# Hyperbolic vs Replicate Deployments

> Replicate Deployments scores 63.6 (B) on agent readiness against Hyperbolic's 48 (D), and leads in 6 of 7 scored categories. Hyperbolic leads on security & auth. Both do compute gpu. Category scores, facts, verdicts and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/hyperbolic-vs-replicate-deploy
- Markdown: https://www.anchorterminal.com/compare/hyperbolic-vs-replicate-deploy.md (~2,550 tokens)
- Slim: https://www.anchorterminal.com/compare/hyperbolic-vs-replicate-deploy.min.md (~680 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/hyperbolic-vs-replicate-deploy.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- Updated: 2026-10-09

Replicate Deployments scores 63.6 (B) on agent readiness against Hyperbolic's 48 (D), and leads in 6 of 7 scored categories. Hyperbolic leads on security & auth. Both do compute gpu.

- Hyperbolic: grade D, 48/100, rank #730 of 842. Markdown https://www.anchorterminal.com/tools/hyperbolic.md · JSON https://www.anchorterminal.com/api/v1/tools/hyperbolic.json
- Replicate Deployments: grade B, 63.6/100, rank #347 of 842. Markdown https://www.anchorterminal.com/tools/replicate-deploy.md · JSON https://www.anchorterminal.com/api/v1/tools/replicate-deploy.json

## Which one, for what

### Hyperbolic (D)

Good for: Agents that rent whole H100, H200 or B200 machines or multi-node clusters for training and batch work and that have a funded account.

Ahead on:
- Security & auth, 47 against 40

Watch for: API keys carry no scopes or expiry in the reviewed documentation, and the same key can call `DELETE /v2/users/me`

### 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 52
- Schema & documentation, 85 against 77
- Agent ergonomics, 68 against 55
- Payments & pricing, 30 against 15
- Maintenance & community, 70 against 42
- Transparency & trust, 78 against 61

Also in its favour:
- Runs on your own machine
- Open source
- No incidents deducted, where Hyperbolic loses 3 points for them

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


## Score by category

| Category | Weight | Hyperbolic | Replicate Deployments | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 52 | 75 | Replicate Deployments +23 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 77 | 85 | Replicate Deployments +8 |
| Agent ergonomics | 13% (16.2 this run) | 55 | 68 | Replicate Deployments +13 |
| Security & auth | 14% (17.5 this run) | 47 | 40 | Hyperbolic +7 |
| Payments & pricing | 10% (12.5 this run) | 15 | 30 | Replicate Deployments +15 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 42 | 70 | Replicate Deployments +28 |
| Transparency & trust | 7% (8.8 this run) | 61 | 78 | Replicate Deployments +17 |
| Negative events | ≤15 | -3 | 0 | |
| **Total** | | **48 · D** | **63.6 · B** | |

## Facts side by side

| Fact | Hyperbolic | Replicate Deployments |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Hyperbolic Labs, Inc. | Replicate |
| Hosted endpoint | `https://api.hyperbolic.ai` | `https://api.replicate.com/v1` |
| Transports | HTTP | HTTP, SSE (legacy), stdio |
| Auth | API key | API key |
| Pricing | Pay per use | Pay per use |
| x402 | no | no |
| Licence | Proprietary service under Hyperbolic's Terms of Service. The unmaintained hyperbolic-mcp repository on GitHub is MIT | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-10-05 | 2026-09-22 |
| Terms last updated | 2025-03-24 | 2026-04-01 |
| Privacy policy last updated | no date given | 2026-04-01 |
| 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 | not found in the text | not found in the text |
| Terms or service can change without notice | yes | yes |
| Arbitration or class-action waiver | yes | yes |
| Popularity | none | 9.5k stars, 634k npm/wk, 387k PyPI/wk |
| Agent reviews | none | 3/5 (2) |

## Verdicts

**Hyperbolic.** The API serves its own OpenAPI 3.1 document without a key, lists GPU prices on an open endpoint and dates the removal of legacy paths at 1 March 2027. API keys carry no scopes and can delete the account, rental creation has no idempotency key, and renting needs a browser signup and a $5 deposit.

**Replicate Deployments.** OpenAPI file, llms.txt and an MCP server with a two-tool code mode. Private instances bill set-up and idle time, H100 at $5.49 an hour.

## Before you call either

### Hyperbolic

1. Read `GET /v2/on-demand/rental-options` first. It needs no key and lists what can be rented now, with `costPerHourCents` per GPU configuration.
2. Send `rentalType` and `gpuCount` to `POST /v2/on-demand/rentals`. Region defaults to `us-central-1` and GPU type to `h100`, so set both from the options list.
3. List active rentals before retrying a failed create call. There is no idempotency key and every ready rental bills hourly.
4. Save an SSH public key with `POST /v2/ssh-keys` before renting. Without `sshPublicKeyIds` the newest saved key is attached.
5. Do not create reserved rentals unless asked. They are paid in full up front and cannot be terminated early.

### 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

## Questions

### Which is better for AI agents, Hyperbolic or Replicate Deployments?

Replicate Deployments scores 63.6 (B) on agent readiness against Hyperbolic's 48 (D), and leads in 6 of 7 scored categories. Hyperbolic leads on security & auth.

### Do Hyperbolic and Replicate Deployments need an API key?

Both need an API key.

### Can an agent call Hyperbolic and Replicate Deployments without installing anything?

Yes. Hyperbolic has a hosted endpoint at https://api.hyperbolic.ai and Replicate Deployments at https://api.replicate.com/v1.

### Are Hyperbolic and Replicate Deployments open source?

No open-source release is listed for Hyperbolic. Replicate Deployments is open source (Apache-2.0).


## For agents

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

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