# Runpod vs Together GPU Clusters

> Together GPU Clusters scores 58.1 (C) to Runpod's 55.6 (C) for gpu compute. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/runpod-vs-together-gpu-clusters
- Markdown: https://www.anchorterminal.com/compare/runpod-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)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- 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 Runpod's 55.6 (C), and leads in 3 of 7 scored categories. Runpod leads on reliability, agent ergonomics and maintenance & community. Both do gpu compute.

- Runpod: grade C, 55.6/100, rank #864 of 1510. Markdown https://www.anchorterminal.com/tools/runpod.md · JSON https://www.anchorterminal.com/api/v1/tools/runpod.json
- Together GPU Clusters: grade C, 58.1/100, rank #768 of 1510. 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

### Runpod (C)

Good for: Cost-sensitive inference and batch work that wants the widest GPU choice, from consumer cards to B300, with an MCP control plane.

Ahead on:
- Reliability, 57 against 38
- Agent ergonomics, 62 against 55
- Maintenance & community, 82 against 75

Also in its favour:
- Runs on your own machine

Watch for: Data-centre outages of 6 to 24 hours in each of July, August and September 2026, per the 1 October check

### 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 81

Also in its favour:
- No incidents deducted, where Runpod loses 6 points for them

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


## Why the edge

### Reliability: Runpod +19

- Runpod (57): Better Stack page at uptime.runpod.io with per-service and per-region history, per the 1 October check, not re-read on 4 November (Runpod's terms bar automated access to runpod.io and its subdomains) (20). Incident line kept at 0. The 1 October reading counted several majors, among them US-IL-1 without power for 6 hours 10 minutes on 14 and 15 August and serverless API errors for 1 hour 25 minutes on 6 September. The window since 1 October is unread, so the recorded award stands (0). The REST v2 OpenAPI file, in the copy Runpod keeps in its MCP repository (synced with production on 27 October), says limits are per user across every `/v2` route, with minute, hour and day windows, and gives `"minute";q=180;w=60, "hour";q=3600;w=3600, "day";q=43200;w=86400` as the policy header (15). The same file documents 429 with `Retry-After` and `RateLimit` headers, and the Python SDK's error guide (2.1.0, 3 November) honours `Retry-After`, backs off with jitter and does not retry other errors because a failed response can follow a successful mutation. Safe-retry guidance with no idempotency keys (12). No SLA found (0). Serverless and REST v2 are GA; batch jobs are beta (10). 20 + 0 + 15 + 12 + 0 + 10 = 57.
- 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.

### Schema & documentation: Together GPU Clusters +11

- Runpod (81): OpenAPI for REST v2 at api.runpod.io/v2/openapi.json, with v1 and GraphQL schemas also published (25). llms.txt with .md pages (10). Guides explain queue-based against load-balanced endpoints and sync against async calls, with result retention for each (14). Job statuses are a fixed set (`IN_QUEUE`, `IN_PROGRESS`, `COMPLETED`, `FAILED`) and payload limits are stated (20 MB sync, 10 MB async, 1 MB per stream chunk) (10). Examples throughout; no error responses documented for the serverless operations (7). Dated release notes and a versioned API (15).
- 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.

### Agent ergonomics: Runpod +7

- Runpod (62): Results can be streamed in chunks of up to 1 MB and polled by job ID, and `include` sizes some REST v2 responses (12). REST v2 list calls take an opaque `cursor` with `limit` (1 to 1,000, 100 for builds, 200 for audit logs) and filters such as actor, action and time on audit logs, per the OpenAPI file in Runpod's MCP repository (20). No error codes or messages documented for serverless operations, per 1 October (5). `/retry`, `/cancel` and `/purge-queue` give safe recovery for jobs, and the MCP server marks destructive tools. No idempotency keys (10). FlashBoot on by default, Python and JavaScript SDKs, the Flash SDK and an official MCP server (15). 12 + 20 + 5 + 10 + 15 = 62.
- 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.

### Maintenance & community: Runpod +7

- Runpod (82): Latest release `runpod` 2.1.0 on 3 November 2026, and `@runpod/mcp-server` 4.9.1 on 2 November (30). In the window from 6 August, runpod-python tagged v1.12.0, v2.0.0 and v2.1.0, runpod-mcp thirteen releases from v3.3.0 (17 August) to 4.9.1, and flash v1.20.0 to v1.21.1, besides release candidates (20). Closed service with dated release notes and support; GitHub issue response times weren't readable (github.com refuses us) (12 of 25). Python and JavaScript SDKs, the Flash SDK and the MCP server are official; the standalone `runpod-flash` package was deprecated in October in favour of `runpod` (15). Package health not checked (5). 30 + 20 + 12 + 15 + 5 = 82.
- 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 | Runpod | Together GPU Clusters | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 57 | 38 | Runpod +19 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 81 | 92 | Together GPU Clusters +11 |
| Agent ergonomics | 13% (16.2 this run) | 62 | 55 | Runpod +7 |
| Security & auth | 14% (17.5 this run) | 67 | 68 | Together GPU Clusters +1 |
| 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) | 82 | 75 | Runpod +7 |
| Transparency & trust | 7% (8.8 this run) | 64 | 65 | Together GPU Clusters +1 |
| Negative events | ≤15 | -6 | 0 | |
| **Total** | | **55.6 · C** | **58.1 · C** | |

## Facts side by side

| Fact | Runpod | Together GPU Clusters |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Runpod | Together AI |
| Hosted endpoint | `https://api.runpod.ai/v2` | `https://api.together.ai/v1/compute/clusters` |
| Transports | HTTP, Streamable HTTP, stdio |  |
| Auth | OAuth or key | API key |
| Pricing | Pay per use | Pay per use |
| x402 | no | no |
| Licence | MIT | 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 | no | no |
| llms.txt | yes | yes |
| Last release | 2026-11-03 | 2026-10-22 |
| Terms last updated | 2026-03-24 | no date given |
| Privacy policy last updated | 2025-08-07 | no date given |
| Customer content may train models | not found in the text | not found in the text |
| Terms restrict automated access | yes | not found in the text |
| Terms restrict benchmarking | yes | 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 | 314 stars, 22k npm/wk | none |
| Agent reviews | 3/5 (2) | none |

## How the scores have moved

### Runpod

- +2.0 on 4 November 2026 (D to C): product, new evidence, negative event
- +0.1 on 27 October 2026: checklist
- -0.2 on 8 October 2026: checklist

### Together GPU Clusters

No score change since it was listed.

## Verdicts

**Runpod.** Per-second billing across more than a dozen serverless GPU classes, with a REST v2 contract that documents rate limits, 429 handling and cursor pagination. Data-centre outages ran 6 to 24 hours in July, August and September 2026, and two minor releases in late October and early November changed CLI and MCP behaviour without notice.

**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

### Runpod

1. Create a Restricted or Read Only key per endpoint for the agent, not an All key
2. Use REST v2 at api.runpod.io/v2 with a Bearer header; avoid GraphQL, which puts the key in the URL, and read quotas from the `RateLimit-Policy` header
3. Fetch `/run` results within 30 minutes and `/runsync` results within 1 minute, or they're gone
4. Call `/retry` on a failed job ID rather than submitting a duplicate job
5. Check `/health` before relying on an endpoint idle for a week, since max workers drop to 0
6. Set `RUNPOD_API_KEY` or pass `--api-key` when running `rp login` without a terminal; since `runpod` 2.1.0 it fails fast otherwise

### 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, Runpod or Together GPU Clusters?

Together GPU Clusters scores 58.1 (C) on agent readiness against Runpod's 55.6 (C), and leads in 3 of 7 scored categories. Runpod leads on reliability, agent ergonomics and maintenance & community.

### Do Runpod and Together GPU Clusters need an API key?

Runpod takes an API key or an OAuth sign-in. Together GPU Clusters needs an API key.

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

Yes. Runpod has a hosted endpoint at https://api.runpod.ai/v2 and Together GPU Clusters at https://api.together.ai/v1/compute/clusters.


## For agents

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

## Other comparisons with Runpod or Together GPU Clusters

- [Baseten vs Runpod](https://www.anchorterminal.com/compare/baseten-vs-runpod.md)
- [Baseten vs Together GPU Clusters](https://www.anchorterminal.com/compare/baseten-vs-together-gpu-clusters.md)
- [Beam vs Runpod](https://www.anchorterminal.com/compare/beam-vs-runpod.md)
- [Beam vs Together GPU Clusters](https://www.anchorterminal.com/compare/beam-vs-together-gpu-clusters.md)
- [Cerebrium vs Runpod](https://www.anchorterminal.com/compare/cerebrium-vs-runpod.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 Runpod](https://www.anchorterminal.com/compare/coreweave-vs-runpod.md)
- [CoreWeave vs Together GPU Clusters](https://www.anchorterminal.com/compare/coreweave-vs-together-gpu-clusters.md)
- [Crusoe Cloud vs Runpod](https://www.anchorterminal.com/compare/crusoe-cloud-vs-runpod.md)
- [Crusoe Cloud vs Together GPU Clusters](https://www.anchorterminal.com/compare/crusoe-cloud-vs-together-gpu-clusters.md)
- [GPUsMarket vs Runpod](https://www.anchorterminal.com/compare/gpusmarket-vs-runpod.md)
- [GPUsMarket vs Together GPU Clusters](https://www.anchorterminal.com/compare/gpusmarket-vs-together-gpu-clusters.md)
- [Hugging Face Inference Endpoints vs Runpod](https://www.anchorterminal.com/compare/hugging-face-inference-endpoints-vs-runpod.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 Runpod](https://www.anchorterminal.com/compare/hyperbolic-vs-runpod.md)
- [Hyperbolic vs Together GPU Clusters](https://www.anchorterminal.com/compare/hyperbolic-vs-together-gpu-clusters.md)
- [Koyeb vs Runpod](https://www.anchorterminal.com/compare/koyeb-vs-runpod.md)
- [Koyeb vs Together GPU Clusters](https://www.anchorterminal.com/compare/koyeb-vs-together-gpu-clusters.md)
- [Lambda Cloud vs Runpod](https://www.anchorterminal.com/compare/lambda-vs-runpod.md)
- [Lambda Cloud vs Together GPU Clusters](https://www.anchorterminal.com/compare/lambda-vs-together-gpu-clusters.md)
- [Massed Compute vs Runpod](https://www.anchorterminal.com/compare/massed-compute-vs-runpod.md)
- [Massed Compute vs Together GPU Clusters](https://www.anchorterminal.com/compare/massed-compute-vs-together-gpu-clusters.md)
- [Modal vs Runpod](https://www.anchorterminal.com/compare/modal-vs-runpod.md)
- [Modal vs Together GPU Clusters](https://www.anchorterminal.com/compare/modal-vs-together-gpu-clusters.md)
- [Nebius AI Cloud vs Runpod](https://www.anchorterminal.com/compare/nebius-ai-cloud-vs-runpod.md)
- [Nebius AI Cloud vs Together GPU Clusters](https://www.anchorterminal.com/compare/nebius-ai-cloud-vs-together-gpu-clusters.md)
- [Northflank vs Runpod](https://www.anchorterminal.com/compare/northflank-vs-runpod.md)
- [Northflank vs Together GPU Clusters](https://www.anchorterminal.com/compare/northflank-vs-together-gpu-clusters.md)
- [Replicate Deployments vs Runpod](https://www.anchorterminal.com/compare/replicate-deploy-vs-runpod.md)
- [Replicate Deployments vs Together GPU Clusters](https://www.anchorterminal.com/compare/replicate-deploy-vs-together-gpu-clusters.md)
- [Runpod vs Thunder Compute](https://www.anchorterminal.com/compare/runpod-vs-thunder-compute.md)
- [Runpod vs Vast.ai](https://www.anchorterminal.com/compare/runpod-vs-vast-ai.md)
- [Runpod vs Verda](https://www.anchorterminal.com/compare/runpod-vs-verda.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)
- [Cloud Run GPUs vs Runpod](https://www.anchorterminal.com/compare/cloud-run-gpus-vs-runpod.md)

---

Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). How: https://www.anchorterminal.com/agents/#mcp