CoreWeave vs Modal: Complete Comparison (2026)

Why choose CoreWeave

• Higher Support score (7/10 vs 6/10)
• Higher Cost score (6/10 vs 5/10)
• Better fit for enterprise (9/10 vs 7/10)
• Includes Dedicated Servers, which Modal lacks

Why choose Modal

• Has a free plan (CoreWeave does not)
• Higher Ease of Use score (8/10 vs 5/10)
• Better fit for startups (9/10 vs 6/10)
• Better fit for developers (9/10 vs 7/10)
• Includes Serverless Functions, which CoreWeave lacks

CoreWeave

Pros

• Free internet egress and internal data transfer, which lowers the cost of moving large datasets and model checkpoints.
• Large inventory of current NVIDIA hardware, from L40S to GB200 NVL72, with InfiniBand for multi-node training.
• Spot rates are well below on-demand rates, for example $19.71 versus $49.24 per hour for an 8-GPU H100 node, and committed discounts reach up to 60%.
• The CKS control plane and SUNK Slurm scheduler are free, so you pay only for compute.
• A Terraform and OpenTofu provider manages clusters, VPCs, storage, and inference as code.

Cons

• No free tier or trial credits, and minimum spend is reported to be high even for light use.
• No managed databases, serverless functions, or CDN, so a second cloud is often needed.
• Regions are concentrated in North America and Europe, with limited Asia-Pacific coverage.
• The best pricing usually requires multi-year contracts and an enterprise sales process.
• Few public user reviews are available on G2 or Gartner to validate claims.

Modal

Pros

• GPUs from the T4 up to the B300 are available without quota requests or reservations, and workloads can burst to thousands of containers.
• Per-second billing and scale-to-zero mean idle bursty inference workloads cost nothing.
• Python developers define infrastructure in code and deploy with a single CLI command, with no Kubernetes or Dockerfiles needed.
• The free Starter plan includes $30 a month of compute, and startup and academic credit programs are available.
• Sandboxes support large numbers of concurrent isolated environments for AI agents and untrusted code.

Cons

• Always-on or steady workloads can cost more than reserved GPU rentals from providers such as RunPod or Lambda.
• Containers stay billable for 60 seconds after the last request by default, and keep-warm settings are a common source of bill surprises.
• Region pinning raises prices by 1.15 to 1.75 times, and non-preemptible execution by 3 times.
• SSO, audit logs, and HIPAA support are limited to the custom-priced Enterprise plan.
• Credits from AWS, GCP, or Azure cannot be applied to Modal usage.