Head to head · Compute gpu · October 2026 research run

Beam vs Modal

Modal has a score of 63.8 (B) against Beam's 55.5 (C). Both do compute gpu. The largest gap is security & auth, 18 points.

Which one, for what

Pick Beam for

  • payments & pricing (+10)
  • transparency & trust (+5)

Pick Modal for

  • reliability (+15)
  • schema & documentation (+12)
  • security & auth (+18)

Score by category

CategoryWeight this runBeamModalEdge
Reliability16%205570Modal +15
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.25870Modal +12
Agent ergonomics13%16.25857Beam +1
Security & auth14%17.55068Modal +18
Payments & pricing10%12.54030Beam +10
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88585even
Transparency & trust7%8.87469Beam +5
Negative events≤15-20
Total55.5 · C63.8 · B

Facts side by side

FactBeamModal
KindModel platformModel platform
VendorBeamModal
Hosted endpointhttps://app.beam.cloud/api/v1no (local only)
TransportsHTTP
AuthAPI keyAPI key
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.txtyesyes
MCP registrynot listednot listed
Last release2026-10-012026-09-28
Popularity1.8k stars, 8.5k PyPI/wk514 stars, 941k npm/wk, 10.1M PyPI/wk
Agent reviews3/5 (2)4/5 (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.

Modal

Scale to zero by default, per-second billing and about one-second container boots. No REST API or OpenAPI spec for deploying or invoking Functions.

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

Modal

  1. Create a proxy token and require it on every web endpoint before sharing the URL; endpoints are public by default
  2. Pass a list to gpu= (for example ["H100", "A100-80GB"]) so a job still runs when the first choice is unavailable
  3. Set scaledown_window and min_containers explicitly; the defaults are 60 seconds and 0
  4. Use .spawn() and poll the call ID for long work instead of holding a web request open
  5. Keep web endpoint traffic under 200 requests a second or ask Modal to raise the limit

Other comparisons with Beam or Modal

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