Head to head · GPU compute · October 2026 research run

Koyeb vs Together GPU Clusters

Together GPU Clusters scores 58.1 (C) on agent readiness against Koyeb's 46.6 (D), and leads in 5 of 7 scored categories. Koyeb leads on reliability. Both do gpu compute.

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

Which one, for what

Koyeb D

Best for Teams that want low-cost H100, H200 or B200 containers with scale to zero and an SLA, deployed from Git or an image.

Ahead on

  • Reliability, 50 against 38

Watch for

Public changelog silent since 27 February 2026, so API changes surface only through CLI and SDK releases

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 31
  • Security & auth, 68 against 50

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 +61

Koyeb 31

No downloadable OpenAPI file. The API reference at koyeb.com/docs/reference/api renders only by script, and the generated docs in the Go and Python client repositories aren't a published contract (0, was 10). No llms.txt (www.koyeb.com/llms.txt and /docs/llms.txt both 404) and no Markdown twins (0). Guides on scale to zero and autoscaling say when to use each setting (10, held). Typed parameters with required bodies in the Go client's docs, but service types and statuses are free strings with no listed values (8, held). CLI examples throughout; no documented error responses found (5, held). /v1 paths, but the public changelog stopped on 27 February 2026 (8, held). 0 + 0 + 10 + 8 + 5 + 8 = 31.

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.

Security & auth Together GPU Clusters +18

Koyeb 50

Personal access tokens and organisation tokens sent as Bearer; no scopes found (20). RBAC only on Enterprise; no read-only token (5). Runs your own containers and returns their output (10). Audit logs only on Enterprise (10). ISO 27001 and SOC 2 listed on the pricing page for Enterprise; www.koyeb.com/.well-known/security.txt is 404 and no disclosure policy, SECURITY.md or bug bounty found, so a bare certification claim (5). 20 + 5 + 10 + 10 + 5 = 50.

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.

Reliability Koyeb +12

Koyeb 50

Graded on the hosted lines for its platform API. Instatus page at status.koyeb.com with components (API, Control Panel, Build / Provisioning and one per region) and history back to 2022 in its feed (20). Since 7 August the feed holds nine incidents and one maintenance. The eight in September each name one region, one GPU type or some customers, or ran 6 to 52 minutes (8, 11, 15, 21, 22 and 23 September and two on 29 September). On 16 October Koyeb posted a separate incident, "The ongoing maintenance is causing API to fail with 500", on the API, Control Panel and Build components for 24 minutes, inside a maintenance window announced the day before for 07:00 to 08:00 UTC with "max 10m unavailability". The status page labels it an incident and the outage ran past the unavailability announced, so it counts as an incident, and the API failing with 500 is errors across the board, one major outage (10). No API rate limits found in the docs we could read (0). No 429 or backoff guidance found (0). The Scale plan lists a 99.9 per cent uptime SLA and Enterprise 99.99, with an SLA document at /docs/legal/sla setting service credits (10). Services and GPUs are generally available; light sleep is a preview (10). 20 + 10 + 0 + 0 + 10 + 10 = 50.

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.

Score by category

CategoryWeight this runKoyebTogether GPU ClustersEdge
Reliability16%205038Koyeb +12
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.23192Together GPU Clusters +61
Agent ergonomics13%16.25155Together GPU Clusters +4
Security & auth14%17.55068Together GPU Clusters +18
Payments & pricing10%12.52020even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87375Together GPU Clusters +2
Transparency & trust7%8.86465Together GPU Clusters +1
Negative events≤1500
TotalD 46.6/100C 58.1/100

Facts side by side

FactKoyebTogether GPU Clusters
KindPlatformHTTP API
VendorKoyebTogether AI
Hosted endpointhttps://app.koyeb.com/v1https://api.together.ai/v1/compute/clusters
TransportsHTTP
AuthTokenAPI key
PricingFreemiumPay per use
x402nono
LicenceApache-2.0Proprietary 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.txtnoyes
Last release2026-10-202026-10-22
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
Popularity72 starsnone
Agent reviews3.5/5 (2)none

How the scores have moved

Verdicts

Koyeb

Koyeb publishes per-second GPU prices without a login, from $0.50 an hour for an RTX 4000 SFF Ada to $2.50 for an H100, with an SLA document from the Scale plan. It has no downloadable OpenAPI file, documented rate limits or error codes, and no free compute plan, and its public changelog has been silent since 27 February 2026.

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

Koyeb

  1. Pass dry_run on service create or update to validate the definition before anything deploys
  2. Page service lists with limit and offset and filter by statuses instead of fetching everything
  3. Expect the first request after deep sleep to take 1 to 5 seconds and retry once with a timeout
  4. Set --min-scale 0 on GPU services so idle instances stop billing
  5. Read the CLI's CHANGES.md and the Python SDK tags for API changes, since the web changelog stopped in February 2026

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, Koyeb or Together GPU Clusters?

Together GPU Clusters scores 58.1 (C) on agent readiness against Koyeb's 46.6 (D), and leads in 5 of 7 scored categories. Koyeb leads on reliability.

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

Yes. Koyeb has a hosted endpoint at https://app.koyeb.com/v1 and Together GPU Clusters at https://api.together.ai/v1/compute/clusters.

Other comparisons with Koyeb or Together GPU Clusters

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