-01T14:13:48.625189825Z" }, "pages": [ { "url": "https://docs.verda.com/welcome-to-verda/release-notes/verda-api-changes/", "kind": "changelog", "status": 304, "checkedAt": "2026-11-07T14:08:35.488323411Z", "changedAt": "2026-11-05T12:32:20.917395122Z", "fingerprint": "edd04ebbd363" }, { "url": "https://verda.com/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-11-07T14:23:19.050824521Z", "changedAt": "2026-11-07T14:23:19.050824521Z", "fingerprint": "1777e38584d3" }, { "url": "https://verda.com/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:23:21.35557714Z", "changedAt": "2026-11-07T14:23:21.35557714Z", "fingerprint": "bcf01daa54c0" }, { "url": "https://verda.com/terms-and-conditions", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:23:23.638199688Z", "changedAt": "2026-11-07T14:23:23.638199688Z", "fingerprint": "95ec6c6c21ba" } ], "github": { "repo": "verda-cloud/verda-cli", "checkedAt": "2026-11-02T09:35:54.540508327Z", "stars": 16, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-28T16:20:14Z", "openIssues": 1, "openPRs": 0, "issuesOpened90d": 1, "issuesClosed90d": 1, "prsMerged90d": 9, "ci": { "branch": "main", "runs": 50, "success": 48, "failure": 2, "other": 0, "latest": "success", "latestAt": "2026-10-28T16:20:17Z" }, "replies": { "sampled": 4, "unanswered": 1, "medianDays": 2.2 } }, "updatedAt": "2026-11-07T19:22:42.939055171Z" } }, "edges": [ { "by": 22, "category": "reliability", "leads": "verda", "name": "Reliability", "reasons": { "a": "Read with the hosted lines. status.together.ai lists the website, the playground and serverless models with no component for GPU clusters, and a vendor page with no component for the product takes 15 in this run, as for Together's Code Sandbox and fine-tuning listings (15). No incident history for clusters can be read (5). No rate limits for the clusters API found (0). Together's docs give 429 and 503 backoff guidance for its APIs, per the inference listing's 1 November check, and the CLI has `--non-interactive` and `--json` for scripted retries, but creation has no idempotency key (8). No SLA for clusters found; the published 99% commitment covers provisioned inference throughput only (0). Generally available since 9 September 2025 and out of the CLI's beta paths since 22 October 2026, with preemptible nodes in preview (10). 15+5+0+8+0+10 = 38.", "b": "Graded on the hosted lines for the REST API. BetterStack page at status.verda.com with 21 components, 180-day bars and an RSS feed (20). The feed lists eight incidents from 4 August to 2 November 2026, none posted against the API component and each limited to one product, one location or some customers. Serverless Containers were slow or unavailable for about 9.5 hours on 13 August, the container gateway returned intermittent 500s on 4 September, container uploads failed for about 2 hours on 20 September, a small number of instances, volumes and billing records were affected on 25 September, Serverless Containers degraded during a security update on 9 October, FIN03 services and Google SSO sign-in failed during maintenance on 11 October, the container registry vccr.io was down on 19 October, and FIN-02 lost network connectivity on 23 October. This run reads all of them as partial, minor only (20). api.verda.com, which hosts the API reference with the rate limits, answered robots.txt with 401 on 2 November 2026, so the 8 October readings from its OpenAPI document are struck. The docs' changelog says rate limits apply since 11 March 2026 and points to that reference, with no numbers on a page we can read (0). The official Go SDK's retry middleware backs off on 429 and 5xx, instance actions already in the requested state answer 204 and volume deletion is idempotent per the docs' changelog, and serverless job request IDs answer 409 on a repeat, but instance creation has no idempotency key and Retry-After is documented only on the refused host (10 of 15). No SLA found, and the terms give no warranty of uninterrupted availability (0). The REST API is generally available, while the CLI's MCP server is marked beta (10)." }, "scores": { "a": 38, "b": 60 } }, { "by": 20, "category": "schema", "leads": "together-gpu-clusters", "name": "Schema \u0026 documentation", "reasons": { "a": "Public OpenAPI 3.1 for /v1/compute/clusters and shared volumes, MIT, embedded in every reference page (25). llms.txt and a Markdown twin of every page (10). The docs say when to choose Kubernetes or Slurm and each capacity type, and the management page carries instructions for agents on reporting live availability and prices (18). Enums for cluster type, billing type, GPU type and status, required fields marked (13). CLI, Python, TypeScript and console steps on each task, with 402 and 403 cases documented, though no error catalogue for the clusters API (11). Versioned SDKs and a dated changelog with cluster entries (15). 25+10+18+13+11+15 = 92.", "b": "api.verda.com's robots.txt answered 401 on 2 November 2026, so the OpenAPI document and the API reference there weren't read and the 8 October counts taken from them (112 operations, 156 schemas, 104 enums, 756 examples) are struck. The docs' changelog names the OpenAPI specification and its schemas (oneOf for UUID-or-array fields, the 19 March 2026 auth fix), and the Go and Python SDKs carry typed models, but no per-operation reference is readable on an allowed host (20 of 25). `llms.txt` on verda.com and docs.verda.com, every docs page as Markdown and the corpus in `llms-full.txt` (10). Docs guides and changelog entries describe what endpoints do and their billing effects, for example that `shutdown` keeps charging, while the reference descriptions are unread (10 of 20). Required fields and enums are visible only through the SDKs' typed models and validation, such as the Go SDK's limits added in v1.7.0, and the docs ask clients to treat enums as open (8 of 15). The docs corpus carries 62 curl examples and the Python SDK lists seven error codes, while per-operation error responses sit in the unread reference (9 of 15). Versioned in the path, with a dated changelog of 24 entries in 2026, the newest on 7 October (15)." }, "scores": { "a": 92, "b": 72 } }, { "by": 11, "category": "transparency", "leads": "verda", "name": "Transparency \u0026 trust", "reasons": { "a": "Closed service under Together's terms, with Apache-2.0 SDKs, which don't raise the line for a closed API (15). The privacy policy's data table covers GPU clusters, per the 4 November Code Sandbox check, and the billing page states when volumes are deleted after credit runs out, with no retention period for data on deleted clusters (15). The 3.0 breaking change came with a migration guide on the day, and reservations carry dated end-of-term emails, with no notice period for API changes found (8). Regions are listed through the API and US regions appear in examples; subprocessors and data locations for clusters were not established (8). 15+15+8+8 = 46.", "b": "Closed service under Terms of Service dated 30 September 2025 and Finnish law. The CLI and SDKs are Apache-2.0 (15 of 30). The terms include data processing terms, and the privacy policy has a retention table. Deleted customer data is removed within 96 hours per the privacy policy and clause 10.9.2, while Schedule 3 of the same terms says 72 hours. The privacy policy shows no readable date (20 of 30). No deprecation policy with a notice period. HDD volumes were announced as deprecated in April 2026 before creation was blocked on 21 September (10 of 20). The docs name three data centres in Helsinki, the terms promise 15 days' notice of a new sub-processor, and the privacy policy names Front and Stripe. The sub-processor list is drawn by script and we couldn't read it (12 of 20)." }, "scores": { "a": 65, "b": 76 } }, { "by": 8, "category": "ergonomics", "leads": "verda", "name": "Agent ergonomics", "reasons": { "a": "Cluster objects are compact, and `--json` gives machine-readable output, but list calls take no field selection (15). No pagination or filters on the clusters list (8). 402 and 403 with readable messages such as \"Insufficient credits for cluster creation\", and troubleshooting for common failures (12). Status polling until Ready is documented and deletes run non-interactively, but there is no idempotency key on creation and a duplicate create bills a second cluster (8). Official Python and TypeScript SDKs and a CLI, though a create takes GPU type, region, driver and CUDA versions, cluster type and billing type (12). 15+8+12+8+12 = 55.", "b": "Read from the docs' changelog and the SDKs on 2 November, since the API reference host refuses our reader. No field selection, and instance and volume lists return whole arrays (12 of 25). `page` and `pageSize` with totals in `X-Total-Count` on scripts and journals, a cursor on the audit log, and status, tag and location filters on other lists, but no pagination on instances or volumes (12 of 20). Errors carry a stable `code` and a `message`, and bulk actions return per-item results with 207 (16). Actions that are already in the requested state return 204 and volume deletion is idempotent, but create calls have no idempotency key. The MCP tools require `confirm: true` for billed and destructive calls and carry no read-only or destructive annotations (10 of 20). Official SDKs for Python and Go, a Terraform provider and a CLI. A launch needs an instance type, image, hostname, SSH key and location (13 of 15)." }, "scores": { "a": 55, "b": 63 } }, { "by": 8, "category": "maintenance", "leads": "verda", "name": "Maintenance \u0026 community", "reasons": { "a": "Closed service. The newest cluster change is CLI and SDK 3.0 on 22 October 2026, 15 days before this check (30). Dated cluster entries in the 90 days from 8 August include 12, 18, 19, 24, 27 and 28 August, 10 September and 22 October (20). Dated changelog, a support portal and Discord, with responsiveness not tested (8). Python SDK 3.1 and TypeScript SDK 1.0 are current and cover clusters (15). SDK CI and dependencies weren't audited (2). 30+20+8+15+2 = 75.", "b": "Dated sources counted on 2 November. Go SDK `verdacloud-sdk-go` v1.7.0 on 28 October 2026, Python SDK `verda` 1.25.0 on 23 October, CLI v1.9.0 on 22 October, and the newest API changelog entry on 7 October (30). 11 dated API entries from 11 September to 7 October 2026, plus Go SDK v1.4.3, v1.5.0, v1.6.0, v1.6.1, v1.6.2 and v1.7.0, Python SDK 1.24.1 and 1.25.0 and CLI v1.8.1, v1.8.2 and v1.9.0 in the 90 days (20). A public changelog, monthly release notes, email and chat support and a forum. GitHub issues were not read (10 of 15). Current official clients for Python and Go, a Terraform provider and a CLI (15). The CLI repository runs lint, test and security workflows, and the Go SDK added a go fix check on 27 October 2026 (8 of 10)." }, "scores": { "a": 75, "b": 83 } } ], "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "Together AI", "b": "Verda", "name": "Vendor" }, { "a": "https://api.together.ai/v1/compute/clusters", "b": "https://api.verda.com/v1", "name": "Hosted endpoint" }, { "a": "", "b": "HTTP, stdio", "name": "Transports" }, { "a": "API key", "b": "OAuth", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary service under Together's terms of service. The Python SDK and CLI are Apache-2.0 and the OpenAPI document is MIT", "b": "Proprietary service under Verda's Terms of Service. The CLI, the Python SDK and the Go SDK on GitHub are Apache-2.0", "name": "Licence" }, { "a": "none", "b": "18", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-22", "b": "2026-10-28", "name": "Last release" }, { "a": "no date given", "b": "2025-09-30", "name": "Terms last updated" }, { "a": "no date given", "b": "no date given", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "yes", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "10k PyPI/wk", "name": "Popularity" }, { "a": "none", "b": "3.3/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Together GPU Clusters scores 58.1 (C) on agent readiness against Verda's 53.3 (D), and leads in 1 of 7 scored categories. Verda leads on reliability, agent ergonomics, maintenance \u0026 community and transparency \u0026 trust.", "question": "Which is better for AI agents, Together GPU Clusters or Verda?" }, { "answer": "Together GPU Clusters needs an API key. Verda uses an OAuth sign-in.", "question": "Do Together GPU Clusters and Verda need an API key?" }, { "answer": "Yes. Together GPU Clusters has a hosted endpoint at https://api.together.ai/v1/compute/clusters and Verda at https://api.verda.com/v1.", "question": "Can an agent call Together GPU Clusters and Verda without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Schema \u0026 documentation, 92 against 72" ], "also": [ "No incidents deducted, where Verda loses 9 points for them" ], "goodFor": "Training, fine-tuning and batch jobs that need several 8-GPU nodes with InfiniBand, run by a pipeline that creates and deletes clusters.", "slug": "together-gpu-clusters", "watchFor": "Provisioning takes 10 minutes to an hour, and a cluster can't be paused or scaled to zero" }, { "aheadOn": [ "Reliability, 60 against 38", "Agent ergonomics, 63 against 55", "Maintenance \u0026 community, 83 against 75", "Transparency \u0026 trust, 76 against 65" ], "also": [ "Runs on your own machine" ], "goodFor": "Agents that rent whole GPU machines or clusters in Finland for training or batch work, or deploy scale-to-zero container endpoints, and that can run a local CLI for MCP.", "slug": "verda", "watchFor": "No free tier. Accounts are prepaid, and instances are discontinued and volumes deleted when the balance reaches zero" } ], "history": { "together-gpu-clusters": null, "verda": [ { "causes": [ "security", "evidence" ], "date": "2026-11-02", "delta": -9, "from": 62.3, "fromGrade": "B", "to": 53.3, "toGrade": "D" } ] }, "job": { "capability": "compute.gpu", "name": "GPU compute" }, "others": [ { "json": "https://www.anchorterminal.com/compare/baseten-vs-together-gpu-clusters.json", "title": "Baseten vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/baseten-vs-together-gpu-clusters" }, { "json": "https://www.anchorterminal.com/compare/baseten-vs-verda.json", "title": "Baseten vs Verda", "url": "https://www.anchorterminal.com/compare/baseten-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/beam-vs-together-gpu-clusters.json", "title": "Beam vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/beam-vs-together-gpu-clusters" }, { "json": "https://www.anchorterminal.com/compare/beam-vs-verda.json", "title": "Beam vs Verda", "url": "https://www.anchorterminal.com/compare/beam-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/cerebrium-vs-together-gpu-clusters.json", "title": "Cerebrium vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/cerebrium-vs-together-gpu-clusters" }, { "json": "https://www.anchorterminal.com/compare/cerebrium-vs-verda.json", "title": "Cerebrium vs Verda", "url": "https://www.anchorterminal.com/compare/cerebrium-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/cloud-run-gpus-vs-together-gpu-clusters.json", "title": "Cloud Run GPUs vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/cloud-run-gpus-vs-together-gpu-clusters" }, { "json": "https://www.anchorterminal.com/compare/coreweave-vs-together-gpu-clusters.json", "title": "CoreWeave vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/coreweave-vs-together-gpu-clusters" }, { "json": "https://www.anchorterminal.com/compare/coreweave-vs-verda.json", "title": "CoreWeave vs Verda", "url": "https://www.anchorterminal.com/compare/coreweave-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/crusoe-cloud-vs-together-gpu-clusters.json", "title": "Crusoe Cloud vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/crusoe-cloud-vs-together-gpu-clusters" }, { "json": "https://www.anchorterminal.com/compare/crusoe-cloud-vs-verda.json", "title": "Crusoe Cloud vs Verda", "url": "https://www.anchorterminal.com/compare/crusoe-cloud-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/gpusmarket-vs-together-gpu-clusters.json", "title": "GPUsMarket vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/gpusmarket-vs-together-gpu-clusters" }, { "json": "https://www.anchorterminal.com/compare/gpusmarket-vs-verda.json", "title": "GPUsMarket vs Verda", "url": "https://www.anchorterminal.com/compare/gpusmarket-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-together-gpu-clusters.json", "title": "Hugging Face Inference Endpoints vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-together-gpu-clusters" }, { "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-together-gpu-clusters.json", "title": "Hyperbolic vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/hyperbolic-vs-together-gpu-clusters" }, { "json": "https://www.anchorterminal.com/compare/hyperbolic-vs-verda.json", "title": "Hyperbolic vs Verda", "url": "https://www.anchorterminal.com/compare/hyperbolic-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/koyeb-vs-together-gpu-clusters.json", "title": "Koyeb vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/koyeb-vs-together-gpu-clusters" }, { "json": "https://www.anchorterminal.com/compare/koyeb-vs-verda.json", "title": "Koyeb vs Verda", "url": "https://www.anchorterminal.com/compare/koyeb-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/lambda-vs-together-gpu-clusters.json", "title": "Lambda Cloud vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/lambda-vs-together-gpu-clusters" }, { "json": "https://www.anchorterminal.com/compare/lambda-vs-verda.json", "title": "Lambda Cloud vs Verda", "url": "https://www.anchorterminal.com/compare/lambda-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/massed-compute-vs-together-gpu-clusters.json", "title": "Massed Compute vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/massed-compute-vs-together-gpu-clusters" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/modal-vs-together-gpu-clusters.json", "title": "Modal vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/modal-vs-together-gpu-clusters" }, { "json": "https://www.anchorterminal.com/compare/modal-vs-verda.json", "title": "Modal vs Verda", "url": "https://www.anchorterminal.com/compare/modal-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/nebius-ai-cloud-vs-together-gpu-clusters.json", "title": "Nebius AI Cloud vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/nebius-ai-cloud-vs-together-gpu-clusters" }, { "json": "https://www.anchorterminal.com/compare/nebius-ai-cloud-vs-verda.json", "title": "Nebius AI Cloud vs Verda", "url": "https://www.anchorterminal.com/compare/nebius-ai-cloud-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/northflank-vs-together-gpu-clusters.json", "title": "Northflank vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/northflank-vs-together-gpu-clusters" }, { "json": "https://www.anchorterminal.com/compare/northflank-vs-verda.json", "title": "Northflank vs Verda", "url": "https://www.anchorterminal.com/compare/northflank-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/replicate-deploy-vs-together-gpu-clusters.json", "title": "Replicate Deployments vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/replicate-deploy-vs-together-gpu-clusters" }, { "json": "https://www.anchorterminal.com/compare/replicate-deploy-vs-verda.json", "title": "Replicate Deployments vs Verda", "url": "https://www.anchorterminal.com/compare/replicate-deploy-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/runpod-vs-together-gpu-clusters.json", "title": "Runpod vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/runpod-vs-together-gpu-clusters" }, { "json": "https://www.anchorterminal.com/compare/runpod-vs-verda.json", "title": "Runpod vs Verda", "url": "https://www.anchorterminal.com/compare/runpod-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/thunder-compute-vs-together-gpu-clusters.json", "title": "Thunder Compute vs Together GPU Clusters", "url": "https://www.anchorterminal.com/compare/thunder-compute-vs-together-gpu-clusters" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/together-gpu-clusters-vs-vast-ai.json", "title": "Together GPU Clusters vs Vast.ai", "url": "https://www.anchorterminal.com/compare/together-gpu-clusters-vs-vast-ai" }, { "json": "https://www.anchorterminal.com/compare/vast-ai-vs-verda.json", "title": "Vast.ai vs Verda", "url": "https://www.anchorterminal.com/compare/vast-ai-vs-verda" }, { "json": "https://www.anchorterminal.com/compare/cloud-run-gpus-vs-verda.json", "title": "Cloud Run GPUs vs Verda", "url": "https://www.anchorterminal.com/compare/cloud-run-gpus-vs-verda" } ], "panel": null, "scores": [ { "by": 22, "edge": "verda", "key": "reliability", "name": "Reliability", "together-gpu-clusters": 38, "verda": 60, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 20, "edge": "together-gpu-clusters", "key": "schema", "name": "Schema \u0026 documentation", "together-gpu-clusters": 92, "verda": 72, "weight": 13 }, { "by": 8, "edge": "verda", "key": "ergonomics", "name": "Agent ergonomics", "together-gpu-clusters": 55, "verda": 63, "weight": 13 }, { "by": 0, "edge": "", "key": "security", "name": "Security \u0026 auth", "together-gpu-clusters": 68, "verda": 68, "weight": 14 }, { "by": 0, "edge": "", "key": "payments", "name": "Payments \u0026 pricing", "together-gpu-clusters": 20, "verda": 20, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 8, "edge": "verda", "key": "maintenance", "name": "Maintenance \u0026 community", "together-gpu-clusters": 75, "verda": 83, "weight": 7 }, { "by": 11, "edge": "verda", "key": "transparency", "name": "Transparency \u0026 trust", "together-gpu-clusters": 65, "verda": 76, "weight": 7 } ], "summary": "Together GPU Clusters scores 58.1 (C) on agent readiness against Verda's 53.3 (D), and leads in 1 of 7 scored categories. Verda leads on reliability, agent ergonomics, maintenance \u0026 community and transparency \u0026 trust. Both do gpu compute.", "tasks": null, "tutorials": [], "verdicts": { "together-gpu-clusters": "Multi-node H100 to B300 clusters on Kubernetes or Slurm, created and deleted headlessly through an OpenAPI-described API, a CLI with JSON output and two SDKs, at published GPU-hour prices. Clusters take 10 minutes to an hour to provision, can't be paused, and have no status component, SLA or idempotent create.", "verda": "Verda documents its API changes in a dated changelog, publishes hourly GPU prices, and its CLI's MCP server refuses billed or destructive calls without `confirm: true`. Access needs a browser signup and a prepaid balance, credentials carry one scope, instance creation has no idempotency key, and two SDK security fixes in 2026 came without an advisory or release." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/together-gpu-clusters-vs-verda", "json": "https://www.anchorterminal.com/compare/together-gpu-clusters-vs-verda.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/together-gpu-clusters-vs-verda.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/together-gpu-clusters-vs-verda.min.md" }, "markdown": "Together GPU Clusters scores 58.1 (C) on agent readiness against Verda's 53.3 (D), and leads in 1 of 7 scored categories. Verda leads on reliability, agent ergonomics, maintenance \u0026 community and transparency \u0026 trust. Both do gpu compute.\n\n- Together GPU Clusters: grade C, 58.1/100, rank #768 of 1510. Markdown https://www.anchorterminal.com/tools/together-gpu-clusters.md · JSON https://www.anchorterminal.com/api/v1/tools/together-gpu-clusters.json\n- Verda: grade D, 53.3/100, rank #952 of 1510. Markdown https://www.anchorterminal.com/tools/verda.md · JSON https://www.anchorterminal.com/api/v1/tools/verda.json\n- Best GPU and serverless compute for AI workloads: https://www.anchorterminal.com/best/gpu-compute/index.md\n- All 231 gpu compute comparisons: https://www.anchorterminal.com/compare/gpu-compute/index.md\n\n## Which one, for what\n\n### Together GPU Clusters (C)\n\nGood for: Training, fine-tuning and batch jobs that need several 8-GPU nodes with InfiniBand, run by a pipeline that creates and deletes clusters.\n\nAhead on:\n- Schema \u0026 documentation, 92 against 72\n\nAlso in its favour:\n- No incidents deducted, where Verda loses 9 points for them\n\nWatch for: Provisioning takes 10 minutes to an hour, and a cluster can't be paused or scaled to zero\n\n### Verda (D)\n\nGood for: Agents that rent whole GPU machines or clusters in Finland for training or batch work, or deploy scale-to-zero container endpoints, and that can run a local CLI for MCP.\n\nAhead on:\n- Reliability, 60 against 38\n- Agent ergonomics, 63 against 55\n- Maintenance \u0026 community, 83 against 75\n- Transparency \u0026 trust, 76 against 65\n\nAlso in its favour:\n- Runs on your own machine\n\nWatch for: No free tier. Accounts are prepaid, and instances are discontinued and volumes deleted when the balance reaches zero\n\n\n## Why the edge\n\n### Reliability: Verda +22\n\n- Together GPU Clusters (38): Read with the hosted lines. status.together.ai lists the website, the playground and serverless models with no component for GPU clusters, and a vendor page with no component for the product takes 15 in this run, as for Together's Code Sandbox and fine-tuning listings (15). No incident history for clusters can be read (5). No rate limits for the clusters API found (0). Together's docs give 429 and 503 backoff guidance for its APIs, per the inference listing's 1 November check, and the CLI has `--non-interactive` and `--json` for scripted retries, but creation has no idempotency key (8). No SLA for clusters found; the published 99% commitment covers provisioned inference throughput only (0). Generally available since 9 September 2025 and out of the CLI's beta paths since 22 October 2026, with preemptible nodes in preview (10). 15+5+0+8+0+10 = 38.\n- Verda (60): Graded on the hosted lines for the REST API. BetterStack page at status.verda.com with 21 components, 180-day bars and an RSS feed (20). The feed lists eight incidents from 4 August to 2 November 2026, none posted against the API component and each limited to one product, one location or some customers. Serverless Containers were slow or unavailable for about 9.5 hours on 13 August, the container gateway returned intermittent 500s on 4 September, container uploads failed for about 2 hours on 20 September, a small number of instances, volumes and billing records were affected on 25 September, Serverless Containers degraded during a security update on 9 October, FIN03 services and Google SSO sign-in failed during maintenance on 11 October, the container registry vccr.io was down on 19 October, and FIN-02 lost network connectivity on 23 October. This run reads all of them as partial, minor only (20). api.verda.com, which hosts the API reference with the rate limits, answered robots.txt with 401 on 2 November 2026, so the 8 October readings from its OpenAPI document are struck. The docs' changelog says rate limits apply since 11 March 2026 and points to that reference, with no numbers on a page we can read (0). The official Go SDK's retry middleware backs off on 429 and 5xx, instance actions already in the requested state answer 204 and volume deletion is idempotent per the docs' changelog, and serverless job request IDs answer 409 on a repeat, but instance creation has no idempotency key and Retry-After is documented only on the refused host (10 of 15). No SLA found, and the terms give no warranty of uninterrupted availability (0). The REST API is generally available, while the CLI's MCP server is marked beta (10).\n\n### Schema \u0026 documentation: Together GPU Clusters +20\n\n- Together GPU Clusters (92): Public OpenAPI 3.1 for /v1/compute/clusters and shared volumes, MIT, embedded in every reference page (25). llms.txt and a Markdown twin of every page (10). The docs say when to choose Kubernetes or Slurm and each capacity type, and the management page carries instructions for agents on reporting live availability and prices (18). Enums for cluster type, billing type, GPU type and status, required fields marked (13). CLI, Python, TypeScript and console steps on each task, with 402 and 403 cases documented, though no error catalogue for the clusters API (11). Versioned SDKs and a dated changelog with cluster entries (15). 25+10+18+13+11+15 = 92.\n- Verda (72): api.verda.com's robots.txt answered 401 on 2 November 2026, so the OpenAPI document and the API reference there weren't read and the 8 October counts taken from them (112 operations, 156 schemas, 104 enums, 756 examples) are struck. The docs' changelog names the OpenAPI specification and its schemas (oneOf for UUID-or-array fields, the 19 March 2026 auth fix), and the Go and Python SDKs carry typed models, but no per-operation reference is readable on an allowed host (20 of 25). `llms.txt` on verda.com and docs.verda.com, every docs page as Markdown and the corpus in `llms-full.txt` (10). Docs guides and changelog entries describe what endpoints do and their billing effects, for example that `shutdown` keeps charging, while the reference descriptions are unread (10 of 20). Required fields and enums are visible only through the SDKs' typed models and validation, such as the Go SDK's limits added in v1.7.0, and the docs ask clients to treat enums as open (8 of 15). The docs corpus carries 62 curl examples and the Python SDK lists seven error codes, while per-operation error responses sit in the unread reference (9 of 15). Versioned in the path, with a dated changelog of 24 entries in 2026, the newest on 7 October (15).\n\n### Transparency \u0026 trust: Verda +11\n\n- Together GPU Clusters (65): Closed service under Together's terms, with Apache-2.0 SDKs, which don't raise the line for a closed API (15). The privacy policy's data table covers GPU clusters, per the 4 November Code Sandbox check, and the billing page states when volumes are deleted after credit runs out, with no retention period for data on deleted clusters (15). The 3.0 breaking change came with a migration guide on the day, and reservations carry dated end-of-term emails, with no notice period for API changes found (8). Regions are listed through the API and US regions appear in examples; subprocessors and data locations for clusters were not established (8). 15+15+8+8 = 46.\n- Verda (76): Closed service under Terms of Service dated 30 September 2025 and Finnish law. The CLI and SDKs are Apache-2.0 (15 of 30). The terms include data processing terms, and the privacy policy has a retention table. Deleted customer data is removed within 96 hours per the privacy policy and clause 10.9.2, while Schedule 3 of the same terms says 72 hours. The privacy policy shows no readable date (20 of 30). No deprecation policy with a notice period. HDD volumes were announced as deprecated in April 2026 before creation was blocked on 21 September (10 of 20). The docs name three data centres in Helsinki, the terms promise 15 days' notice of a new sub-processor, and the privacy policy names Front and Stripe. The sub-processor list is drawn by script and we couldn't read it (12 of 20).\n\n### Agent ergonomics: Verda +8\n\n- Together GPU Clusters (55): Cluster objects are compact, and `--json` gives machine-readable output, but list calls take no field selection (15). No pagination or filters on the clusters list (8). 402 and 403 with readable messages such as \"Insufficient credits for cluster creation\", and troubleshooting for common failures (12). Status polling until Ready is documented and deletes run non-interactively, but there is no idempotency key on creation and a duplicate create bills a second cluster (8). Official Python and TypeScript SDKs and a CLI, though a create takes GPU type, region, driver and CUDA versions, cluster type and billing type (12). 15+8+12+8+12 = 55.\n- Verda (63): Read from the docs' changelog and the SDKs on 2 November, since the API reference host refuses our reader. No field selection, and instance and volume lists return whole arrays (12 of 25). `page` and `pageSize` with totals in `X-Total-Count` on scripts and journals, a cursor on the audit log, and status, tag and location filters on other lists, but no pagination on instances or volumes (12 of 20). Errors carry a stable `code` and a `message`, and bulk actions return per-item results with 207 (16). Actions that are already in the requested state return 204 and volume deletion is idempotent, but create calls have no idempotency key. The MCP tools require `confirm: true` for billed and destructive calls and carry no read-only or destructive annotations (10 of 20). Official SDKs for Python and Go, a Terraform provider and a CLI. A launch needs an instance type, image, hostname, SSH key and location (13 of 15).\n\n### Maintenance \u0026 community: Verda +8\n\n- Together GPU Clusters (75): Closed service. The newest cluster change is CLI and SDK 3.0 on 22 October 2026, 15 days before this check (30). Dated cluster entries in the 90 days from 8 August include 12, 18, 19, 24, 27 and 28 August, 10 September and 22 October (20). Dated changelog, a support portal and Discord, with responsiveness not tested (8). Python SDK 3.1 and TypeScript SDK 1.0 are current and cover clusters (15). SDK CI and dependencies weren't audited (2). 30+20+8+15+2 = 75.\n- Verda (83): Dated sources counted on 2 November. Go SDK `verdacloud-sdk-go` v1.7.0 on 28 October 2026, Python SDK `verda` 1.25.0 on 23 October, CLI v1.9.0 on 22 October, and the newest API changelog entry on 7 October (30). 11 dated API entries from 11 September to 7 October 2026, plus Go SDK v1.4.3, v1.5.0, v1.6.0, v1.6.1, v1.6.2 and v1.7.0, Python SDK 1.24.1 and 1.25.0 and CLI v1.8.1, v1.8.2 and v1.9.0 in the 90 days (20). A public changelog, monthly release notes, email and chat support and a forum. GitHub issues were not read (10 of 15). Current official clients for Python and Go, a Terraform provider and a CLI (15). The CLI repository runs lint, test and security workflows, and the Go SDK added a go fix check on 27 October 2026 (8 of 10).\n\n## Score by category\n\n| Category | Weight | Together GPU Clusters | Verda | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 38 | 60 | Verda +22 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 92 | 72 | Together GPU Clusters +20 |\n| Agent ergonomics | 13% (16.2 this run) | 55 | 63 | Verda +8 |\n| Security \u0026 auth | 14% (17.5 this run) | 68 | 68 | even |\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) | 75 | 83 | Verda +8 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 65 | 76 | Verda +11 |\n| Negative events | ≤15 | 0 | -9 | |\n| **Total** | | **58.1 · C** | **53.3 · D** | |\n\n## Facts side by side\n\n| Fact | Together GPU Clusters | Verda |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Together AI | Verda |\n| Hosted endpoint | `https://api.together.ai/v1/compute/clusters` | `https://api.verda.com/v1` |\n| Transports | | HTTP, stdio |\n| Auth | API key | OAuth |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Proprietary service under Together's terms of service. The Python SDK and CLI are Apache-2.0 and the OpenAPI document is MIT | Proprietary service under Verda's Terms of Service. The CLI, the Python SDK and the Go SDK on GitHub are Apache-2.0 |\n| Tools exposed | none | 18 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-22 | 2026-10-28 |\n| Terms last updated | no date given | 2025-09-30 |\n| Privacy policy last updated | no date given | no date given |\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 | yes | yes |\n| Terms or service can change without notice | not found in the text | not found in the text |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | none | 10k PyPI/wk |\n| Agent reviews | none | 3.3/5 (4) |\n\n## How the scores have moved\n\n### Together GPU Clusters\n\nNo score change since it was listed.\n\n### Verda\n\n- -9.0 on 2 November 2026 (B to D): security, new evidence\n\n## Verdicts\n\n**Together GPU Clusters.** Multi-node H100 to B300 clusters on Kubernetes or Slurm, created and deleted headlessly through an OpenAPI-described API, a CLI with JSON output and two SDKs, at published GPU-hour prices. Clusters take 10 minutes to an hour to provision, can't be paused, and have no status component, SLA or idempotent create.\n\n**Verda.** Verda documents its API changes in a dated changelog, publishes hourly GPU prices, and its CLI's MCP server refuses billed or destructive calls without `confirm: true`. Access needs a browser signup and a prepaid balance, credentials carry one scope, instance creation has no idempotency key, and two SDK security fixes in 2026 came without an advisory or release.\n\n## Before you call either\n\n### Together GPU Clusters\n\n1. Use `tg clusters`, not `tg beta clusters`, which stopped working with CLI 3.0 on 22 October 2026\n2. Pass `--json` and `--non-interactive`, poll `tg clusters retrieve` until status is Ready, and delete the cluster in a cleanup step\n3. Check for an existing cluster by name before retrying a create, since creation has no idempotency key\n4. Read live availability from the regions API and prices from the pricing page; the regions response has no prices\n5. Use a project admin's key when the task needs the kubeconfig, since other roles get none\n\n### Verda\n\n1. Exchange the client ID and secret at `POST /v1/oauth2/token`, then send the access token as a Bearer header. It expires after 3,600 seconds, so refresh it.\n2. Send `location_code` on every create call. Requests without it have returned 400 since March 2026.\n3. Call `GET /v1/instance-availability` before launching. `POST /v1/instances` returns 503 `service_unavailable` when the location has no capacity.\n4. List instances before retrying a failed launch, because create has no idempotency key.\n5. Use the `delete` action to stop charges. `shutdown` keeps billing, and deleted volumes stay recoverable for 96 hours unless `delete_permanently` is set.\n\n## Questions\n\n### Which is better for AI agents, Together GPU Clusters or Verda?\n\nTogether GPU Clusters scores 58.1 (C) on agent readiness against Verda's 53.3 (D), and leads in 1 of 7 scored categories. Verda leads on reliability, agent ergonomics, maintenance \u0026 community and transparency \u0026 trust.\n\n### Do Together GPU Clusters and Verda need an API key?\n\nTogether GPU Clusters needs an API key. Verda uses an OAuth sign-in.\n\n### Can an agent call Together GPU Clusters and Verda without installing anything?\n\nYes. Together GPU Clusters has a hosted endpoint at https://api.together.ai/v1/compute/clusters and Verda at https://api.verda.com/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/together-gpu-clusters-vs-verda.json, and with the fewest tokens: https://www.anchorterminal.com/compare/together-gpu-clusters-vs-verda.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"together-gpu-clusters\", \"b\": \"verda\"}`. From a terminal: `anchor compare together-gpu-clusters verda`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/together-gpu-clusters.json and https://www.anchorterminal.com/api/v1/tools/verda.json\n\n## Other comparisons with Together GPU Clusters or Verda\n\n- [Baseten vs Together GPU Clusters](https://www.anchorterminal.com/compare/baseten-vs-together-gpu-clusters.md)\n- [Baseten vs Verda](https://www.anchorterminal.com/compare/baseten-vs-verda.md)\n- [Beam vs Together GPU Clusters](https://www.anchorterminal.com/compare/beam-vs-together-gpu-clusters.md)\n- [Beam vs Verda](https://www.anchorterminal.com/compare/beam-vs-verda.md)\n- [Cerebrium vs Together GPU Clusters](https://www.anchorterminal.com/compare/cerebrium-vs-together-gpu-clusters.md)\n- [Cerebrium vs Verda](https://www.anchorterminal.com/compare/cerebrium-vs-verda.md)\n- [Cloud Run GPUs vs Together GPU Clusters](https://www.anchorterminal.com/compare/cloud-run-gpus-vs-together-gpu-clusters.md)\n- [CoreWeave vs Together GPU Clusters](https://www.anchorterminal.com/compare/coreweave-vs-together-gpu-clusters.md)\n- [CoreWeave vs Verda](https://www.anchorterminal.com/compare/coreweave-vs-verda.md)\n- [Crusoe Cloud vs Together GPU Clusters](https://www.anchorterminal.com/compare/crusoe-cloud-vs-together-gpu-clusters.md)\n- [Crusoe Cloud vs Verda](https://www.anchorterminal.com/compare/crusoe-cloud-vs-verda.md)\n- [GPUsMarket vs Together GPU Clusters](https://www.anchorterminal.com/compare/gpusmarket-vs-together-gpu-clusters.md)\n- [GPUsMarket vs Verda](https://www.anchorterminal.com/compare/gpusmarket-vs-verda.md)\n- [Hugging Face Inference Endpoints vs Together GPU Clusters](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-together-gpu-clusters.md)\n- [Hugging Face Inference Endpoints vs Verda](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-verda.md)\n- [Hyperbolic vs Together GPU Clusters](https://www.anchorterminal.com/compare/hyperbolic-vs-together-gpu-clusters.md)\n- [Hyperbolic vs Verda](https://www.anchorterminal.com/compare/hyperbolic-vs-verda.md)\n- [Koyeb vs Together GPU Clusters](https://www.anchorterminal.com/compare/koyeb-vs-together-gpu-clusters.md)\n- [Koyeb vs Verda](https://www.anchorterminal.com/compare/koyeb-vs-verda.md)\n- [Lambda Cloud vs Together GPU Clusters](https://www.anchorterminal.com/compare/lambda-vs-together-gpu-clusters.md)\n- [Lambda Cloud vs Verda](https://www.anchorterminal.com/compare/lambda-vs-verda.md)\n- [Massed Compute vs Together GPU Clusters](https://www.anchorterminal.com/compare/massed-compute-vs-together-gpu-clusters.md)\n- [Massed Compute vs Verda](https://www.anchorterminal.com/compare/massed-compute-vs-verda.md)\n- [Modal vs Together GPU Clusters](https://www.anchorterminal.com/compare/modal-vs-together-gpu-clusters.md)\n- [Modal vs Verda](https://www.anchorterminal.com/compare/modal-vs-verda.md)\n- [Nebius AI Cloud vs Together GPU Clusters](https://www.anchorterminal.com/compare/nebius-ai-cloud-vs-together-gpu-clusters.md)\n- [Nebius AI Cloud vs Verda](https://www.anchorterminal.com/compare/nebius-ai-cloud-vs-verda.md)\n- [Northflank vs Together GPU Clusters](https://www.anchorterminal.com/compare/northflank-vs-together-gpu-clusters.md)\n- [Northflank vs Verda](https://www.anchorterminal.com/compare/northflank-vs-verda.md)\n- [Replicate Deployments vs Together GPU Clusters](https://www.anchorterminal.com/compare/replicate-deploy-vs-together-gpu-clusters.md)\n- [Replicate Deployments vs Verda](https://www.anchorterminal.com/compare/replicate-deploy-vs-verda.md)\n- [Runpod vs Together GPU Clusters](https://www.anchorterminal.com/compare/runpod-vs-together-gpu-clusters.md)\n- [Runpod vs Verda](https://www.anchorterminal.com/compare/runpod-vs-verda.md)\n- [Thunder Compute vs Together GPU Clusters](https://www.anchorterminal.com/compare/thunder-compute-vs-together-gpu-clusters.md)\n- [Thunder Compute vs Verda](https://www.anchorterminal.com/compare/thunder-compute-vs-verda.md)\n- [Together GPU Clusters vs Vast.ai](https://www.anchorterminal.com/compare/together-gpu-clusters-vs-vast-ai.md)\n- [Vast.ai vs Verda](https://www.anchorterminal.com/compare/vast-ai-vs-verda.md)\n- [Cloud Run GPUs vs Verda](https://www.anchorterminal.com/compare/cloud-run-gpus-vs-verda.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-07", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Together GPU Clusters vs Verda", "url": "" } ], "description": "Together GPU Clusters scores 58.1 (C) to Verda's 53.3 (D) for gpu compute. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Together GPU Clusters C 58.1", "Verda D 53.3", "scores" ], "h1": "Together GPU Clusters vs Verda", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/together-gpu-clusters-vs-verda", "published": "2026-10-01", "section": "tools", "title": "Together GPU Clusters vs Verda for AI agents (2026) | Anchor Terminal", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/together-gpu-clusters-vs-verda" }, "tokens": { "markdown": 5300, "slim": 2980 }, "version": 1 }