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Prime Inference

Run and scale your models through one reliable, OpenAI-compatible API. Call open models per token, or serve your own on dedicated capacity.

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AOverview

Serve open-source and custom models through the same stack that trains them.

  1. 01

    Model Library
    GLM, DeepSeek, Kimi and more, ready to call.

    View Catalog
  2. 02

    Serverless API
    Pay per token, with nothing to deploy or manage.

    Explore Models
  3. 03

    Dedicated Deployment
    Your own endpoint, sized to your traffic.

    Deploy a Model

1Model library

Access leading open-source models. Serve GLM, DeepSeek, Kimi and more through one API.

View Catalog
Read the Docs

2Serverless API

Serverless API. Call frontier open models per token through one OpenAI-compatible API.

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Prime Hosted

Run models directly on Prime infrastructure, with serving managed by our team for reliable, production-ready performance.

Explore Models
  1. 2.1Hosted and managed by Prime
  2. 2.2Production-ready model serving
  3. 2.3OpenAI-compatible API
  4. 2.4No infrastructure to deploy or maintain

Prime Gateway

Access leading third-party models through one OpenAI-compatible API, with a simple and unified integration.

Read the Docs
  1. 2.5Access to third-party models
  2. 2.6One API for multiple providers
  3. 2.7Simple model switching
  4. 2.8Pay-per-token access

3Dedicated Deployment

Scale beyond serverless. Dedicated endpoints on reserved compute for open models; built for trillions of tokens with an SLA of 99.9% uptime.

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Step 1

Choose your model

Bring an open model, your own fine-tune, or a model trained with Model Factory.

Step 2

Configure your capacity

Select the hardware and serving configuration that match your workload.

Step 3

Launch your endpoint

Prime provisions your endpoint on dedicated hardware, backed by a 99.9% uptime SLA.

Step 4

Scale with demand

Add capacity as traffic grows, from millions to trillions of tokens.

Talk to our Team

Our engineers size the deployment with you.

Prime Intellect will handle your data pursuant to our Privacy Policy.

Your data. Your model. Your edge. Built for the most security-conscious teams in AI, enterprise and the public sector.

Data never leaves your perimeter
Choose serverless or a VPC deployment based on the control you need.
Full access and audit
Role-based access control, audit logs on every dispatch, lifecycle automation for checkpoints, datasets and artifacts.
You own the intelligence
The model is yours. You decide what trains, what deploys and what memory is retained. Opt out of training any time.

Questions.

When should I use a Dedicated Deployment?

Use a Dedicated Deployment when you need predictable latency, a 99.9% uptime SLA, custom model support, or serving capacity designed around your traffic.

Can I deploy models trained with Model Factory?

Yes. Deploy an open model, your own fine-tune or a model trained with Model Factory to a dedicated endpoint on reserved hardware, backed by a 99.9% uptime SLA. Model Factory runs are the fastest path from training to production.

Do I need to manage the infrastructure?

No. On the Serverless API there is nothing to deploy. For a Dedicated Deployment, Prime provisions the hardware and our team manages the serving.

Is the API OpenAI-compatible?

Yes. Point any OpenAI SDK at Prime Inference's endpoint with your API key, and switch models by changing the model name.

How is inference priced?

The Serverless API, Prime Gateway included, is billed per token. Dedicated capacity for your own models is sized and priced with our team.