CoreWeave vs Modal Comparison
Detailed comparison of features, pricing, and capabilities
Last updated May 1, 2026
Overview
Compare key metrics and features at a glance
CoreWeave
https://www.coreweave.com
CoreWeave is a specialized cloud provider focused on GPU-accelerated computing, offering large-scale infrastructure optimized for AI/ML workloads, visual effects rendering, and high-performance computing. The company operates one of the largest fleets of NVIDIA GPUs in the cloud, providing on-demand access to compute resources through Kubernetes-based orchestration. CoreWeave went public on the Nasdaq in March 2025 and serves major AI companies, enterprises, and research institutions requiring massive parallel compute capacity.
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 | CoreWeave | Modal |
|---|---|---|
| Category | AI Cloud Infrastructure | AI Cloud Infrastructure |
| Starting Price | $4/mo | Free |
| Plans Available | 9 | 3 |
| Features Tracked | 14 | 20 |
| Founded | 2017 | 2021 |
| Headquarters | Roseland, USA | New York, USA |
Features
Detailed feature-by-feature comparison
Feature Comparison
| Feature | | |
|---|---|---|
| core | ||
| AI Object Storage | ||
| Automatic Dependency Management | ||
| Bare Metal Performance | ||
| Batch Job Processing | ||
| Cron Jobs | ||
| Custom Container Runtime | ||
| Fast Boot Times | ||
| File Storage | ||
| GPU-Backed Notebooks | ||
| HPC-First Architecture | ||
| High Durability Storage | ||
| High-Throughput Storage System | ||
| InfiniBand Networking | ||
| Kubernetes Orchestration | ||
| Mega GPU Clusters | ||
| Model Training and Fine-tuning | ||
| Multi-Cloud GPU Pool | ||
| NVIDIA GPU Access | ||
| No Egress Fees | ||
| Python-Native Code Definition | ||
| SLURM on Kubernetes (SUNK) | ||
| Scale to Zero Pricing | ||
| Serverless GPU Inference | ||
| Web Endpoints | ||
| custom | ||
| Custom Instance Types | ||
| integration | ||
| Cloud Bucket Integration | ||
| External Database Connectivity | ||
| Key-Value Dictionaries | ||
| Networking Tools | ||
| Persistent Volumes | ||
| Task Queues | ||
| security | ||
| Enterprise Security | ||
| Sandboxes for Untrusted Code | ||
| support | ||
| Integrated Logging and Monitoring | ||
Pricing
Compare pricing plans and value for money
CoreWeave
From $4/mo
Price Components
- On-Demand Compute: $42/hour
- On-Demand Compute: $68.8/hour
- On-Demand Compute: $49.24/hour
- On-Demand Compute: $6.42/hour
- Spot Compute: $2.99/hour
Best For
AI research labs and enterprises training large language models or running distributed inference at scale who prioritize raw compute performance and cost efficiency over geographic flexibility.
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 CoreWeave, Modal is being collected and will be available soon.
Strengths & Limitations
Key strengths and limitations of each service
CoreWeave
AI research labs and enterprises training large language models or running distributed inference at scale who prioritize raw compute performance and cost efficiency over geographic flexibility.
- Bare-metal GPU infrastructure eliminates virtualization overhead, delivering 2-3x faster training speeds than legacy cloud providers with identical hardware
- Massive scale support up to 100k+ GPU clusters with InfiniBand networking enables near-linear scaling for distributed AI training at supercomputing scale
- Transparent pricing with zero egress fees and sub-1 minute boot times reduces total cost of ownership by 30-40% versus AWS/Azure for data-intensive ML workloads
- Limited geographic footprint compared to AWS/Azure/GCP, restricting deployment options for enterprises requiring multi-region redundancy or specific data residency compliance
- Smaller ecosystem of pre-built integrations and managed services means users need deeper DevOps expertise to orchestrate complex multi-cloud architectures
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
CoreWeave
Modal
Comparison FAQ
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