Modal
Serverless Python for GPU workloads.

HARDWARE REQUIREMENTS //
Self-hosted server · Datacenter GPU (80 GB+)
T4 → H100 available. B200 in preview.
Why we recommend Modal
- Genuinely free
Has a free tier you can actually finish a project on, not the 3-credits-then-paywall pattern.
- Top-tier pick
Power-user score 85/100 — consistently rated highly by people who use this every day, not just benchmark chasers.
- Beginner-friendly
You don't need to read a paper before getting your first result — sensible defaults and a quick install.
- Hosted API too
Both self-hostable and available as a hosted API — prototype on someone else's GPU, deploy on yours.
Documentation-led datasheet
This page summarizes upstream documentation, release information, and editorially reviewed catalogue fields. It is not presented as a hands-on benchmark. Verify changing requirements at the official project; report stale data through our corrections channel.
AT-A-GLANCE SIGNALS //
DERIVED FROM THIS PAGE'S DATA- Install difficultyEasy
Runs CPU-only — no CUDA / driver gymnastics required.
- Hardware comfortEnthusiast
Needs 16 GB minimum — RTX 3090 / 4090 territory.
- EcosystemAPI-first
Exposes a stable API — you can build on top of it programmatically.
- VerificationRecent
Catalogue entry last updated 68 days ago — re-verification due soon.
Other orchestration & apis tools we rate
Three picks across different tradeoffs — so you don't end up with three near-clones of Modal.
What is Modal?
Define functions in Python; Modal runs them on-demand on GPUs. Excellent for batched ComfyUI workflows, fine-tunes, and exposing models as HTTPS endpoints with autoscaling.
Pros & cons
✓ PROS
- Cleanest dev experience for serverless GPU
- Autoscaling to zero
- Good cold-start mitigations
– CONS
- Locked to their SDK
- Less raw control than a VM
What's actually free?
$30/month free compute credit on signup.


