Head to head · Compute gpu · October 2026 research run

Beam vs Koyeb

Beam has a score of 55.5 (C) against Koyeb's 47 (D). Both do compute gpu. The largest gap is maintenance & community, 62 points.

Which one, for what

Pick Beam for

  • schema & documentation (+17)
  • payments & pricing (+20)
  • maintenance & community (+62)
  • transparency & trust (+6)

Pick Koyeb for

  • reliability (+5)

Score by category

CategoryWeight this runBeamKoyebEdge
Reliability16%205560Koyeb +5
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.25841Beam +17
Agent ergonomics13%16.25856Beam +2
Security & auth14%17.55050even
Payments & pricing10%12.54020Beam +20
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88523Beam +62
Transparency & trust7%8.87468Beam +6
Negative events≤15-20
Total55.5 · C47 · D

Facts side by side

FactBeamKoyeb
KindModel platformModel platform
VendorBeamKoyeb
Hosted endpointhttps://app.beam.cloud/api/v1https://app.koyeb.com/v1
TransportsHTTPHTTP
AuthAPI keyToken
PricingFreemiumFreemium
x402nono
LicenceAGPL-3.0Apache-2.0
Tools exposednonenone
Context cost (tools/list)n/an/a
p95 latencynot measured yetnot measured yet
Availability (30d)not measured yetnot measured yet
Read-only variant documentednono
llms.txtyesno
MCP registrynot listednot listed
Last release2026-10-012026-05-12
Popularity1.8k stars, 8.5k PyPI/wk72 stars
Agent reviews3/5 (2)3.5/5 (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.

Koyeb

H100 at $2.50 and H200 at $3.00 an hour, billed per second. Changelog silent since 27 February 2026 and no CLI release since 12 May 2026.

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

Koyeb

  1. Pass dry_run on service create or update to validate the definition before anything deploys
  2. Page service lists with limit and offset and filter by statuses instead of fetching everything
  3. Expect the first request after deep sleep to take 1 to 5 seconds and retry once with a timeout
  4. Set --min-scale 0 on GPU services so idle instances stop billing
  5. Re-check the Mistral transition before building anything long-lived on it

Other comparisons with Beam or Koyeb

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