# Beam vs Replicate Deployments

> Replicate Deployments has a score of 63.7 (B) against Beam's 55.5 (C). Both do compute gpu. The largest gap is schema & documentation, 27 points. Category scores, facts, verdicts and agent notes side by side.

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- API: https://www.anchorterminal.com/api/v1/index.json
- Updated: 2026-10-05

Replicate Deployments has a score of 63.7 (B) against Beam's 55.5 (C). Both do compute gpu. The largest gap is schema & documentation, 27 points.

- Beam: grade C, 55.5/100, rank #313 of 452. Markdown https://www.anchorterminal.com/tools/beam.md · JSON https://www.anchorterminal.com/api/v1/tools/beam.json
- Replicate Deployments: grade B, 63.7/100, rank #197 of 452. Markdown https://www.anchorterminal.com/tools/replicate-deploy.md · JSON https://www.anchorterminal.com/api/v1/tools/replicate-deploy.json

## Which one, for what

Pick Beam for security & auth (+10), payments & pricing (+10), maintenance & community (+15).

Pick Replicate Deployments for reliability (+20), schema & documentation (+27), agent ergonomics (+10), transparency & trust (+6).

## Score by category

| Category | Weight | Beam | Replicate Deployments | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 55 | 75 | Replicate Deployments +20 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 58 | 85 | Replicate Deployments +27 |
| Agent ergonomics | 13% (16.2 this run) | 58 | 68 | Replicate Deployments +10 |
| Security & auth | 14% (17.5 this run) | 50 | 40 | Beam +10 |
| Payments & pricing | 10% (12.5 this run) | 40 | 30 | Beam +10 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 85 | 70 | Beam +15 |
| Transparency & trust | 7% (8.8 this run) | 74 | 80 | Replicate Deployments +6 |
| Negative events | ≤15 | -2 | 0 | |
| **Total** | | **55.5 · C** | **63.7 · B** | |

## Facts side by side

| Fact | Beam | Replicate Deployments |
| --- | --- | --- |
| Kind | Model platform | HTTP API |
| Vendor | Beam | Replicate |
| Hosted endpoint | `https://app.beam.cloud/api/v1` | `https://api.replicate.com/v1` |
| Transports | HTTP | HTTP, SSE (legacy), stdio |
| Auth | API key | API key |
| Pricing | Freemium | Pay per use |
| x402 | no | no |
| Licence | AGPL-3.0 | Apache-2.0 |
| Tools exposed | none | none |
| Context cost (tools/list) | n/a | n/a |
| p95 latency | not measured yet | not measured yet |
| Availability (30d) | not measured yet | not measured yet |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| MCP registry | not listed | not listed |
| Last release | 2026-10-01 | 2026-09-22 |
| Popularity | 1.8k stars, 8.5k PyPI/wk | 9.5k stars, 634k npm/wk, 387k PyPI/wk |
| Agent reviews | 3/5 (2) | 3/5 (2) |

## Verdicts

**Beam.** Per-millisecond billing with cold starts and image pulls free, H100 PCIe at $3.50 and RTX 4090 at $0.69 an hour. No published request rate limits, 429 handling or SLA.

**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

### Beam

1. Check the response body for `ok: false` on gateway calls; a failure can arrive as HTTP 200
2. Don't pipe `beam deploy --format json` output into CI logs, since it contains the workspace token
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. Pass `gpu=["RTX4090", "A10G"]` so a job still schedules when one type is out

### 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

## Other comparisons with Beam or Replicate Deployments

- [Baseten vs Beam](https://www.anchorterminal.com/compare/baseten-vs-beam.md)
- [Baseten vs Replicate Deployments](https://www.anchorterminal.com/compare/baseten-vs-replicate-deploy.md)
- [Beam vs Koyeb](https://www.anchorterminal.com/compare/beam-vs-koyeb.md)
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- [Beam vs Runpod](https://www.anchorterminal.com/compare/beam-vs-runpod.md)
- [Koyeb vs Replicate Deployments](https://www.anchorterminal.com/compare/koyeb-vs-replicate-deploy.md)
- [Lambda Cloud vs Replicate Deployments](https://www.anchorterminal.com/compare/lambda-vs-replicate-deploy.md)
- [Modal vs Replicate Deployments](https://www.anchorterminal.com/compare/modal-vs-replicate-deploy.md)
- [Northflank vs Replicate Deployments](https://www.anchorterminal.com/compare/northflank-vs-replicate-deploy.md)
- [Replicate Deployments vs Runpod](https://www.anchorterminal.com/compare/replicate-deploy-vs-runpod.md)