Modal vs Vast.ai Comparison
Detailed comparison of features, pricing, and capabilities
Last updated May 1, 2026
Overview
Compare key metrics and features at a glance
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.
Vast.ai
https://vast.ai
Vast.ai is a decentralized cloud GPU marketplace that connects individuals and businesses who need GPU compute resources with hosts who have idle GPU hardware available for rent. The platform allows users to rent GPU instances at significantly lower prices than traditional cloud providers by aggregating consumer and data center GPUs from around the world. Vast.ai supports a wide range of use cases including machine learning training, inference, rendering, and other compute-intensive workloads.
Quick Comparison
| Detail | Modal | Vast.ai |
|---|---|---|
| Category | AI Cloud Infrastructure | AI Cloud Infrastructure |
| Starting Price | Free | Contact Sales |
| Plans Available | 3 | 3 |
| Features Tracked | 20 | 16 |
| Founded | 2021 | 2017 |
| Headquarters | New York, USA | San Francisco, USA |
Features
Detailed feature-by-feature comparison
Feature Comparison
| Feature | | |
|---|---|---|
| api | ||
| CLI & SDK | ||
| REST API | ||
| core | ||
| Automatic Dependency Management | ||
| Batch Job Processing | ||
| Clusters for Training | ||
| Cron Jobs | ||
| Custom Container Runtime | ||
| Diverse GPU Support | ||
| GPU Marketplace | ||
| GPU-Backed Notebooks | ||
| High-Throughput Storage System | ||
| Instance Filtering | ||
| Interruptible Instances | ||
| Model Training and Fine-tuning | ||
| Multi-Cloud GPU Pool | ||
| On-Demand Instances | ||
| Per-Second Billing | ||
| Pre-Built Templates | ||
| Python-Native Code Definition | ||
| Real-Time Pricing | ||
| Reserved Instances | ||
| Scale to Zero Pricing | ||
| Serverless GPU Inference | ||
| Serverless Inference | ||
| Web Endpoints | ||
| integration | ||
| Cloud Bucket Integration | ||
| External Database Connectivity | ||
| Key-Value Dictionaries | ||
| Networking Tools | ||
| Persistent Volumes | ||
| Task Queues | ||
| security | ||
| Direct Payload Delivery | ||
| SOC2 Certification | ||
| Sandboxes for Untrusted Code | ||
| support | ||
| 24/7 Expert Support | ||
| Integrated Logging and Monitoring | ||
Pricing
Compare pricing plans and value for money
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.
Vast.ai
Contact Sales
Price Components
- GPU Usage: $0/second
- GPU Usage: $0/second
- Reserved Capacity: $0/term
Best For
Cost-sensitive ML practitioners and researchers running batch training, inference, or rendering on flexible, preemptible GPU workloads.
Integrations
See which third-party services are supported
Supported Integrations
Coming Soon
Integration comparison data for Modal, Vast.ai is being collected and will be available soon.
Strengths & Limitations
Key strengths and limitations of each service
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
Vast.ai
Cost-sensitive ML practitioners and researchers running batch training, inference, or rendering on flexible, preemptible GPU workloads.
- Decentralized marketplace aggregates 20,000+ GPUs worldwide, offering 3-6x savings via dynamic real-time pricing over hyperscalers.
- Per-second billing with on-demand, interruptible (50%+ cheaper), and reserved options for flexible cost control.
- Supports diverse high-end GPUs like RTX 4090, A100, H200 with pre-built AI templates and multi-GPU configs.
- Instant deployment via web, CLI, SDK, API, and native Docker for rapid ML training and inference.
- Interruptible instances risk preemption, unsuitable for production needing guaranteed uptime.
- Decentralized peer-to-peer model may yield inconsistent reliability versus managed hyperscaler infrastructure.
- Small team (11-50 employees) limits enterprise-grade support and scale compared to giants like AWS.
Company Info
Company details and background
Modal
Vast.ai
Comparison FAQ
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