Head to head · GPU compute · October 2026 research run

Cerebrium vs 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. Both do gpu compute.

Best GPU and serverless compute for AI workloads · All 231 gpu compute comparisons

Which one, for what

Cerebrium D

Best 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

Best 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

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

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

CategoryWeight this runCerebriumTogether GPU ClustersEdge
Reliability16%204838Cerebrium +10
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27092Together GPU Clusters +22
Agent ergonomics13%16.24955Together GPU Clusters +6
Security & auth14%17.56068Together GPU Clusters +8
Payments & pricing10%12.53020Cerebrium +10
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.86575Together GPU Clusters +10
Transparency & trust7%8.86465Together GPU Clusters +1
Negative events≤15-20
TotalD 52.5/100C 58.1/100

Facts side by side

FactCerebriumTogether GPU Clusters
KindPlatformHTTP API
VendorCerebrium Inc.Together AI
Hosted endpointhttps://rest.cerebrium.aihttps://api.together.ai/v1/compute/clusters
TransportsHTTP
AuthAPI keyAPI key
PricingFreemiumPay per use
x402nono
LicenceProprietary service under Cerebrium's terms of service. The CLI is MITProprietary 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 documentednono
llms.txtyesyes
Last release2026-09-162026-10-22
Terms last updatedno date givenno date given
Privacy policy last updatedno date givenno date given
Customer content may train modelsnot found in the textnot found in the text
Terms restrict automated accessyesnot found in the text
Terms restrict benchmarkingnot found in the textyes
Terms or service can change without noticeyesnot found in the text
Arbitration or class-action waivernot found in the textnot found in the text

How the scores have moved

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.

Other comparisons with Cerebrium or Together GPU Clusters

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