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Modal

modal.com

Modal is a platform for running AI workloads instantly with scalable GPUs and Python-first infrastructure.

Overview

Modal is a programmable AI infrastructure platform that lets you run inference, training, and batch workloads using simple Python code. It handles GPUs, autoscaling, storage, and observability for you, so deploying AI feels fast, local, and effortless.

Key features

  • Sub-second cold starts and instant autoscaling
  • Python-first SDK for defining infrastructure as code
  • Support for any GPU type (B300, B200, H100, A100, L40S, etc.)
  • Multi-node training with up to 128 B200s
  • Sandboxes for running untrusted code at scale
  • Built-in observability with logging and metrics
  • Global GPU infrastructure across multiple clouds
  • Pay-per-second billing with no idle costs
  • Token-based pricing for shared endpoints
  • SOC2 and HIPAA compliance
Pros
  • No infrastructure management required
  • Extremely fast autoscaling and cold starts
  • Flexible hardware selection and multi-cloud routing
  • Transparent per-second billing with no reserved capacity
  • Strong observability and production-ready tooling
  • Supports full ML lifecycle from training to inference
  • Isolated sandboxes for secure agent execution
Cons
  • Requires Python for SDK usage
  • Learning curve for distributed training and advanced features
  • Pricing can be high for sustained GPU workloads compared to reserved instances
  • Limited to serverless model (not suitable for always-on services)
Use this if
You need to run AI models, training jobs, or batch processing at scale without managing infrastructure. Ideal for spiky or unpredictable workloads where serverless autoscaling provides cost savings.
Skip this if
You need always-on services, have predictable sustained GPU usage where reserved instances are cheaper, or require non-Python infrastructure definitions.

Best for

AI teams running inference and training workloadsBatch processing and data-intensive computeBuilding and scaling AI agentsFine-tuning and reinforcement learningTeams needing instant autoscaling without capacity planningGPU-accelerated research and experimentation

Alternatives

AWS SageMakerGoogle Vertex AILambda LabsPaperspaceRunPodTogether AI

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