Five short prompts for an agent that needs a GPU

I work on CloudGPU. If your assistant can call GPU tools, the useful request is one short sentence: what to do, what the cap is, and when to wait. Here are five prompts you can paste, plus the short steps behind each one.

1. Rent a GPU

Prompt:

Use CloudGPU for this task: check my running instances, show the current quote and a $2 budget cap, and wait for my approval before creating anything.

Steps:

1. Use an MCP-capable client with CloudGPU connected (remote endpoint https://cloudgpu.app/mcp, or the local MCP server). Approving account access is not approval of this paid task.
2. Let the agent inspect running instances and whether this task needs a GPU.
3. Review the live quote, the $2 budget cap (a cap, not a GPU price), the time limit, the command, and the expected outputs. Treat storage charges as separate.
4. Approve only that quote, then let the agent create the rental or submit the Job. Keep the instance or Job id; do not retry an uncertain request blindly.

Guide: https://cloudgpu.app/guides/can-chatgpt-rent-and-reuse-a-cloud-gpu?utm_source=devto&utm_medium=article&utm_campaign=202611_agent_answers&utm_content=dt1115_rent

2. Reuse a running instance

Prompt:

Check whether I already have a suitable running CloudGPU instance for this task, and if it still fits, reuse it for these approved commands instead of starting a new GPU.

Steps:

1. Have the agent list running instances and check ownership, readiness, remaining spend, time and idle limits, and available memory or disk.
2. If a running rental fits, run only the newly approved commands on that same instance. Do not extend the original limits, and do not keep an idle GPU just to use remaining prepaid time.
3. A saved Workspace version reuses selected project files, not the operating system or installed packages. A later Job still needs a fresh quote and approval.
4. Separate Jobs each start and release their own GPU; they do not borrow a live rental. If applying files to an existing user-owned instance fails, do not stop that instance.

Guide: https://cloudgpu.app/guides/how-to-reuse-a-running-gpu-over-remote-mcp?utm_source=devto&utm_medium=article&utm_campaign=202611_agent_answers&utm_content=dt1115_reuse

3. Control the budget

Prompt:

For this CloudGPU task, set a $2 budget cap and a 1-hour time cap, show the current quote, and do not start until I approve.

Steps:

1. The $2 and 1-hour figures bound this request only. They are this-task caps, not a GPU price, and not approval for later tasks.
2. Review the live quote, including the billing increment, minimum charge, and time for setup, downloads, and bringing results back.
3. A top-up or a funded balance is not approval of this quote. Storage charges need a separate ok; they are not covered by the GPU spend cap.
4. After the task, check the recorded cost and confirm that a GPU rented for this task was released.

Guide: https://cloudgpu.app/guides/how-to-set-gpu-budget-caps-over-remote-mcp?utm_source=devto&utm_medium=article&utm_campaign=202611_agent_answers&utm_content=dt1115_budget

4. Run ComfyUI

Prompt:

Use CloudGPU to run this ComfyUI workflow: prefer a running instance if it already fits, keep a $2 budget cap, and download the images when it finishes.

Steps:

1. Prefer the official ComfyUI template. First check for a suitable running instance.
2. If a new rental is needed, review the live quote and this-task caps, then approve before creating it. The $2 figure is a budget cap, not a GPU price.
3. The template provides ComfyUI, not model weights. Download the weights the workflow needs onto the instance, into the matching folders under ComfyUI/models/.
4. If a public HTTPS API address is shown, it is only live while the instance runs. Submit an API-format workflow with POST /prompt, poll GET /history/{prompt_id}, and fetch images with GET /view.
5. Confirm the downloaded files first. Stop a rental only if this task created it. Do not stop an existing instance you were only reusing unless the owner asked.

Guide: https://cloudgpu.app/rent-gpu-for-comfyui?utm_source=devto&utm_medium=article&utm_campaign=202611_agent_answers&utm_content=dt1115_comfy

5. Save the results

Prompt:

Download this CloudGPU task’s results to ./outputs, confirm the files are there, and only then stop a GPU rented for this task.

Steps:

1. Stopping a rental deletes the instance disk. Saving files and stopping billing are separate steps.
2. Copy the results off the running machine first (a client download, rsync, or explicitly requested Job collection) and open the saved files to confirm they arrived.
3. If you also want a Workspace version, save selected project files after they are on the client computer. Workspace is not a full-disk backup and does not keep installed packages.
4. GPU spend caps do not approve extra paid storage. After the files are confirmed, stop only a GPU rented for this task. Do not destroy an existing user-owned instance you were only reusing unless the owner asked.

Guide: https://cloudgpu.app/guides/how-to-save-gpu-results-over-remote-mcp?utm_source=devto&utm_medium=article&utm_campaign=202611_agent_answers&utm_content=dt1115_save

Paste one prompt per task. The agent should wait when the quote is new, reuse a running machine when it already fits, and clean up only a rental it created for this request, after the downloads are confirmed.