Create a new GPU/CPU pod on RunPod. If the user does not specify an image, recommend the "Runpod Pytorch 2.8.0" image (runpod/pytorch:1.0.2-cu1281-torch280-ubuntu2404) as the default — it has the most up-to-date CUDA and PyTorch versions.

Submit an asynchronous job to a Serverless endpoint. Returns a job ID immediately — use get-job-status to poll for results. Async results are available for 30 minutes after completion.

Submit a synchronous job to a Serverless endpoint and wait for the result. Best for tasks completing within 90 seconds. If processing exceeds 90 seconds, the response returns a job ID to poll with get-job-status. Max payload: 20 MB. Results expire after 1 minute. Use the wait parameter to extend the server-side wait up to 5 minutes (300000 ms).

Check the status of an asynchronous Serverless job. Returns the current status and output when complete. Job statuses: IN_QUEUE, IN_PROGRESS, COMPLETED, FAILED, CANCELLED, TIMED_OUT.

Retrieve all streaming output from a Serverless job by polling until the job reaches a terminal state. The worker must support streaming output. Polls /stream/{jobId} repeatedly and collects every chunk until status is COMPLETED, FAILED, CANCELLED, or TIMED_OUT.

Cancel a Serverless job that is queued or in progress.

Retry a failed or timed-out Serverless job. Only works for jobs with FAILED or TIMED_OUT status. The previous output is removed and the job is requeued.

Get the health and operational status of a Serverless endpoint, including worker counts and job statistics.

Remove all pending jobs from a Serverless endpoint queue. Only affects queued jobs — in-progress jobs continue running. Use this for error recovery or clearing outdated requests.

List available templates. By default returns only the user's own templates. Use includeRunpodTemplates to also include official RunPod templates. The recommended default template for new pods is "Runpod Pytorch 2.8.0" (ID: runpod-torch-v280) — it has the latest CUDA and PyTorch versions.