Skip to content
HIPS
  • Earn with your GPU
  • Pricing
  • Docs
Sign inJoin early access
01 GAMING GPU

AI inference for builders.

A distributed GPU network, managed by HIPS.

We’re bringing available GPUs together to make AI inference more affordable. Run open-weight models and models of your own through one API, with HIPS managing the network behind your application.

Join early access
How it works

We are inviting early-access interest while we develop the platform.

02RECEIPT, COLLECTED EDITION
Drawing: A receipt bound in three volumes at one end of a long shelf, the top one open at its contents, which end at usage limit reached, the usage-limit slip running out from under its open cover as a bookmark, HiP standing at the shelf's free end as a bookend

More room in your AI budget

More of your AI budget should go toward what you are building. HIPS brings available GPU capacity together around that goal: useful inference with room to grow.

Bring inference costs into the design of your product. Choose the model and capacity that fit the work, with a clear view of what each request costs.

03CONNECTION DETAIL (SECTION A-A)
Drawing: A code window whose endpoint, key and model settings are struck through and set again to the HIPS base URL, API key and model, its cable into a coupling cut in section, a key turned in the nut, the language-model module on its stand clamped on the socket, and a request riding to the HIPS endpoint and back

Build with HIPS

Familiar code. A new inference network.

For open-weight language models, we’re designing HIPS to work with familiar coding tools and supported provider-style client SDKs, starting with OpenAI-style integrations. Connect your client with a HIPS API key, base URL, and supported model ID, and let HIPS coordinate the GPU capacity behind each request.

A HIPS API key, base URL, and supported model or deployment ID are the starting configuration. Explore the developer previews and see what needs checking when moving an existing integration.

Developer hubMigrate to HIPS
04MODEL TYPES, EXPLODED (VIEW C)
Drawing: A builder's laptop cabled into the HIPS endpoint, where a model cube is exploded into a row of types on a shelf: language, image, audio, video and classifier, with HiP queuing at the end of the row, classified by the classifier as a block, blue, and the route from the endpoint on to a suitable GPU

Run the models your application needs

From language and images to audio, video, and specialist tasks, we’re bringing a curated range of open-weight models into one inference platform.

Explore model capabilities, test an idea in the playground, and connect through an API. Follow the same path from your first experiment to an application people use.

Explore model capabilities
05OWN MODELS, DOCKED
Drawing: A model repository's sheet with its pinned revision lists its files; they run down to a gate where the weight files pass into an open crate and a code file is turned back; the crate is sealed, stencilled weights: yours, and seats in the dock on the socket beside the HIPS SDK plate, where an AI job card runs on it, HiP standing on the plate's far end

Bring your own model

Already trained a model for your product or business? We’re building a way to run it through HIPS.

Bring the model you have trained for your product, then choose the execution option that fits its workload and your requirements.

Deploy your model

Your model weights will never be used to train other models. Request inputs and generated outputs follow your plan’s separate data-use policy.

06ALWAYS-ON CAPACITY (DETAIL G)
Drawing: A data hall where a model rides into one rack, which is held ready, always-on marked on the floor in front of it, under a duty trace that stays high all the time while requests come and go

Keep a model loaded when it matters

Keep a model loaded between requests with always-on GPU capacity, supplied by providers suited to continuous allocation.

Choose an hourly allocation for work that needs a model to remain resident, and follow the deployment and its cost in the Console.

Always-on GPU capacity
07GENERAL ARRANGEMENT
Drawing: A builder's laptop, figure 1, the AI app, beside a stack of receipts, the HIPS station and the GPU owners' machines in one street, a personal computer and a taller data-center rack, a request running through the station from the laptop to a port on the personal computer and a second lead along the floor to the rack, inside a field of personal computers and data-center racks

Make more of the compute already here

Good ideas need somewhere to run. Useful compute is already out there, in personal computers and data centers. HIPS is bringing it into an AI inference marketplace, connecting people who need model results with people who have GPU time to offer.

Providers choose when they contribute capacity. HIPS coordinates the network, matching supported workloads to suitable GPUs and the policies attached to each request.

See how the network works

Understand what you use

Start with usage-based inference, choose always-on capacity for a resident model, or explore monthly plans with included credits.

Explore plans

Have a GPU that spends time idle

We’re building a way for people and businesses to contribute GPU capacity and earn when it is used.

Register GPU interest

Questions before joining

A

Is HIPS available to use today?

We are inviting early-access interest while we develop the platform. Joining the list does not create an operating inference account or guarantee an invitation date.

Rev A
B

Will HIPS support my model?

We intend to support selected open-weight models and customer-owned models across several modalities. Supported architectures, hardware requirements, and the launch catalog will be announced as they are confirmed.

Rev B
C

Is the network decentralized?

The GPU supply is distributed. HIPS centrally manages how work is assigned and how the service is operated.

Rev C
D

Will you train other models with my weights?

No. Customer-owned model weights will never be used to train other models on any plan. Request inputs and generated outputs are a separate category and may be used for training on Free/PAYG and the lower paid plan.

Rev D
E

Do I need a wallet to join early access?

No. You do not need a wallet or payment method to register interest.

Rev E
F

What happens to HIPS Payments?

HIPS Payments continues as a separate division. Existing payments customers can use the HIPS Payments path for their product and support needs. Go to HIPS Payments

Rev F
Contact HIPS

Help shape what comes next

Tell us you’re interested in HIPS. We’ll send updates about early-access availability and the capabilities we’re preparing.

Join early access

Product

  • Inference
  • Models
  • Deploy your model
  • Always-on GPU capacity
  • How it works
  • Use cases
  • Pricing

Developer

  • Docs
  • Quickstart preview
  • Migrate to HIPS
  • HIPS SDK
  • Batch jobs
  • API reference

Provider

  • Earn with your GPU
  • Register GPU interest
  • Download for Mac
  • Download for Windows
  • Download for Linux

Resource

  • Security and Data
  • Resources
  • llms.txt

Company

  • About
  • Contact
  • Affiliate program
  • HIPS Payments

Legal

  • Legal
  • Consumer Health Data Privacy Policy
  • Report content
  • Cookie settings

Support

  • Contact HIPS
  • Looking for payments support?

HIPS. AI inference for builders.

hips.com

Hyperscale Inference Processing Systems OÜ