Modal

✓ Editorially verified

Serverless GPUs and infra for training & serving ML.

Freemium· $30/mo free credits; pay-as-you-go GPU ratesFine-tuningInfrastructure (any model you can host)8.7 / 10

Best for

Pick Modal when you need serverless GPUs for ML workloads and you want to write Python rather than Kubernetes manifests.

Skip if

Skip it for latency-sensitive serving of large models without warm pools.

Modal is a serverless platform for ML workloads — pip install Modal in a Python script, decorate a function, and you can call code that runs on H100s with zero infrastructure setup. The product is genuinely Python-native; the same script runs locally for dev and on Modal's GPUs for prod.

For fine-tuning runs, batch inference, custom serving, and any workload that needs GPUs sometimes but not always, Modal is the most ergonomic option on the market. The auto-scaling is fast (sub-second cold starts on warm pools), the pricing is honest, and the credit-tier free quota is generous for evaluation.

Cold-start latency on large models is the trade-off — for latency-sensitive inference of a 70B parameter model, you'll either keep a warm pool (expensive) or accept multi-second cold starts. Bills can also surprise at scale; the per-second GPU pricing adds up faster than people expect.

Editor's take

Modal is the platform that made serverless GPU access feel like a normal Python decorator. For ML teams that don't want a dedicated ops function, it's transformative.

— The AI Tool Bible editorial team