More compute put to work
You choose the model and the product option. HIPS coordinates the work. Providers decide what capacity they contribute.
We are inviting early-access interest while we develop the platform.
General notes
Useful GPU capacity is spread across personal computers and data centers. HIPS is building a centrally managed inference marketplace that connects that supply with businesses and developers who want to run models.
The steps
- 01
Start with the model
Select a supported open-weight model or bring compatible weights of your own. The model’s architecture, memory needs, and execution requirements determine which resources can run it.
- 02
Apply your choices
Pricing mode, execution-pool choice, data-use policy, and any supported region requirement become part of the job’s requirements. They must continue to apply if work is retried or capacity changes.
- 03
Assign compatible capacity
HIPS will route work to eligible GPUs. Shared inference can use available personal GPU capacity. Always-on deployments use supply appropriate for keeping models resident continuously.
- 04
Return the result and account for the work
Results return through the service. Usage is recorded in the model’s billing units and deducted from the account’s credit balance, with the applicable price visible in the usage record.
Batch jobs and prompt caching
- 1
Batch jobs
For work that does not need an answer right away, batch jobs will let you send many requests at once in one file, in the OpenAI-style batch format. HIPS will run them as capacity becomes free, within a window you choose from 24 hours to 7 days, and tell you when they are done. A batch will cost half the on-demand rate of the same model. No completion time is promised: requests still unfinished when the window closes will come back as expired and will not be charged.
Docs: Batch jobs - 2
Prompt caching
When requests begin with the same text, such as a long system prompt or a shared document, HIPS will reuse that work automatically from a cache kept for your workspace alone. Cached input will be billed at a lower rate than other input, and writing to the cache will cost nothing.
Docs: Prompt caching
A coordinated network
Providers supply GPUs; HIPS operates the service around them. This gives customers one place to access models, manage deployments, and understand usage, while providers control their own participation.