> ## Documentation Index
> Fetch the complete documentation index at: https://docs.u-kiyo.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Choosing a GPU

> Match memory, GPU count, and runtime to your workload.

Start with [current offers](/get-started/pricing); a model appearing in documentation does not guarantee it is in stock.

## Check these fields

* **VRAM per GPU:** allow space for model weights, activations, context, and your application's overhead.
* **GPU quantity:** multiple GPUs require software that can use them. Their memory is not automatically one shared pool.
* **Whole-instance hourly price:** compare the configuration, not just the model name.
* **Maximum duration and budget:** make sure the available runtime covers your job.
* **Storage:** copy important results off the instance before it ends.

A 24 GB card may suit smaller models and image workflows. Larger-memory cards may be needed for larger models or batches. Fit and performance depend on precision, architecture, context length, and software; Ukiyo does not promise a particular model will fit from its parameter count alone.

Use a small representative workload before committing to a long run. See [SSH](/guides/ssh) and [Jupyter](/guides/jupyter) for access; application installation is separate from renting compute.


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.