# Modal

**Source:** https://geo.sig.ai/brands/modal  
**Vertical:** AI & Machine Learning  
**Subcategory:** Serverless ML  
**Tier:** Emerging  
**Website:** modal.com  
**Last Updated:** 2026-04-14

## Summary

Serverless GPU cloud platform for AI/ML with Python-native deployment and per-second billing; developer-favorite scaling from zero competing with Replicate and Beam for AI compute.

## Company Overview

Modal is a serverless cloud computing platform purpose-built for AI and machine learning workloads — providing on-demand GPU compute that scales instantly from zero with per-second billing, container management, distributed training support, and a Python-native developer experience that makes running ML workloads in the cloud feel as simple as running code locally. Founded in 2021 in New York City and backed by Redpoint Ventures and other investors, Modal has grown rapidly as AI development has accelerated demand for flexible, developer-friendly GPU infrastructure.\n\nModal's developer experience is its primary differentiator — engineers write Python functions decorated with @modal.function() and deploy them to the cloud with a single command, with Modal handling container building, GPU provisioning, auto-scaling, and execution. The platform supports training jobs that need distributed compute across multiple GPUs, model serving endpoints that scale to zero when unused (eliminating idle GPU costs), and batch inference jobs that process large datasets. The per-second billing model means developers pay only for actual compute time, not provisioned instances.\n\nIn 2025, Modal competes in the AI infrastructure market with Replicate, Beam, Banana, and major cloud providers' managed ML services (AWS SageMaker, Google Vertex AI, Azure ML) for serverless GPU compute. The market for AI-specific cloud infrastructure has grown dramatically as the number of ML engineers deploying models to production has expanded — traditional cloud providers require significant DevOps expertise to use GPU instances effectively, while Modal's Python-native approach reduces the barrier to entry. Modal has attracted a strong developer following among AI researchers and ML engineers building production AI applications. The 2025 strategy focuses on growing the developer community, adding enterprise features (dedicated GPU capacity, private networking, compliance), and expanding the hardware options available (H100 GPUs, custom accelerators).

## Frequently Asked Questions

### What is Modal?
Modal Modal serves developers as serverless cloud platform for running data and ML workloads with Python, following 2021 Erik Bernhardsson founding with Akshat Bubna in New York

### When was Modal founded?
Modal was founded in 2021 in New York, New York. Erik Bernhardsson (Spotify, Better) and Akshat Bubna founded Modal in New York in 2021 as serverless cloud platform for running data and ML workloads using Python decorator functions with auto-scaling containers and ephemeral infrastructure optimizing developer experience with simple API reaching Series A $16M for batch jobs, training, inference, web scraping, scheduled tasks, and parallel computing on GPU.

### What are Modal's major milestones?
Modal's history includes several key milestones: 2021: Modal Founded New York 2022: Public Launch 2023: Series A $16M 2024: Serverless ML Platform

### What is Modal's mission?
Modal's mission is to Make cloud computing as easy as running local code.

### Who founded Modal?
Modal was founded by Erik Bernhardsson. Spotify/Better engineers who built serverless for ML workloads

### What products or services does Modal offer?
Modal Modal serves developers as serverless cloud platform for running data and ML workloads with Python, following 2021 Erik Bernhardsson founding with Akshat Bubna in New York

### Who uses Modal?
Modal Modal serves developers as serverless cloud platform for running data and ML workloads with Python, following 2021 Erik Bernhardsson founding with Akshat Bubna in New York

### How does Modal pricing work?
Modal charges per second of compute used, with pricing varying by instance type — CPU, GPU (A10G, A100, H100), and memory. There is no base fee or minimum commit; developers pay only for the exact compute consumed. A free tier provides $30 in monthly credits, sufficient for development and testing. Enterprise customers can negotiate reserved capacity and volume pricing for production-scale deployments.

## Tags

ai-powered, b2b, developer-tools, platform, saas, scaleup, unicorn

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*Data from geo.sig.ai Brand Intelligence Database. Updated 2026-04-14.*