# Cloud Run GPUs vs Together GPU Clusters (slim)

> Cloud Run GPUs scores 68.4 (B) to Together GPU Clusters's 58.1 (C) for gpu compute. Prices, MCP, x402, uptime and agent notes side by side.

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Cloud Run GPUs scores 68.4 (B) on agent readiness against Together GPU Clusters's 58.1 (C), and leads in 5 of 7 scored categories. Together GPU Clusters leads on schema & documentation. Both do gpu compute.

- Cloud Run GPUs: B 68.4, rank #288 of 1486 · https://www.anchorterminal.com/tools/cloud-run-gpus.min.md
- Together GPU Clusters: C 58.1, rank #764 of 1486 · https://www.anchorterminal.com/tools/together-gpu-clusters.min.md
- Cloud Run GPUs, good for Serving small and mid-size open models, or batch jobs, from a container that should scale to zero. Ahead on Reliability, 70 against 38; Agent ergonomics, 66 against 55; Security & auth, 78 against 68; Maintenance & community, 80 against 75; Transparency & trust, 84 against 65.
- Together GPU Clusters, good for Training, fine-tuning and batch jobs that need several 8-GPU nodes with InfiniBand, run by a pipeline that creates and deletes clusters. Ahead on Schema & documentation, 92 against 81.

| Category | Cloud Run GPUs | Together GPU Clusters |
| --- | --- | --- |
| Reliability (16%) | 70 | 38 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 81 | 92 |
| Agent ergonomics (13%) | 66 | 55 |
| Security & auth (14%) | 78 | 68 |
| Payments & pricing (10%) | 20 | 20 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 80 | 75 |
| Transparency & trust (7%) | 84 | 65 |

| Fact (where they differ) | Cloud Run GPUs | Together GPU Clusters |
| --- | --- | --- |
| Kind | Platform | HTTP API |
| Vendor | Google Cloud | Together AI |
| Hosted endpoint | `https://run.googleapis.com` | `https://api.together.ai/v1/compute/clusters` |
| Auth | OAuth | API key |
| Licence | Proprietary service under the Google Cloud Platform terms. Client libraries are Apache-2.0 | Proprietary service under Together's terms of service. The Python SDK and CLI are Apache-2.0 and the OpenAPI document is MIT |
| llms.txt | no | yes |
| Last release | 2026-10-30 | 2026-10-22 |
| Terms last updated | 2026-09-02 | no date given |
| Privacy policy last updated | 2026-09-28 | no date given |
| Terms restrict benchmarking | not found in the text | yes |

Why the edge:
- Reliability, Cloud Run GPUs +32: Cloud Run GPUs 70 (Hosted reading. Google Cloud's status page with a JSON incident feed (20). In the 90 days from 8 August 2026 the feed names Cloud Run in three multi-product incidents, a service outage on 20 August (15:40 to 19:20 UTC, 27 products, global and us-west1), a network degradation in us-central1-b on 1 September and a europe-west2 disruption on 20 October. One major (10). Resource limits and GPU quota are published with numbers (3 GPUs a region by default), but no request rate for the Admin API was found on the quotas page (10). Google's client libraries retry with backoff and the Admin API takes etags, while no GPU-specific retry guidance was found (10). An SLA for GPU services, 99.95% with zonal redundancy and 99.5% without (10). GPU services generally available since 7 April 2025 (10). 20+10+10+10+10+10 = 70.); 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.)
- Transparency & trust, Cloud Run GPUs +19: Cloud Run GPUs 84 (Closed service under the Google Cloud terms, with Apache-2.0 client libraries (15). The Cloud Data Processing Addendum and the privacy notice cover customer data, per the Document AI listing's 1 November reading; no Cloud Run statement on GPU instance data after shutdown was found (22). The Cloud terms promise 12 months' notice before a backwards-incompatible API change, and driver versions are announced in the release notes (16). Regions per GPU type listed, with Google's subprocessor list and data-location terms (16). 15+22+16+16 = 69.); 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.)
- Schema & documentation, Together GPU Clusters +11: Cloud Run GPUs 81 (API reading. A public Discovery document for the Cloud Run Admin API v2 (25). No llms.txt; Google's docs answer Markdown only at an unlinked `.md.txt` address, read as half, as for the Document AI listing (5). The GPU page says when to turn zonal redundancy on or off and the best-practices page when to bake models into images or load them from Cloud Storage (16). The GPU type is a free string in a node selector, with CPU and memory minimums stated in prose (9). gcloud, YAML, Terraform and console steps on each page, and errors follow Google's status model with no Cloud Run GPU error list (11). Versioned API (v1 and v2) and dated release notes (15). 25+5+16+9+11+15 = 81.); 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.)
- Agent ergonomics, Cloud Run GPUs +11: Cloud Run GPUs 66 (Platform reading. One `gcloud run deploy` with `--gpu` and `--gpu-type` adds a GPU to a container, and responses carry the service object with `fieldMask` on updates (15). List calls page with `pageSize` and `pageToken` (15). Google's status codes and messages, with quota errors that name the limit (12). Revisions are immutable, traffic can be moved back, and etags guard updates, but no idempotency key on create (12). Client libraries in many languages and gcloud, though a GPU deploy needs instance-based billing, minimum CPU and memory and, past 3 GPUs, a quota request (12). 15+15+12+12+12 = 66.); 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.)
- Security & auth, Cloud Run GPUs +10: Cloud Run GPUs 78 (OAuth 2.0 tokens from service accounts under IAM. Google's APIs accept `access_token` as a query parameter, the 10-point deduction other Google API listings take (20). IAM roles separate viewing, deploying and invoking, and services can require IAM authentication for every call (16). The platform runs your own container and returns its output (10). Cloud Audit Logs record Admin API calls, and request logs go to Cloud Logging (15). Google's vulnerability reward programme, security.txt and certifications (17). 20+16+10+15+17 = 78.); Together GPU Clusters 68 (Project-scoped API keys, revocable with optional expiry, read as Together's other listings read the same key model (30). Admin and editor roles with no read-only role. Only admins get the admin kubeconfig, which has cluster-admin rights, and OIDC lets editors use kubectl under RBAC. Deletes run without confirmation when `--non-interactive` is passed (8). The API returns cluster state, not third-party content (10). Invoices itemise reserved, on-demand and storage charges, and no audit log for cluster operations was found (5). security.txt with a HackerOne route, per the 1 November check of the inference listing (15). 30+8+10+5+15 = 68.)
- Maintenance & community, Cloud Run GPUs +5: Cloud Run GPUs 80 (Closed service with official SDKs. The newest GPU change is 30 October 2026, jobs with GPUs running up to 12 hours (30). Cloud Run release notes dated 4 November, 2 November, 30 October, 24 October and more in the 90 days (20). Release notes, Google Cloud support and public trackers for the client libraries, which were not read (10). Official client libraries in eight languages and gcloud (15). CI results not checked (5). 30+20+10+15+5 = 80.); 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.)