Keywords AI

CoreWeave vs Modal

Compare CoreWeave and Modal side by side. Both are tools in the Inference & Compute category.

Quick Comparison

CoreWeave
CoreWeave
Modal
Modal
CategoryInference & ComputeInference & Compute
PricingUsage-basedUsage-based
Best ForAI companies and startups that need large-scale GPU clusters for training and inferencePython developers who want serverless GPU infrastructure without managing containers or Kubernetes
Websitecoreweave.commodal.com
Key Features
  • Large-scale GPU clusters (H100, A100)
  • InfiniBand networking for distributed training
  • Kubernetes-native orchestration
  • On-demand and reserved capacity
  • Bare-metal performance
  • Serverless cloud for AI
  • Python-native container orchestration
  • Auto-scaling GPU infrastructure
  • Pay-per-second billing
  • Built-in web endpoints
Use Cases
  • Large language model training
  • Distributed training across GPU clusters
  • High-performance inference at scale
  • AI startup compute infrastructure
  • Batch processing and fine-tuning
  • Serverless model inference
  • Data processing pipelines
  • Batch jobs with GPU acceleration
  • Development environments with GPUs
  • Auto-scaling AI APIs

When to Choose CoreWeave vs Modal

CoreWeave
Choose CoreWeave if you need
  • Large language model training
  • Distributed training across GPU clusters
  • High-performance inference at scale
Pricing: Usage-based
Modal
Choose Modal if you need
  • Serverless model inference
  • Data processing pipelines
  • Batch jobs with GPU acceleration
Pricing: Usage-based

About CoreWeave

CoreWeave is a specialized cloud provider built from the ground up for GPU-accelerated workloads. Offering NVIDIA H100 and A100 GPUs on demand, CoreWeave provides significantly lower pricing than hyperscalers for AI training and inference. The platform includes Kubernetes-native orchestration, fast networking, and flexible scaling, making it popular with AI labs and startups that need large GPU clusters without long-term commitments.

About Modal

Modal is a serverless cloud platform for running AI workloads with zero infrastructure management. Developers write Python code and Modal handles containerization, GPU provisioning, scaling, and scheduling automatically. The platform supports GPU-accelerated functions, scheduled jobs, web endpoints, and batch processing, making it particularly popular for ML pipelines, model serving, and data processing tasks.

What is Inference & Compute?

Platforms that provide GPU compute, model hosting, and inference APIs. These companies serve open-source and third-party models, offer optimized inference engines, and provide cloud GPU infrastructure for AI workloads.

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