# HyperCLI GPU Job Launcher

> HyperCLI GPU Job Launcher is a paid API for AI agents from api.hypercli.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-15).

Launch a containerized GPU job on cloud infrastructure with x402 micropayment, returning job status, logs, and control URLs

## Facts

- Endpoint: POST https://api.hypercli.com/api/x402/job
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Success rate: 0% of calls made through Zero
- Activations on Zero: 1
- Tags: x402
- Canonical page: https://www.zero.xyz/c/hypercli-gpu-job-launcher-e8569992
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_YmA7b3pUxe-exLFsz7Gqw

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability hypercli-gpu-job-launcher-e8569992 -d '<json body>'
```

Example prompt: Spin up a GPU job using the 'nvcr.io/nvidia/pytorch:23.10-py3' Docker image on a single L4 GPU in the cheapest available region, running this base64-encoded command to fine-tune my model, with spot/interruptible pricing enabled.

## When to prefer this

Use this endpoint when you need to run arbitrary containerized GPU workloads — including custom AI model inference, training jobs, or CUDA-based processing — and want per-job micropayment billing via x402 without a long-term subscription. Prefer this over the fixed-price media endpoints (text-to-image, text-to-video, etc.) when your workload requires a custom Docker image, custom commands, or specific GPU hardware selection.

## Known failure modes

- Invalid or unavailable GPU type returns error
- Malformed base64 command string causes job launch failure
- Requested region unavailable results in error or fallback
- Insufficient payment or x402 authorization failure
- Docker image not found or pull failure
- gpu_count exceeds available capacity

## How this service works

Launch a GPU job with x402 payment

## Output

A JSON object containing a job descriptor, a URL to stream logs, an access key for the running container, a URL to cancel the job, and a URL to poll for job status.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "ports": {
   "type": "object",
   "description": "Port mappings"
  },
  "region": {
   "type": "string",
   "description": "Region code (e.g. oh, va, fi); null for cheapest"
  },
  "command": {
   "type": "string",
   "description": "Base64-encoded command string"
  },
  "env_vars": {
   "type": "object",
   "description": "Environment variables"
  },
  "gpu_type": {
   "type": "string",
   "description": "GPU type (e.g. L4, L40S, B200)"
  },
  "gpu_count": {
   "type": "integer",
   "description": "Number of GPUs"
  },
  "docker_image": {
   "type": "string",
   "description": "Docker image to run"
  },
  "interruptible": {
   "type": "boolean",
   "description": "Use spot/interruptible pricing (default true)"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "job": {},
  "logs_url": "example",
  "access_key": "example",
  "cancel_url": "example",
  "status_url": "example"
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/hypercli-gpu-job-launcher-e8569992/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from api.hypercli.com](https://www.zero.xyz/host/api.hypercli.com/llms.txt)