Modal
Free tierHigh-performance AI infrastructure with sub-second cold starts and instant autoscaling
Key strengths
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Recent changes
- Starting price: $30/mo → $0/mo
- Plans updated: Starter plan is $0 + compute/month (includes $30/month free credits, 3 seats, 100 containers, 10 GPU concurrency). Team plan is $250 + compute/month (includes $100/month free credits, unlimited seats, 5000 containers, 50 GPU concurrency). Enterprise is custom pricing. Compute billed per second: e.g. H100 SXM5 at $0.001097/sec, CPU at $0.0000131/core/sec, Memory at $0.00000222/GiB/sec.
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Technical Use Cases
Modal is architected to support the full AI/ML development lifecycle across four primary workload categories:
1. Inference Serving Deploy model inference endpoints that autoscale to demand — scaling to zero when idle (eliminating cold-cost waste) and bursting to thousands of GPU instances under load. Per-second billing makes high-throughput, bursty inference economically efficient.
2. Model Training Run distributed training jobs across GPU clusters without provisioning or managing infrastructure. Multi-cloud spanning 20+ clouds provides access to a broad pool of accelerators (including H100 SXM5).
3. Batch & Data Processing Execute large-scale batch workloads — data preprocessing, embedding generation, evaluation pipelines — with instant autoscaling and per-second compute billing to minimize cost.
4. Code Sandboxes Spin up isolated, ephemeral execution environments (sandboxes) at scale — up to millions — suitable for AI agent tool use, code execution, and automated testing pipelines.
Target engineering teams:
- AI/ML platform and infrastructure engineers
- MLOps and LLMOps practitioners
- Independent researchers and developers needing on-demand GPU access
Compliance & security: SOC 2 Type II, HIPAA ready — suitable for regulated industries. Observability stack: Native Datadog and OpenTelemetry integration for metrics, traces, and logs.