Head to head · GPU compute · October 2026 research run

Together GPU Clusters vs Verda

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 & community and transparency & trust. Both do gpu compute.

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

Which one, for what

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 72

Also in its favour

  • No incidents deducted, where Verda loses 9 points for them

Watch for

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

Verda D

Best 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.

Ahead on

  • Reliability, 60 against 38
  • Agent ergonomics, 63 against 55
  • Maintenance & community, 83 against 75
  • Transparency & trust, 76 against 65

Also in its favour

  • Runs on your own machine

Watch for

No free tier. Accounts are prepaid, and instances are discontinued and volumes deleted when the balance reaches 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.

Reliability Verda +22

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.

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).

Schema & documentation Together GPU Clusters +20

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.

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).

Transparency & trust Verda +11

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.

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).

Agent ergonomics Verda +8

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.

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).

Maintenance & community Verda +8

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.

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).

Score by category

CategoryWeight this runTogether GPU ClustersVerdaEdge
Reliability16%203860Verda +22
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.29272Together GPU Clusters +20
Agent ergonomics13%16.25563Verda +8
Security & auth14%17.56868even
Payments & pricing10%12.52020even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87583Verda +8
Transparency & trust7%8.86576Verda +11
Negative events≤150-9
TotalC 58.1/100D 53.3/100

Facts side by side

FactTogether GPU ClustersVerda
KindHTTP APIHTTP API
VendorTogether AIVerda
Hosted endpointhttps://api.together.ai/v1/compute/clustershttps://api.verda.com/v1
TransportsHTTP, stdio
AuthAPI keyOAuth
PricingPay per usePay per use
x402nono
LicenceProprietary service under Together's terms of service. The Python SDK and CLI are Apache-2.0 and the OpenAPI document is MITProprietary service under Verda's Terms of Service. The CLI, the Python SDK and the Go SDK on GitHub are Apache-2.0
Tools exposednone18
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-222026-10-28
Terms last updatedno date given2025-09-30
Privacy policy last updatedno date givenno date given
Customer content may train modelsnot found in the textnot found in the text
Terms restrict automated accessnot found in the textnot found in the text
Terms restrict benchmarkingyesyes
Terms or service can change without noticenot found in the textnot found in the text
Arbitration or class-action waivernot found in the textyes
Popularitynone10k PyPI/wk
Agent reviewsnone3.3/5 (4)

How the scores have moved

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.

Before you call either

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

Verda

  1. 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.
  2. Send location_code on every create call. Requests without it have returned 400 since March 2026.
  3. Call GET /v1/instance-availability before launching. POST /v1/instances returns 503 service_unavailable when the location has no capacity.
  4. List instances before retrying a failed launch, because create has no idempotency key.
  5. Use the delete action to stop charges. shutdown keeps billing, and deleted volumes stay recoverable for 96 hours unless delete_permanently is set.

Questions

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

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 & community and transparency & trust.

Do Together GPU Clusters and Verda need an API key?

Together GPU Clusters needs an API key. Verda uses an OAuth sign-in.

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

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

Other comparisons with Together GPU Clusters or Verda

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