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Modal Alternative

The Modal alternative built for startups

Same Python-native serverless GPU experience. Lower cost on A100 and below. Velar is the lean alternative to Modal — per-second billing, scale to zero, no mandatory team plan fee.

Why teams switch from Modal to Velar

Modal is a great product. But for startups and indie developers, GPU costs add up fast. Velar gives you the same developer experience at a price that makes sense for early-stage teams.

Lower GPU costs where it counts

A100 at $1.74/hr vs Modal's $2.50/hr. L40S at $1.08/hr vs $1.95/hr. Per-second billing means you never overpay for idle time.

Same Python workflow

Decorate a function, specify a GPU, deploy. No YAML, no Kubernetes, no Docker knowledge required.

No minimum spend

Run experiments and side projects without worrying about hitting a monthly minimum. Pay only for what you use.

Velar vs Modal

FeatureVelarModal
Python-native SDK
Per-second billing
Scale to zero
Sub-minute deploys
Free starter credits
A100 80GB pricing$1.74/hr$2.50/hr
L40S 48GB pricing$1.08/hr$1.95/hr
Free tier

Pricing as of March 2026. Check velar.run/pricing for current rates.

Familiar Python-native API

If you already know Modal, you already know Velar. Decorate your function, specify the GPU, and deploy. The workflow is intentionally familiar so your team can migrate in minutes, not days.

  • Deploy with a single Python decorator
  • No YAML, no Docker knowledge required
  • Works with any Python ML library
  • Built-in logs and cost tracking
import velar

app = velar.App("inference")
image = velar.Image.from_registry(
    "pytorch/pytorch:2.1.0-cuda12.1-cudnn8-runtime"
).pip_install("transformers")

@app.function(gpu="A100", image=image)
def generate(prompt: str):
    from transformers import pipeline
    pipe = pipeline("text-generation", model="gpt2")
    return pipe(prompt)[0]["generated_text"]

app.deploy()
result = generate.remote("Hello, world")

Ready to make the switch?

Velar Cloud is paused. Join the waitlist for the relaunch. Deploy your first workload in under 5 minutes.