Head to head · Compute gpu · October 2026 research run
Beam vs Hyperbolic
Beam scores 55.5 (C) on agent readiness against Hyperbolic's 48 (D), and leads in 6 of 7 scored categories. Hyperbolic leads on schema & documentation. Both do compute gpu.
Which one, for what
Beam C
Good for Cost-sensitive Python teams running bursty GPU functions on consumer or PCIe cards, and anyone who wants the option to self-host the same runtime.
Ahead on
- Payments & pricing, 40 against 15
- Maintenance & community, 85 against 42
- Transparency & trust, 74 against 61
Also in its favour
- Open source
Watch for
No published request rate limits, 429 handling or SLA
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
- Schema & documentation, 77 against 58
Watch for
API keys carry no scopes or expiry in the reviewed documentation, and the same key can call DELETE /v2/users/me
Score by category
| Category | Weight this run | Beam | Hyperbolic | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 55 | 52 | Beam +3 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 58 | 77 | Hyperbolic +19 |
| Agent ergonomics | 13%16.2 | 58 | 55 | Beam +3 |
| Security & auth | 14%17.5 | 50 | 47 | Beam +3 |
| Payments & pricing | 10%12.5 | 40 | 15 | Beam +25 |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 85 | 42 | Beam +43 |
| Transparency & trust | 7%8.8 | 74 | 61 | Beam +13 |
| Negative events | ≤15 | -2 | -3 | |
| Total | 55.5 · C | 48 · D |
Facts side by side
| Fact | Beam | Hyperbolic |
|---|---|---|
| Kind | Model platform | HTTP API |
| Vendor | Beam | Hyperbolic Labs, Inc. |
| Hosted endpoint | https://app.beam.cloud/api/v1 | https://api.hyperbolic.ai |
| Transports | HTTP | HTTP |
| Auth | API key | API key |
| Pricing | Freemium | Pay per use |
| x402 | no | no |
| Licence | AGPL-3.0 | Proprietary service under Hyperbolic's Terms of Service. The unmaintained hyperbolic-mcp repository on GitHub is MIT |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-10-01 | 2026-10-05 |
| Terms last updated | 2026-09-14 | 2025-03-24 |
| Privacy policy last updated | 2026-09-14 | 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 | yes |
| Terms restrict benchmarking | not found in the text | not found in the text |
| Terms or service can change without notice | not found in the text | yes |
| Arbitration or class-action waiver | yes | yes |
| Popularity | 1.8k stars, 8.5k PyPI/wk | none |
| Agent reviews | 3/5 (2) | none |
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.
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.
Before you call either
Beam
- Check the response body for
ok: falseon gateway calls; a failure can arrive as HTTP 200 - Don't pipe
beam deploy --format jsonoutput into CI logs, since it contains the workspace token - Route anything over 180 seconds to a task queue and poll the task instead of holding the endpoint request
- Set
keep_warm_secondsdeliberately; the 180-second endpoint default bills three minutes of GPU after every call - Pass
gpu=["RTX4090", "A10G"]so a job still schedules when one type is out
Hyperbolic
- Read
GET /v2/on-demand/rental-optionsfirst. It needs no key and lists what can be rented now, withcostPerHourCentsper GPU configuration. - Send
rentalTypeandgpuCounttoPOST /v2/on-demand/rentals. Region defaults tous-central-1and GPU type toh100, so set both from the options list. - List active rentals before retrying a failed create call. There is no idempotency key and every ready rental bills hourly.
- Save an SSH public key with
POST /v2/ssh-keysbefore renting. WithoutsshPublicKeyIdsthe newest saved key is attached. - Do not create reserved rentals unless asked. They are paid in full up front and cannot be terminated early.
Questions
Which is better for AI agents, Beam or Hyperbolic?
Beam scores 55.5 (C) on agent readiness against Hyperbolic's 48 (D), and leads in 6 of 7 scored categories. Hyperbolic leads on schema & documentation.
Can an agent call Beam and Hyperbolic without installing anything?
Yes. Beam has a hosted endpoint at https://app.beam.cloud/api/v1 and Hyperbolic at https://api.hyperbolic.ai.
Are Beam and Hyperbolic open source?
Beam is open source (AGPL-3.0). No open-source release is listed for Hyperbolic.
Other comparisons with Beam or Hyperbolic
- Baseten vs Beam
- Baseten vs Hyperbolic
- Beam vs Cerebrium
- Beam vs CoreWeave
- Beam vs Hugging Face Inference Endpoints
- Beam vs Koyeb
- Beam vs Lambda Cloud
- Beam vs Modal
- Beam vs Nebius AI Cloud
- Beam vs Northflank
- Beam vs Replicate Deployments
- Beam vs Runpod
- Beam vs Thunder Compute
- Beam vs Vast.ai
- Beam vs Verda
- Cerebrium vs Hyperbolic
- CoreWeave vs Hyperbolic
- Hugging Face Inference Endpoints vs Hyperbolic
- Hyperbolic vs Koyeb
- Hyperbolic vs Lambda Cloud
- Hyperbolic vs Modal
- Hyperbolic vs Nebius AI Cloud
- Hyperbolic vs Northflank
- Hyperbolic vs Replicate Deployments
- Hyperbolic vs Runpod
- Hyperbolic vs Thunder Compute
- Hyperbolic vs Vast.ai
- Hyperbolic vs Verda
Machine-readable
- This page as Markdown
/compare/beam-vs-hyperbolic.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/beam.json·/api/v1/tools/hyperbolic.json - From a terminal
anchor compare beam hyperbolic(the CLI) - Over MCP
compare_tools {"a": "beam", "b": "hyperbolic"}at/mcp, no key