Modal - Serverless Cloud for AI, ML, and Data Applications

Modal Serverless Cloud for AI, ML, and Data Applications

What is Modal?

Modal offers a serverless cloud environment specifically designed for AI, machine learning, and data-intensive applications. It allows developers to deploy and scale their applications without managing infrastructure. Modal's infrastructure provides sub-second container starts, seamless autoscaling to hundreds of GPUs, and flexible configuration options.

The platform supports a wide range of use cases, including generative AI inference, model fine-tuning, and large-scale batch processing. With zero configuration files and straightforward Python integration, Modal simplifies the process of deploying complex applications, allowing developers focus on innovation, not on server management.

Features

Flexible Environments: Bring your own image or build one in Python, scale resources as needed, and leverage state-of-the-art GPUs like H100s & A100s.
Seamless Integrations: Export function logs to Datadog or any OpenTelemetry-compatible provider, and easily mount cloud storage from major providers (S3, R2 etc.).
Data Storage: Manage data effortlessly with storage solutions (network volumes, key-value stores and queues).
Job Scheduling: Set up cron jobs, retries, and timeouts, or use batching to optimize resource usage.
Web Endpoints: Deploy and manage web services with ease. Create custom domains, set up streaming and websockets, and serve functions as secure HTTPS endpoints.
Built-In Debugging: Use the modal shell for interactive debugging and set breakpoints to pinpoint issues quickly.

Use Cases

Generative AI Inference
Fine-tuning and training models
Batch processing
Language Model Serving
Image, Video, and 3D Processing
Audio Processing
Sandboxed Code Execution
Computational Biology Applications

FAQs

How does serverless pricing differ from traditional on-demand pricing?

With serverless pricing, you only pay for the resources consumed during code execution, by the CPU cycle. Traditional on-demand pricing often involves paying for idle resources.
What kinds of applications can I deploy using Modal?

You can deploy a wide range of applications including, but not limited to, language model inference, image/video/3D processing, audio processing, fine-tuning, job queues, batch processing, sandboxing code, and computational biology applications.
Can I use my AWS, GCP, or Azure credits on Modal?

You can use committed AWS spend on Modal via AWS Marketplace. Coming soon to Google Cloud Marketplace.