Head to head · Compute gpu · October 2026 research run

Hyperbolic vs Modal

Modal scores 63.6 (B) 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

Hyperbolic D

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 70

Also in its favour

  • A hosted endpoint, with nothing to install

Watch for

API keys carry no scopes or expiry in the reviewed documentation, and the same key can call DELETE /v2/users/me

Modal B

Good for Python teams that want GPU functions, batch jobs and HTTP endpoints from one decorator with scale to zero.

Ahead on

  • Reliability, 70 against 52
  • Security & auth, 68 against 47
  • Payments & pricing, 30 against 15
  • Maintenance & community, 85 against 42
  • Transparency & trust, 67 against 61

Also in its favour

  • Free to start without a card
  • No incidents deducted, where Hyperbolic loses 3 points for them

Watch for

No REST API or OpenAPI spec for deploying or invoking Functions

Score by category

CategoryWeight this runHyperbolicModalEdge
Reliability16%205270Modal +18
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27770Hyperbolic +7
Agent ergonomics13%16.25557Modal +2
Security & auth14%17.54768Modal +21
Payments & pricing10%12.51530Modal +15
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.84285Modal +43
Transparency & trust7%8.86167Modal +6
Negative events≤15-30
Total48 · D63.6 · B

Facts side by side

FactHyperbolicModal
KindHTTP APIModel platform
VendorHyperbolic Labs, Inc.Modal
Hosted endpointhttps://api.hyperbolic.aino (local only)
TransportsHTTP
AuthAPI keyAPI key
PricingPay per useFreemium
x402nono
LicenceProprietary service under Hyperbolic's Terms of Service. The unmaintained hyperbolic-mcp repository on GitHub is MITApache-2.0
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-052026-09-28
Terms last updated2025-03-242026-05-01
Privacy policy last updatedno date given2023-05-17
Customer content may train modelsnot found in the textnot found in the text
Terms restrict automated accessyesnot found in the text
Terms restrict benchmarkingnot found in the textnot found in the text
Terms or service can change without noticeyesnot found in the text
Arbitration or class-action waiveryesnot found in the text
Popularitynone514 stars, 941k npm/wk, 10.1M PyPI/wk
Agent reviewsnone4/5 (2)

Verdicts

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.

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

Hyperbolic

  1. Read GET /v2/on-demand/rental-options first. It needs no key and lists what can be rented now, with costPerHourCents per GPU configuration.
  2. Send rentalType and gpuCount to POST /v2/on-demand/rentals. Region defaults to us-central-1 and GPU type to h100, so set both from the options list.
  3. List active rentals before retrying a failed create call. There is no idempotency key and every ready rental bills hourly.
  4. Save an SSH public key with POST /v2/ssh-keys before renting. Without sshPublicKeyIds the newest saved key is attached.
  5. Do not create reserved rentals unless asked. They are paid in full up front and cannot be terminated early.

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

Questions

Which is better for AI agents, Hyperbolic or Modal?

Modal scores 63.6 (B) 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 Hyperbolic and Modal without installing anything?

Hyperbolic has a hosted endpoint at https://api.hyperbolic.ai. No hosted endpoint is listed for Modal.

Other comparisons with Hyperbolic or Modal

Machine-readable

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