Heroku vs Modal Comparison
Detailed comparison of features, pricing, and capabilities
Last updated May 1, 2026
Overview
Compare key metrics and features at a glance
Heroku
https://www.heroku.com
Heroku is a cloud platform as a service (PaaS) that enables companies to build, deliver, monitor and scale applications. The platform supports several programming languages and allows developers to deploy, manage, and scale modern apps without having to manage the underlying infrastructure. Heroku was acquired by Salesforce in 2010 and has since become one of the most popular PaaS solutions for web application deployment.
Modal
https://modal.com
Modal is a cloud infrastructure platform that allows developers and data scientists to run code in the cloud without managing servers or infrastructure. It provides a Python-native interface for running serverless functions, training machine learning models, and deploying AI applications with on-demand GPU and CPU compute. Modal handles scaling, containerization, and dependency management automatically, enabling teams to go from local code to production cloud workloads with minimal configuration.
Quick Comparison
| Detail | Heroku | Modal |
|---|---|---|
| Category | Platform as a Service (PaaS) | AI Cloud Infrastructure |
| Starting Price | Contact Sales | Free |
| Plans Available | 0 | 3 |
| Features Tracked | 17 | 20 |
| Founded | 2007 | 2021 |
| Headquarters | San Francisco, USA | New York, USA |
Features
Detailed feature-by-feature comparison
Feature Comparison
| Feature | | |
|---|---|---|
| api | ||
| CLI Access | ||
| core | ||
| Application Metrics | ||
| Automatic Dependency Management | ||
| Autoscaling | ||
| Batch Job Processing | ||
| Cron Jobs | ||
| Custom Container Runtime | ||
| Dynos | ||
| GPU-Backed Notebooks | ||
| Heroku Dashboard | ||
| Heroku Key-Value Store | ||
| Heroku Pipelines | ||
| Heroku Postgres | ||
| High-Throughput Storage System | ||
| Managed Inference and Agents | ||
| Model Training and Fine-tuning | ||
| Multi-Cloud GPU Pool | ||
| Multi-language Support | ||
| Python-Native Code Definition | ||
| Scale to Zero Pricing | ||
| Serverless GPU Inference | ||
| Web Endpoints | ||
| custom | ||
| Buildpacks | ||
| integration | ||
| Add-ons Marketplace | ||
| Apache Kafka on Heroku | ||
| Cloud Bucket Integration | ||
| External Database Connectivity | ||
| Heroku AppLink | Add-on | |
| Key-Value Dictionaries | ||
| Model Context Protocol (MCP) | ||
| Networking Tools | ||
| Persistent Volumes | ||
| Task Queues | ||
| security | ||
| Sandboxes for Untrusted Code | ||
| Security Patches | ||
| support | ||
| Integrated Logging and Monitoring | ||
| Team Collaboration | ||
Pricing
Compare pricing plans and value for money
Heroku
Contact Sales
No pricing data available yet
Best For
Developers and startups needing quick Git-based deploys and managed scaling for modern web apps without infrastructure management.
Modal
From $0/mo
Price Components
- base_fee: $0/month (30 included)
- seats: $0/user (3 included)
- CPU: $0.0000131/core-second
- Memory: $0.00000222/GiB-second
- Nvidia B200: $0.001736/second
Best For
Python-focused ML teams and startups needing rapid GPU-accelerated model training and inference without managing Kubernetes, containers, or infrastructure scaling.
Integrations
See which third-party services are supported
Supported Integrations
Coming Soon
Integration comparison data for Heroku, Modal is being collected and will be available soon.
Strengths & Limitations
Key strengths and limitations of each service
Heroku
Developers and startups needing quick Git-based deploys and managed scaling for modern web apps without infrastructure management.
- Git push deployment and dyno autoscaling enable instant scaling for web apps, unlike more complex setups on AWS or Azure.
- Managed data services like Heroku Postgres and Redis handle backups and HA, freeing developers from infra tasks.
- Native buildpacks for Node.js, Python, Java, and others simplify multi-language deploys versus custom configs elsewhere.
- Doubled 1GB slug limit supports AI/ML frameworks, boosting complex app compatibility.
- Transitioning to sustaining engineering mode limits new features, lagging behind innovative PaaS like Upsun.
- Runs atop AWS EC2 with dyno-based pricing that can escalate costs for high-traffic apps versus granular cloud options.
- Enterprise feature freeze pushes users toward Salesforce alternatives like Agentforce.
Modal
Python-focused ML teams and startups needing rapid GPU-accelerated model training and inference without managing Kubernetes, containers, or infrastructure scaling.
- Python-native serverless platform eliminates manual containerization and dependency management, reducing deployment friction for ML engineers and data scientists
- On-demand access to high-performance GPUs (A100, H100) with per-second billing removes upfront infrastructure costs and commitment lock-in common with traditional cloud providers
- Automatic horizontal scaling to thousands of parallel containers with zero-to-scale capability enables cost-efficient handling of bursty AI workloads without manual orchestration
- Limited to Python ecosystem, excluding teams using Go, Node.js, or other languages that dominate in serverless and edge computing markets
- Series B funding and 11-50 employee count signal smaller scale and fewer enterprise resources compared to hyperscalers (AWS, Google Cloud, Azure) controlling 65% of AIaaS market revenue
Company Info
Company details and background
Heroku
Modal
Comparison FAQ
Common questions about comparing Heroku and Modal
No FAQs available yet