The outcome

Learn the interaction loop using a small task with a clear outcome.

Hyperbolic is a AI compute platform for serverless open-model inference and on-demand GPU marketplace workloads. Testing and serving open text, image, audio, and vision-language models through serverless APIs, or renting GPU capacity for controlled model and compute workloads. This guide narrows that broad capability into one repeatable outcome, with checkpoints that keep the source material and your judgment in the loop.

Before you begin

Set the boundary before the tool starts.

Choose one real task, identify who will use the result, and decide what evidence or test will make the result acceptable. Gather only the source material needed for that task. If the work contains confidential, personal, regulated, or client-owned information, confirm that the platform and account are approved before sharing it.

Troiana principle

AI should make the work easier to inspect. If the workflow removes the source, the owner, or the review step, redesign the workflow.

Step by step

A workflow you can repeat.

  1. 01

    Define the task, data class, quality, latency, modality, context, model license, region, retention, throughput, cost, and rollback requirements.

  2. 02

    Choose serverless inference for bounded API use or a rented GPU for controlled software and model workloads, documenting the different security responsibilities.

  3. 03

    Run a versioned benchmark with server-side credentials, representative inputs, constrained outputs, usage logging, and no automatic consequential actions.

  4. 04

    Review quality, safety, latency, failure, privacy path, license, and total cost, then pin the chosen model or image, monitor it, and retain a tested fallback.

Working standard

What good use looks like.

  • State the outcome before the background.
  • Provide the real source material.
  • Review the result before expanding the task.

OpenAI compatibility covers interface shape, not model behavior, moderation, licensing, context, or reliability. Zero-retention serverless claims do not automatically govern software and data placed on a rented GPU. Treat marketplace machines as untrusted infrastructure until verified, use SSH keys and least privilege, encrypt and delete data, pin dependencies and models, control spend, and never expose credentials or management ports.

Official references

Check the current product documentation.

Features, plan limits, availability, and data controls change. These official pages are the starting points used for this collection.