# Cerebrium vs Together GPU Clusters

> Together GPU Clusters scores 58.1 (C) to Cerebrium's 52.5 (D) for gpu compute. Prices, MCP, x402, uptime and agent notes side by side.

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- Updated: 2026-11-07

Together GPU Clusters scores 58.1 (C) on agent readiness against Cerebrium's 52.5 (D), and leads in 5 of 7 scored categories. Cerebrium leads on reliability and payments & pricing. Both do gpu compute.

- Cerebrium: grade D, 52.5/100, rank #989 of 1510. Markdown https://www.anchorterminal.com/tools/cerebrium.md · JSON https://www.anchorterminal.com/api/v1/tools/cerebrium.json
- 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
- Best GPU and serverless compute for AI workloads: https://www.anchorterminal.com/best/gpu-compute/index.md
- All 231 gpu compute comparisons: https://www.anchorterminal.com/compare/gpu-compute/index.md

## Which one, for what

### Cerebrium (D)

Good for: Teams serving their own models as real-time endpoints (voice, LLM, image) who want per-second billing, multi-region placement and a scriptable management API.

Ahead on:
- Reliability, 48 against 38
- Payments & pricing, 30 against 20

Watch for: `disable_auth` defaults to true, so a deployed endpoint answers without a token unless the owner changes it

### Together GPU Clusters (C)

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 70
- Agent ergonomics, 55 against 49
- Security & auth, 68 against 60
- Maintenance & community, 75 against 65

Watch for: Provisioning takes 10 minutes to an hour, and a cluster can't be paused or scaled to zero


## Why the edge

### Schema & documentation: Together GPU Clusters +22

- Cerebrium (70): Public OpenAPI 3.0 spec for the management API with 94 operations on 73 paths. Deployed endpoints take whatever the owner's function defines (25). llms.txt and a .md twin of every docs page (10). Operation descriptions are one line each. The guides say when to use the protected tier, async runs or a custom runtime (12 of 20). Required fields are marked, but the spec has no enums (valid values such as member and billing sit in prose) and several arrays and objects are untyped (7 of 15). The guides carry many worked examples. The spec has no examples and documents only 400 and 401 errors with a `message` string (8 of 15). Paths are versioned v2, v3 and v4 and CLI releases are dated on GitHub, but the spec version is a fixed 1.0.0 and no platform changelog was found (8 of 15). Docs and spec per the 8 October check, not re-read on 4 November. 25 + 10 + 12 + 7 + 8 + 8 = 70.
- 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.

### Reliability: Cerebrium +10

- Cerebrium (48): Graded as a hosted service. Status page at status.cerebrium.ai with 11 components and 90 days of history, per the 8 October check, not re-read on 4 November (cerebrium.ai's terms bar robots and automatic means) (20). The 8 October reading covered the window to that day. Since 6 August it held degradations of 5 hours 7 minutes on 19 August (US, upstream) and 7 hours 20 minutes on 2 September (EU, provider network), both partial; 9 October to 4 November is unread, so the line keeps its recorded award (10). No request rate limits found. Plans publish concurrency caps of 5 GPUs and 500 containers on Hobby and 30 and 1,000 on Standard (5 of 15). No 429 or backoff guidance for callers found. Webhook forwarding retries failed deliveries and the docs ask for idempotent webhook receivers, partly met, kept (3 of 15). No SLA found. The 99.9 and 99.999 per cent uptime figures on the site are claims without terms (0). Endpoints, the CLI and the REST API are GA, while multi-region deployment and checkpointing are marked beta (10). Docs and status per the 8 October check, not re-read on 4 November. 20 + 10 + 5 + 3 + 0 + 10 = 48.
- 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.

### Payments & pricing: Cerebrium +10

- Cerebrium (30): No machine payment protocol (0). Per-second GPU, CPU and memory prices and the storage price are published without a login (20). The Hobby plan has no fee, but compute is billed from the first second, no free compute allowance is stated and the pricing page does not say whether a card is needed, partly met, kept (10 of 20). Signup and `cerebrium login` are browser flows (0). Pricing per the 8 October check, not re-read on 4 November. 0 + 20 + 10 + 0 = 30.
- Together GPU Clusters (20): No machine payment protocol (0). Per GPU-hour prices for each capacity type and per GiB-month storage published without a login (20). No free trial, and creation needs credit for the full reservation or a minimum on-demand period (0). Sign-up and credit purchase are browser steps (0). 0+20+0+0 = 20.

### Maintenance & community: Together GPU Clusters +10

- Cerebrium (65): CLI v2.9.0 tagged on 16 September 2026, 49 days before the check, the newest tag in the repository; commits since (20 and 21 October, licence notices and a Go 1.26.10 upgrade) are untagged (20). Five tagged releases since 6 August 2026 (v2.5.4 on 7 August, v2.6.0, v2.7.0, v2.8.0, v2.9.0) (20). Closed service with a Discord community and Slack or Intercom support by plan. No platform changelog, and we couldn't read the GitHub issue tracker (8 of 25). The CLI ships on PyPI, Homebrew and as binaries. There is no language SDK (10 of 15). The repository has lint and test workflows and now pins Go 1.26.10. CI status wasn't visible in the clone (7 of 10). 20 + 20 + 8 + 10 + 7 = 65.
- 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.

### Security & auth: Together GPU Clusters +8

- Cerebrium (60): Service account tokens expire after up to one year (or never, if set to 0), are limited to 1 to 50 named projects and are revoked by deleting the account. Inference API keys are separate and can be deleted. No per-action scopes, and the CLI's SECURITY.md says tokens sit in plaintext in a config file with mode 0644 (20 of 30). Users have owner, member and billing roles, but tokens have no read-only form, and `disable_auth` defaults to true, so deployed endpoints answer without a token unless the owner changes it (5 of 20). Runs the owner's code and returns its output (10). Docs readings per the 8 October check, not re-read on 4 November. Audit log of 22 actions with actor, IP address and outcome, in the dashboard and over the API, on Standard (7 days) and Enterprise (30 days) only (12 of 15). SOC 2 Type II announced on 8 July 2026, HIPAA BAA on request, a trust centre, and disclosure to security@cerebrium.ai. No security.txt and no bug bounty found (13 of 20). No advisory for cerebrium on OSV on 4 November. 20 + 5 + 10 + 12 + 13 = 60.
- 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.

### Agent ergonomics: Together GPU Clusters +6

- Cerebrium (49): No field selection. A `limit` parameter on five list operations, and app and run objects are small (12 of 25). The audit log and runs page with `limit` and `nextToken` and filter by status, status code and time, though other lists use `page`, `pageSize` or `offset` (14 of 20). Errors are a `message` string with 400 or 401. Deployed endpoints return 200, 401, 403, 404 or 5xx, and a function can set its own `status_code` (10 of 20). No idempotency keys. Async calls return a `run_id` that can be listed and cancelled (5 of 20). Defaults are sensible (`min_replicas` 0, `cooldown` 60) and `cerebrium init` writes a working config, but there is a CLI only and no language SDK (8 of 15). Docs per the 8 October check, not re-read on 4 November; the CLI clone confirms `--output json` on list commands since 10 August. 12 + 14 + 10 + 5 + 8 = 49.
- 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.

## Score by category

| Category | Weight | Cerebrium | Together GPU Clusters | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 48 | 38 | Cerebrium +10 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 70 | 92 | Together GPU Clusters +22 |
| Agent ergonomics | 13% (16.2 this run) | 49 | 55 | Together GPU Clusters +6 |
| Security & auth | 14% (17.5 this run) | 60 | 68 | Together GPU Clusters +8 |
| Payments & pricing | 10% (12.5 this run) | 30 | 20 | Cerebrium +10 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 65 | 75 | Together GPU Clusters +10 |
| Transparency & trust | 7% (8.8 this run) | 64 | 65 | Together GPU Clusters +1 |
| Negative events | ≤15 | -2 | 0 | |
| **Total** | | **52.5 · D** | **58.1 · C** | |

## Facts side by side

| Fact | Cerebrium | Together GPU Clusters |
| --- | --- | --- |
| Kind | Platform | HTTP API |
| Vendor | Cerebrium Inc. | Together AI |
| Hosted endpoint | `https://rest.cerebrium.ai` | `https://api.together.ai/v1/compute/clusters` |
| Transports | HTTP |  |
| Auth | API key | API key |
| Pricing | Freemium | Pay per use |
| x402 | no | no |
| Licence | Proprietary service under Cerebrium's terms of service. The CLI is MIT | Proprietary service under Together's terms of service. The Python SDK and CLI are Apache-2.0 and the OpenAPI document is MIT |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-09-16 | 2026-10-22 |
| Terms last updated | no date given | no date given |
| Privacy policy last updated | no date given | no date given |
| Customer content may train models | not found in the text | not found in the text |
| Terms restrict automated access | yes | not found in the text |
| Terms restrict benchmarking | not found in the text | yes |
| Terms or service can change without notice | yes | not found in the text |
| Arbitration or class-action waiver | not found in the text | not found in the text |

## How the scores have moved

### Cerebrium

- -2.9 on 4 November 2026 (C to D): correction, time
- +0.1 on 27 October 2026: checklist

### Together GPU Clusters

No score change since it was listed.

## Verdicts

**Cerebrium.** Per-second GPU prices are public, a 94-operation OpenAPI spec covers the management API, and service account tokens expire and are limited to named projects. Deployed endpoints are callable without a token unless `disable_auth = false` is set, and no request rate limits, 429 handling or SLA were found in the reviewed documentation.

**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.

## Before you call either

### Cerebrium

1. Set `disable_auth = false` in `cerebrium.toml` before deploying. The default leaves the endpoint callable by anyone with the URL
2. Authenticate headless with `CEREBRIUM_SERVICE_ACCOUNT_TOKEN`. `cerebrium login` opens a browser
3. Raise `response_grace_period` for long work. It defaults to 15 minutes and async runs stop at 12 hours
4. Send `?async=true` to get a `run_id` with HTTP 202, and add `webhookEndpoint` because async calls return no result to the caller
5. Check the plan before choosing hardware. A100, H100, H200, B200 and RTX PRO 6000 need Standard, and `protected` compute bills at twice the listed rate

### Together GPU Clusters

1. Use `tg clusters`, not `tg beta clusters`, which stopped working with CLI 3.0 on 22 October 2026
2. Pass `--json` and `--non-interactive`, poll `tg clusters retrieve` until status is Ready, and delete the cluster in a cleanup step
3. Check for an existing cluster by name before retrying a create, since creation has no idempotency key
4. Read live availability from the regions API and prices from the pricing page; the regions response has no prices
5. Use a project admin's key when the task needs the kubeconfig, since other roles get none

## Questions

### Which is better for AI agents, Cerebrium or Together GPU Clusters?

Together GPU Clusters scores 58.1 (C) on agent readiness against Cerebrium's 52.5 (D), and leads in 5 of 7 scored categories. Cerebrium leads on reliability and payments & pricing.

### Can an agent call Cerebrium and Together GPU Clusters without installing anything?

Yes. Cerebrium has a hosted endpoint at https://rest.cerebrium.ai and Together GPU Clusters at https://api.together.ai/v1/compute/clusters.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/cerebrium-vs-together-gpu-clusters.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cerebrium-vs-together-gpu-clusters.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "cerebrium", "b": "together-gpu-clusters"}`. From a terminal: `anchor compare cerebrium together-gpu-clusters`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cerebrium.json and https://www.anchorterminal.com/api/v1/tools/together-gpu-clusters.json

## Other comparisons with Cerebrium or Together GPU Clusters

- [Baseten vs Cerebrium](https://www.anchorterminal.com/compare/baseten-vs-cerebrium.md)
- [Baseten vs Together GPU Clusters](https://www.anchorterminal.com/compare/baseten-vs-together-gpu-clusters.md)
- [Beam vs Cerebrium](https://www.anchorterminal.com/compare/beam-vs-cerebrium.md)
- [Beam vs Together GPU Clusters](https://www.anchorterminal.com/compare/beam-vs-together-gpu-clusters.md)
- [Cerebrium vs Cloud Run GPUs](https://www.anchorterminal.com/compare/cerebrium-vs-cloud-run-gpus.md)
- [Cerebrium vs CoreWeave](https://www.anchorterminal.com/compare/cerebrium-vs-coreweave.md)
- [Cerebrium vs Crusoe Cloud](https://www.anchorterminal.com/compare/cerebrium-vs-crusoe-cloud.md)
- [Cerebrium vs GPUsMarket](https://www.anchorterminal.com/compare/cerebrium-vs-gpusmarket.md)
- [Cerebrium vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/cerebrium-vs-hugging-face-inference-endpoints.md)
- [Cerebrium vs Hyperbolic](https://www.anchorterminal.com/compare/cerebrium-vs-hyperbolic.md)
- [Cerebrium vs Koyeb](https://www.anchorterminal.com/compare/cerebrium-vs-koyeb.md)
- [Cerebrium vs Lambda Cloud](https://www.anchorterminal.com/compare/cerebrium-vs-lambda.md)
- [Cerebrium vs Massed Compute](https://www.anchorterminal.com/compare/cerebrium-vs-massed-compute.md)
- [Cerebrium vs Modal](https://www.anchorterminal.com/compare/cerebrium-vs-modal.md)
- [Cerebrium vs Nebius AI Cloud](https://www.anchorterminal.com/compare/cerebrium-vs-nebius-ai-cloud.md)
- [Cerebrium vs Northflank](https://www.anchorterminal.com/compare/cerebrium-vs-northflank.md)
- [Cerebrium vs Replicate Deployments](https://www.anchorterminal.com/compare/cerebrium-vs-replicate-deploy.md)
- [Cerebrium vs Runpod](https://www.anchorterminal.com/compare/cerebrium-vs-runpod.md)
- [Cerebrium vs Thunder Compute](https://www.anchorterminal.com/compare/cerebrium-vs-thunder-compute.md)
- [Cerebrium vs Vast.ai](https://www.anchorterminal.com/compare/cerebrium-vs-vast-ai.md)
- [Cerebrium vs Verda](https://www.anchorterminal.com/compare/cerebrium-vs-verda.md)
- [Cloud Run GPUs vs Together GPU Clusters](https://www.anchorterminal.com/compare/cloud-run-gpus-vs-together-gpu-clusters.md)
- [CoreWeave vs Together GPU Clusters](https://www.anchorterminal.com/compare/coreweave-vs-together-gpu-clusters.md)
- [Crusoe Cloud vs Together GPU Clusters](https://www.anchorterminal.com/compare/crusoe-cloud-vs-together-gpu-clusters.md)
- [GPUsMarket vs Together GPU Clusters](https://www.anchorterminal.com/compare/gpusmarket-vs-together-gpu-clusters.md)
- [Hugging Face Inference Endpoints vs Together GPU Clusters](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-together-gpu-clusters.md)
- [Hyperbolic vs Together GPU Clusters](https://www.anchorterminal.com/compare/hyperbolic-vs-together-gpu-clusters.md)
- [Koyeb vs Together GPU Clusters](https://www.anchorterminal.com/compare/koyeb-vs-together-gpu-clusters.md)
- [Lambda Cloud vs Together GPU Clusters](https://www.anchorterminal.com/compare/lambda-vs-together-gpu-clusters.md)
- [Massed Compute vs Together GPU Clusters](https://www.anchorterminal.com/compare/massed-compute-vs-together-gpu-clusters.md)
- [Modal vs Together GPU Clusters](https://www.anchorterminal.com/compare/modal-vs-together-gpu-clusters.md)
- [Nebius AI Cloud vs Together GPU Clusters](https://www.anchorterminal.com/compare/nebius-ai-cloud-vs-together-gpu-clusters.md)
- [Northflank vs Together GPU Clusters](https://www.anchorterminal.com/compare/northflank-vs-together-gpu-clusters.md)
- [Replicate Deployments vs Together GPU Clusters](https://www.anchorterminal.com/compare/replicate-deploy-vs-together-gpu-clusters.md)
- [Runpod vs Together GPU Clusters](https://www.anchorterminal.com/compare/runpod-vs-together-gpu-clusters.md)
- [Thunder Compute vs Together GPU Clusters](https://www.anchorterminal.com/compare/thunder-compute-vs-together-gpu-clusters.md)
- [Together GPU Clusters vs Vast.ai](https://www.anchorterminal.com/compare/together-gpu-clusters-vs-vast-ai.md)
- [Together GPU Clusters vs Verda](https://www.anchorterminal.com/compare/together-gpu-clusters-vs-verda.md)

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