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Prime Intellect

The Open Superintelligence Stack

About Prime Intellect

Prime Intellect provides a platform to train, evaluate, and deploy AI models on an integrated compute, training, inference, and sandbox stack. It targets teams building and deploying custom AI workloads across research, development, and production environments.

The platform supports end-to-end workflows from training specialist models to hosting evaluations, observability, sandboxes, and production-grade inference. It integrates model factory deployments with scalable serving and dedicated clusters for enterprise needs.

Users can manage hosted training, evaluations, and traceability of model runs, while accessing open models and a capability-rich serving stack. The system emphasizes open-source components and open models.

Prime Intellect aims to offer a unified stack that covers post-training, inference, and compute within a security-conscious perimeter, with data handling and access controls designed for enterprise and public sector use.

Use cases

  • Train specialist models for tasks, then reinforce with RL against custom rewards.
  • Evaluate and iterate on models with hosted evaluations and traceability.
  • Scale production-grade inference for open and custom models.

Key features

  • Train and deploy custom AI models on an integrated compute, training, and inference stack.
  • Build and deploy your own custom models on one platform across post-training, inference, and compute.
  • Train models with reinforcement learning on managed Prime-RL, our open-source trainer, using hosted compute and sandboxes.
  • Create hosted evaluations for benchmarking model performance.
  • Scale thousands of microVM sandboxes with native Docker and full RL support.
  • Deploy production-grade inference with Serverless API and Prime Hosted for open-model serving.
  • Dedicated deployments offer production-grade capacity with private routing and reliability.

Pros and cons

Pros

Integrated stack for training, evaluation, and deployment.
Open-source RL framework and hosted training.

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