Updated March 10, 2026
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.
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.
Core capabilities each platform advertises.
What each tool does well, and the limitations to keep in mind.
Pros
Cons
Pros
Cons
Choose CoreWeave if you wantChoose if you want
Choose Modal if you wantChoose if you want
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 500+ models through one gateway.