# Replicate Deployments vs Together GPU Clusters (slim)

> 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.

- Full: https://www.anchorterminal.com/compare/replicate-deploy-vs-together-gpu-clusters.md (~5,300 tokens) · this version ~2,830 tokens · JSON https://www.anchorterminal.com/compare/replicate-deploy-vs-together-gpu-clusters.json · canonical https://www.anchorterminal.com/compare/replicate-deploy-vs-together-gpu-clusters
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-07
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

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: B 65.2, rank #432 of 1510 · https://www.anchorterminal.com/tools/replicate-deploy.min.md
- Together GPU Clusters: C 58.1, rank #768 of 1510 · https://www.anchorterminal.com/tools/together-gpu-clusters.min.md
- Replicate Deployments, 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 Runs on your own machine; Open source.
- Together GPU Clusters, 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.

| Category | Replicate Deployments | Together GPU Clusters |
| --- | --- | --- |
| Reliability (16%) | 75 | 38 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 85 | 92 |
| Agent ergonomics (13%) | 73 | 55 |
| Security & auth (14%) | 40 | 68 |
| Payments & pricing (10%) | 30 | 20 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 78 | 75 |
| Transparency & trust (7%) | 79 | 65 |

| Fact (where they differ) | Replicate Deployments | Together GPU Clusters |
| --- | --- | --- |
| Vendor | Replicate | Together AI |
| Hosted endpoint | `https://api.replicate.com/v1` | `https://api.together.ai/v1/compute/clusters` |
| Transports | HTTP, SSE (legacy), stdio |  |
| 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 |
| 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 |
| 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 |

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.)