CoreWeave vs Runpod

CoreWeave

Per-hour prices for 8-GPU H100, H200 and B200 nodes are public, the docs ship as Markdown with llms.txt and embedded OpenAPI specs, and IAM has read-only roles per service. An organisation must be approved by CoreWeave's sales team before any token exists, and no request rate limits were found in the reviewed documentation.

Runpod

Per-second billing across more than a dozen serverless GPU classes, H100 at $4.79 and A100 80 GB at $2.72 an hour. Data-centre outages of 6 to 24 hours in each of July, August and September 2026.

CoreWeave

1. Create an API access token at console.coreweave.com/tokens with an expiry and send it as Authorization: Bearer to https://api.coreweave.com
2. Add GPUs by applying a NodePool resource (compute.coreweave.com/v1alpha1) to a CKS cluster with instanceType and targetNodes. instanceType can't be changed afterwards
3. Set targetNodes to 0 or delete the Node Pool when a job ends. Nodes are whole 8-GPU machines billed by the hour
4. Never pass dry_run to the MCP tool coreweave_kubectl_apply expecting a preview. The reference says the parameter is ignored and the manifest is applied
5. Use a separate Forge API key and https://api.inference.wandb.ai/v1 for Serverless Inference. A CoreWeave API access token doesn't work there

Runpod

1. Create a Restricted or Read Only key per endpoint for the agent, not an All key
2. Use REST v2 at api.runpod.io/v2 with a Bearer header; avoid GraphQL, which puts the key in the URL
3. Fetch /run results within 30 minutes and /runsync results within 1 minute, or they're gone
4. Call /retry on a failed job ID rather than submitting a duplicate job
5. Check /health before relying on an endpoint idle for a week, since max workers drop to 0