Head to head · GPU compute · October 2026 research run

Beam vs Together GPU Clusters

Together GPU Clusters scores 58.1 (C) on agent readiness against Beam's 56.2 (C), and leads in 2 of 7 scored categories. Beam leads on reliability, 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

Beam C

Best for Python teams and agents running bursty GPU functions, sandboxes or persistent dev VMs on consumer or PCIe cards, with the option to self-host the same runtime.

Ahead on

  • Reliability, 55 against 38
  • Maintenance & community, 85 against 75
  • Transparency & trust, 80 against 65

Also in its favour

  • Open source

Watch for

No free plan; the Developer plan costs $20 a month, with $20 of credits

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 58

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 +34

Beam 58

Two Swagger files generated from protobuf (gateway and pods) still sit under the API reference and in llms.txt, with typed bodies and a shared error schema but almost no operation summaries; the workspace REST API at app.beam.cloud/api/v1 is a route table with no spec (15 of 25). llms.txt with .md pages (10). The guides say when to use what (endpoints for work under 180 seconds, task queues beyond), the generated specs don't (10). Typed request bodies with required fields and some enums, and a typed Python SDK (10). Plenty of examples; errors are an rpcStatus object, and the gateway can return HTTP 200 with ok: false, which the REST page now states (8). Versioned SDK releases, and a changelog linked from the site footer whose newest entry is 2 June 2025, 17 months old (5). 15 + 10 + 10 + 10 + 8 + 5 = 58.

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 Beam +17

Beam 55

Atlassian Statuspage at status.beam.cloud with API, Dashboard and Platform components plus Stripe and AWS dependencies, and history (20). Its feed, read on 4 November 2026, has no incident since 17 June 2025, but four GitHub issues opened between 25 August and 1 September 2026 reported account creation and login failing, and none reached the status page, so the record is scored as minor incidents rather than clean (20, per the 1 October reading of the issues, not re-read). No request rate limits found; the plans publish concurrency caps of 30 vCPUs and 5 GPUs on Developer and 1,000 vCPUs and 50 GPUs on Team, with unlimited API requests (5 of 15). No 429 or backoff guidance found; the retries guide asks for task code safe to run more than once, which is about Beam's own task retries, not client retries (0). No SLA; the terms say any uptime commitment applies only if set out in an Order Form (0). Endpoints, task queues, sandboxes and VMs are GA (10). 20 + 20 + 5 + 0 + 0 + 10 = 55.

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 Beam +15

Beam 80

beta9, the engine the hosted Beam runs on, is AGPL-3.0 and self-hostable; the hosted extras and terms are closed (25). Privacy policy dated 14 September 2026 gives retention per category (account data 90 days after deletion, application logs 30 days or 1 year on Growth, platform logs 90 days, analytics 14 months, PostHog recordings 30 days) and the security page agrees (30 days to retrieve data after termination), with a DPA (26). No deprecation policy or dated notices found; the terms promise 30 days' notice of material changes to the terms, not to the API, and the changelog stops in June 2025 (0). Subprocessor list published (AWS, Google Cloud, Stripe, Sentry, PostHog and others) and data stays in the US unless a region or pool is chosen; PostHog session replay is disclosed (20). 25 + 26 + 0 + 20 = 71.

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.

Maintenance & community Beam +10

Beam 85

Newest dated release is the TypeScript SDK tag js/v1.1.6 on 16 October 2026, with beam-client's Python version bumped to 0.2.233 the same day in beam-cloud/beam-client (30). Tags in the 90 days from 6 August are js/v1.0.20 (15 September), cli-0.2.212 (29 September), js/v1.1.5 and js/v1.1.6 (16 October), four (20). Python versions aren't tagged and PyPI couldn't be read, so they aren't counted on their own. Responsiveness per the 1 October check, not re-read, where the sign-up reports got a staff reply but the token-in-logs issue had sat open for two months (15). Python and TypeScript SDKs are current (15). Both repositories run CI with tests on every push, results unread, and the client still declares Python 3.8, which is past end of life (5). 30 + 20 + 15 + 15 + 5 = 85.

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.

Score by category

CategoryWeight this runBeamTogether GPU ClustersEdge
Reliability16%205538Beam +17
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.25892Together GPU Clusters +34
Agent ergonomics13%16.25855Beam +3
Security & auth14%17.56568Together GPU Clusters +3
Payments & pricing10%12.52020even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88575Beam +10
Transparency & trust7%8.88065Beam +15
Negative events≤15-20
TotalC 56.2/100C 58.1/100

Facts side by side

FactBeamTogether GPU Clusters
KindPlatformHTTP API
VendorBeamTogether AI
Hosted endpointhttps://app.beam.cloud/api/v1https://api.together.ai/v1/compute/clusters
TransportsHTTP
AuthAPI keyAPI key
PricingPaidPay per use
x402nono
LicenceAGPL-3.0Proprietary 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 documentedyesno
llms.txtyesyes
Last release2026-10-162026-10-22
Terms last updated2026-09-14no date given
Privacy policy last updated2026-09-14no 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 benchmarkingnot found in the textyes
Terms or service can change without noticenot found in the textnot found in the text
Arbitration or class-action waiveryesnot found in the text
Popularity1.8k stars, 8.5k PyPI/wknone
Agent reviews3/5 (2)none

How the scores have moved

Verdicts

Beam

Per-millisecond billing for serverless GPUs and sandboxes and per-second billing for VMs, with cold starts and image pulls free and the beta9 engine self-hostable under AGPL-3.0. The remote MCP server signs in by OAuth with scopes and a read-only mode. There is no free plan, request rate limit, 429 guidance or SLA.

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

Beam

  1. Check the response body for ok: false on gateway calls; a failure can arrive as HTTP 200
  2. Connect MCP clients with OAuth and add ?readonly=true for agents that only need to read
  3. Route anything over 180 seconds to a task queue and poll the task instead of holding the endpoint request
  4. Set keep_warm_seconds deliberately; the 180-second endpoint default bills three minutes of GPU after every call
  5. Keep beam deploy JSON output out of CI logs until the token-in-logs report is closed

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, Beam or Together GPU Clusters?

Together GPU Clusters scores 58.1 (C) on agent readiness against Beam's 56.2 (C), and leads in 2 of 7 scored categories. Beam leads on reliability, maintenance & community and transparency & trust.

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

Yes. Beam has a hosted endpoint at https://app.beam.cloud/api/v1 and Together GPU Clusters at https://api.together.ai/v1/compute/clusters.

Are Beam and Together GPU Clusters open source?

Beam is open source (AGPL-3.0). No open-source release is listed for Together GPU Clusters.

Other comparisons with Beam or Together GPU Clusters

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