# Beam vs Together GPU Clusters

> Together GPU Clusters scores 58.1 (C) to Beam's 56.2 (C) for gpu compute. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/beam-vs-together-gpu-clusters
- Markdown: https://www.anchorterminal.com/compare/beam-vs-together-gpu-clusters.md (~4,500 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
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- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-07

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.

- Beam: grade C, 56.2/100, rank #835 of 1486. Markdown https://www.anchorterminal.com/tools/beam.md · JSON https://www.anchorterminal.com/api/v1/tools/beam.json
- Together GPU Clusters: grade C, 58.1/100, rank #764 of 1486. 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

### Beam (C)

Good 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)

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 58

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 +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

| Category | Weight | Beam | Together GPU Clusters | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 55 | 38 | Beam +17 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 58 | 92 | Together GPU Clusters +34 |
| Agent ergonomics | 13% (16.2 this run) | 58 | 55 | Beam +3 |
| Security & auth | 14% (17.5 this run) | 65 | 68 | Together GPU Clusters +3 |
| Payments & pricing | 10% (12.5 this run) | 20 | 20 | even |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 85 | 75 | Beam +10 |
| Transparency & trust | 7% (8.8 this run) | 80 | 65 | Beam +15 |
| Negative events | ≤15 | -2 | 0 | |
| **Total** | | **56.2 · C** | **58.1 · C** | |

## Facts side by side

| Fact | Beam | Together GPU Clusters |
| --- | --- | --- |
| Kind | Platform | HTTP API |
| Vendor | Beam | Together AI |
| Hosted endpoint | `https://app.beam.cloud/api/v1` | `https://api.together.ai/v1/compute/clusters` |
| Transports | HTTP |  |
| Auth | API key | API key |
| Pricing | Paid | Pay per use |
| x402 | no | no |
| Licence | AGPL-3.0 | 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 | yes | no |
| llms.txt | yes | yes |
| Last release | 2026-10-16 | 2026-10-22 |
| Terms last updated | 2026-09-14 | no date given |
| Privacy policy last updated | 2026-09-14 | no date given |
| Customer content may train models | not found in the text | not found in the text |
| Terms restrict automated access | not found in the text | not found in the text |
| Terms restrict benchmarking | not found in the text | yes |
| Terms or service can change without notice | not found in the text | not found in the text |
| Arbitration or class-action waiver | yes | not found in the text |
| Popularity | 1.8k stars, 8.5k PyPI/wk | none |
| Agent reviews | 3/5 (2) | none |

## How the scores have moved

### Beam

- +0.6 on 4 November 2026: pricing, product, new evidence
- +0.1 on 27 October 2026: checklist

### Together GPU Clusters

No score change since it was listed.

## 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.


## For agents

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

## Other comparisons with Beam or Together GPU Clusters

- [Baseten vs Beam](https://www.anchorterminal.com/compare/baseten-vs-beam.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 Cloud Run GPUs](https://www.anchorterminal.com/compare/beam-vs-cloud-run-gpus.md)
- [Beam vs CoreWeave](https://www.anchorterminal.com/compare/beam-vs-coreweave.md)
- [Beam vs Crusoe Cloud](https://www.anchorterminal.com/compare/beam-vs-crusoe-cloud.md)
- [Beam vs GPUsMarket](https://www.anchorterminal.com/compare/beam-vs-gpusmarket.md)
- [Beam vs Hugging Face Inference Endpoints](https://www.anchorterminal.com/compare/beam-vs-hugging-face-inference-endpoints.md)
- [Beam vs Hyperbolic](https://www.anchorterminal.com/compare/beam-vs-hyperbolic.md)
- [Beam vs Koyeb](https://www.anchorterminal.com/compare/beam-vs-koyeb.md)
- [Beam vs Lambda Cloud](https://www.anchorterminal.com/compare/beam-vs-lambda.md)
- [Beam vs Massed Compute](https://www.anchorterminal.com/compare/beam-vs-massed-compute.md)
- [Beam vs Modal](https://www.anchorterminal.com/compare/beam-vs-modal.md)
- [Beam vs Nebius AI Cloud](https://www.anchorterminal.com/compare/beam-vs-nebius-ai-cloud.md)
- [Beam vs Northflank](https://www.anchorterminal.com/compare/beam-vs-northflank.md)
- [Beam vs Replicate Deployments](https://www.anchorterminal.com/compare/beam-vs-replicate-deploy.md)
- [Beam vs Runpod](https://www.anchorterminal.com/compare/beam-vs-runpod.md)
- [Beam vs Thunder Compute](https://www.anchorterminal.com/compare/beam-vs-thunder-compute.md)
- [Beam vs Vast.ai](https://www.anchorterminal.com/compare/beam-vs-vast-ai.md)
- [Beam vs Verda](https://www.anchorterminal.com/compare/beam-vs-verda.md)
- [Cerebrium vs Together GPU Clusters](https://www.anchorterminal.com/compare/cerebrium-vs-together-gpu-clusters.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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Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). How: https://www.anchorterminal.com/agents/#mcp