Head to head · Compute gpu · October 2026 research run
Beam vs Verda
Verda scores 62.3 (B) on agent readiness against Beam's 55.5 (C), and leads in 5 of 7 scored categories. Beam leads on payments & pricing. 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 20
Also in its favour
- Open source
Watch for
No published request rate limits, 429 handling or SLA
Verda B
Good for Agents that rent whole GPU machines or clusters in Finland for training or batch work, or deploy scale-to-zero container endpoints, and that can run a local CLI for MCP.
Ahead on
- Reliability, 67 against 55
- Schema & documentation, 82 against 58
- Agent ergonomics, 63 against 58
- Security & auth, 68 against 50
Also in its favour
- Runs on your own machine
Watch for
No free tier. Accounts are prepaid, and instances are discontinued and volumes deleted when the balance reaches zero
Score by category
| Category | Weight this run | Beam | Verda | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 55 | 67 | Verda +12 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 58 | 82 | Verda +24 |
| Agent ergonomics | 13%16.2 | 58 | 63 | Verda +5 |
| Security & auth | 14%17.5 | 50 | 68 | Verda +18 |
| Payments & pricing | 10%12.5 | 40 | 20 | Beam +20 |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 85 | 83 | Beam +2 |
| Transparency & trust | 7%8.8 | 74 | 76 | Verda +2 |
| Negative events | ≤15 | -2 | -3 | |
| Total | 55.5 · C | 62.3 · B |
Facts side by side
| Fact | Beam | Verda |
|---|---|---|
| Kind | Model platform | HTTP API |
| Vendor | Beam | Verda |
| Hosted endpoint | https://app.beam.cloud/api/v1 | https://api.verda.com/v1 |
| Transports | HTTP | HTTP, stdio |
| Auth | API key | OAuth |
| Pricing | Freemium | Pay per use |
| x402 | no | no |
| Licence | AGPL-3.0 | Proprietary service under Verda's Terms of Service. The CLI, the Python SDK and the Go SDK on GitHub are Apache-2.0 |
| Tools exposed | none | 18 |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-10-01 | 2026-10-07 |
| Terms last updated | 2026-09-14 | 2025-09-30 |
| 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 | not found in the text |
| Terms restrict benchmarking | not found in the text | yes |
| Terms or service can change without notice | not found in the text | not found in the text |
| Arbitration or class-action waiver | yes | yes |
| Popularity | 1.8k stars, 8.5k PyPI/wk | 10k PyPI/wk |
| 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.
Verda
The REST API has a public OpenAPI 3.1 document, a dated changelog, published rate limits with Retry-After, and an audit log endpoint. The CLI's MCP server refuses billed or destructive calls without confirm: true. Access needs a browser signup and a prepaid balance, credentials carry one scope, and instance creation has no idempotency key.
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
Verda
- Exchange the client ID and secret at
POST /v1/oauth2/token, then send the access token as a Bearer header. It expires after 3,600 seconds, so refresh it. - Send
location_codeon every create call. Requests without it have returned 400 since March 2026. - Call
GET /v1/instance-availabilitybefore launching.POST /v1/instancesreturns 503service_unavailablewhen the location has no capacity. - List instances before retrying a failed launch, because create has no idempotency key.
- Use the
deleteaction to stop charges.shutdownkeeps billing, and deleted volumes stay recoverable for 96 hours unlessdelete_permanentlyis set.
Questions
Which is better for AI agents, Beam or Verda?
Verda scores 62.3 (B) on agent readiness against Beam's 55.5 (C), and leads in 5 of 7 scored categories. Beam leads on payments & pricing.
Can an agent call Beam and Verda without installing anything?
Yes. Beam has a hosted endpoint at https://app.beam.cloud/api/v1 and Verda at https://api.verda.com/v1.
Are Beam and Verda open source?
Beam is open source (AGPL-3.0). No open-source release is listed for Verda.
Other comparisons with Beam or Verda
- Baseten vs Beam
- Baseten vs Verda
- Beam vs Cerebrium
- Beam vs CoreWeave
- Beam vs Hugging Face Inference Endpoints
- Beam vs Hyperbolic
- 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
- Cerebrium vs Verda
- CoreWeave vs Verda
- Hugging Face Inference Endpoints vs Verda
- Hyperbolic vs Verda
- Koyeb vs Verda
- Lambda Cloud vs Verda
- Modal vs Verda
- Nebius AI Cloud vs Verda
- Northflank vs Verda
- Replicate Deployments vs Verda
- Runpod vs Verda
- Thunder Compute vs Verda
- Vast.ai vs Verda
Machine-readable
- This page as Markdown
/compare/beam-vs-verda.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/beam.json·/api/v1/tools/verda.json - From a terminal
anchor compare beam verda(the CLI) - Over MCP
compare_tools {"a": "beam", "b": "verda"}at/mcp, no key