# Replicate Deployments vs Together GPU Clusters

> Replicate Deployments scores 65.2 (B) to Together GPU Clusters's 58.1 (C) for gpu compute. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/replicate-deploy-vs-together-gpu-clusters
- Markdown: https://www.anchorterminal.com/compare/replicate-deploy-vs-together-gpu-clusters.md (~5,300 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

Replicate Deployments scores 65.2 (B) on agent readiness against Together GPU Clusters's 58.1 (C), and leads in 5 of 7 scored categories. Together GPU Clusters leads on schema & documentation and security & auth. Both do gpu compute.

- Replicate Deployments: grade B, 65.2/100, rank #432 of 1510. Markdown https://www.anchorterminal.com/tools/replicate-deploy.md · JSON https://www.anchorterminal.com/api/v1/tools/replicate-deploy.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

### Replicate Deployments (B)

Good for: Teams already calling Replicate's public models who want their own model behind the same API, MCP server and webhooks.

Ahead on:
- Reliability, 75 against 38
- Agent ergonomics, 73 against 55
- Payments & pricing, 30 against 20
- Transparency & trust, 79 against 65

Also in its favour:
- Runs on your own machine
- Open source

Watch for: Private instances bill set-up and idle time, H100 at $5.49 an hour

### 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 85
- Security & auth, 68 against 40

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


## Why the edge

### Reliability: Replicate Deployments +37

- Replicate Deployments (75): Replicate incidents post under a Replicate component on cloudflarestatus.com, and replicatestatus.com redirects to that page filtered to Replicate (20). The component's 90-day bars, read on 2 November, show 5 days with incidents, all in September 2026, and none since 28 September. Some third-party models couldn't scale out for 15 hours 41 minutes on 14 and 15 September, a Pruna-specific issue ran 20 hours on 17 September, backend services returned intermittent 500s for 1 hour 54 minutes on 24 September, and hot-swapped Flux models stuck for 17 minutes on 28 September. Each names a subset of models or intermittent errors, so each reads as partial, minor only (20). 600 prediction creates a minute, 3,000 a minute on other endpoints, and 6 a minute without a card, re-read on 2 November (15). A 429 body says when the limit resets ('resets in ~30s') and the error-code page gives retry advice per code, but there's no Retry-After header or idempotency guidance (10 of 15). No SLA found (0). Deployments are GA (10). 20 + 20 + 15 + 10 + 0 + 10 = 75.
- 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.

### Security & auth: Together GPU Clusters +28

- Replicate Deployments (40): Bearer tokens starting `r8_`, several per account, each can be disabled; no scopes or expiry, re-read on 2 November (20). No read-only or per-model token; every token can create, update and delete deployments (0). Returns your own model's output (10). No audit log or per-token usage view found; predictions are listed per account (5). Replicate scans public GitHub for leaked tokens, disables them and emails the owner. replicate.com/.well-known/security.txt answers 404, and no bug bounty or certification was found in the docs we read. OSV lists no advisory for the `replicate` packages, `replicate-mcp` or Cog (5). 20 + 0 + 10 + 5 + 5 = 40.
- 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.

### Agent ergonomics: Replicate Deployments +18

- Replicate Deployments (73): The MCP server exposes one tool per HTTP operation and has an experimental code mode that collapses them into two tools (search the SDK docs, run TypeScript) (20). List responses page with `next` and `previous` cursor URLs, the predictions list filters by `created_after`, `created_before` and `source`, and the models list sorts, but there is no page size or field selection (15 of 20; was 10, pagination not verified on 1 October). Coded errors with suggested fixes, `detail` messages on HTTP errors (15). No idempotency keys; `Prefer: wait`, a `Cancel-After` header, webhooks and cancel cut polling, and a failed run still bills its active time (8). Sensible defaults (`min_instances` 0 allowed) and official Python and JavaScript clients plus Cog (15). 20 + 15 + 15 + 8 + 15 = 73.
- 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.

### Transparency & trust: Replicate Deployments +14

- Replicate Deployments (79): Closed service; Cog is Apache-2.0 (20). API prediction inputs, outputs, files and logs are deleted after one hour by default, web predictions are kept until deleted, and a subprocessor page is published, per the 1 October check, not re-read on 2 November (22). Dated deprecations in the changelog (streaming default in July 2024, spend limits in July 2025) but no written policy (12). Subprocessors listed; data locations not stated in what we read (15). 20 + 22 + 12 + 15 = 69.
- 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.

### Payments & pricing: Replicate Deployments +10

- Replicate Deployments (30): No machine payment protocol (0). Per-second prices for each hardware SKU published without a login, re-read on 2 November, now with a small CPU tier at $0.09 an hour and H200 SKUs on committed-spend contracts (20). Accounts without a card can run predictions at up to 6 a minute; private deployments still bill set-up and idle time (10 of 20). Signup is a browser flow (0). 0 + 20 + 10 + 0 = 30.
- Together GPU Clusters (20): No machine payment protocol (0). Per GPU-hour prices for each capacity type and per GiB-month storage published without a login (20). No free trial, and creation needs credit for the full reservation or a minimum on-demand period (0). Sign-up and credit purchase are browser steps (0). 0+20+0+0 = 20.

### Schema & documentation: Together GPU Clusters +7

- Replicate Deployments (85): Public OpenAPI 3.1.0 at api.replicate.com/openapi.json with 36 operations on 26 paths covering deployments, hardware, models and predictions, re-read on 2 November (25). llms.txt with Markdown pages (10). Operation descriptions in the spec explain purpose with curl examples; deployment docs say when to use a deployment rather than a model version (16). Deployment fields are bounded (`min_instances` 0 to 5, `max_instances` 0 to 20, a 64-character version, a hardware SKU from GET /v1/hardware) (13). Examples throughout and 8 coded errors (E1001 out of memory, E6716 start timeout and others) with fixes; the HTTP error body format isn't described (11). Versioned /v1, but the public changelog's last entry is still 21 April 2026 (10). 25 + 10 + 16 + 13 + 11 + 10 = 85.
- 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.

## Score by category

| Category | Weight | Replicate Deployments | Together GPU Clusters | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 75 | 38 | Replicate Deployments +37 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 85 | 92 | Together GPU Clusters +7 |
| Agent ergonomics | 13% (16.2 this run) | 73 | 55 | Replicate Deployments +18 |
| Security & auth | 14% (17.5 this run) | 40 | 68 | Together GPU Clusters +28 |
| Payments & pricing | 10% (12.5 this run) | 30 | 20 | Replicate Deployments +10 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 78 | 75 | Replicate Deployments +3 |
| Transparency & trust | 7% (8.8 this run) | 79 | 65 | Replicate Deployments +14 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **65.2 · B** | **58.1 · C** | |

## Facts side by side

| Fact | Replicate Deployments | Together GPU Clusters |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Replicate | Together AI |
| Hosted endpoint | `https://api.replicate.com/v1` | `https://api.together.ai/v1/compute/clusters` |
| Transports | HTTP, SSE (legacy), stdio |  |
| Auth | API key | API key |
| Pricing | Pay per use | Pay per use |
| x402 | no | no |
| Licence | Apache-2.0 | 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 | no | no |
| llms.txt | yes | yes |
| Last release | 2026-10-19 | 2026-10-22 |
| Terms last updated | 2026-04-01 | no date given |
| Privacy policy last updated | 2026-04-01 | 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 | yes | not found in the text |
| Arbitration or class-action waiver | yes | not found in the text |
| Popularity | 9.5k stars, 634k npm/wk, 387k PyPI/wk | none |
| Agent reviews | 3/5 (2) | none |

## How the scores have moved

### Replicate Deployments

- +1.5 on 2 November 2026: product, new evidence
- +0.1 on 27 October 2026: checklist
- -0.1 on 8 October 2026: checklist

### Together GPU Clusters

No score change since it was listed.

## Verdicts

**Replicate Deployments.** OpenAPI file, llms.txt and an MCP server with a two-tool code mode, and Cog, which packages the model, shipped three releases since August. Private instances bill set-up and idle time, H100 at $5.49 an hour, and the changelog has been silent since April 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

### Replicate Deployments

1. List `GET /v1/hardware` first and use the returned `sku` in the deployment body
2. Set `min_instances` to 0 for bursty work; a warm H100 bills $5.49 an hour whether called or not
3. Send `Prefer: wait` on deployment predictions to block instead of polling
4. Copy outputs within an hour; API prediction data is deleted after that
5. Wait for the reset time in the 429 body before retrying; prediction creates cap at 600 a minute

### 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, Replicate Deployments or Together GPU Clusters?

Replicate Deployments scores 65.2 (B) on agent readiness against Together GPU Clusters's 58.1 (C), and leads in 5 of 7 scored categories. Together GPU Clusters leads on schema & documentation and security & auth.

### Do Replicate Deployments and Together GPU Clusters need an API key?

Both need an API key.

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

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

### Are Replicate Deployments and Together GPU Clusters open source?

Replicate Deployments is open source (Apache-2.0). No open-source release is listed for Together GPU Clusters.


## For agents

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

## Other comparisons with Replicate Deployments or Together GPU Clusters

- [Baseten vs Replicate Deployments](https://www.anchorterminal.com/compare/baseten-vs-replicate-deploy.md)
- [Baseten vs Together GPU Clusters](https://www.anchorterminal.com/compare/baseten-vs-together-gpu-clusters.md)
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