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Train a model using reinforcement learning on Prime Intellect’s infrastructure — no GPUs to manage.
Shared Hosted Training for LoRA runs will stop accepting new runs on October 5, 2026. Hosted Training is transitioning to dedicated runs. Existing LoRA adapters will remain downloadable and deployable until further notice.
The steps below cover the legacy shared LoRA service. Full fine-tuning (FFT) is currently in closed beta.

Prerequisites

1. Install the CLI and log in

2. Set up your workspace

This sets up your workspace with AGENTS.md, environments, and example training configs in configs/rl/.

3. Launch training

Pick one of the example configs and run it:
That’s it. Prime Intellect handles the GPU cluster, rollouts, and optimization. You’ll get a dashboard link in the output. You can also launch your coding agent (Claude, Cursor, OpenCode, etc.) and use it to manage your workspace and research workflows.

4. Monitor progress

Terminal:
Dashboard: Open the link from the previous step to see reward curves, rubric scores, and individual rollouts in real time.

Next steps

End-to-End Run

Detailed walkthrough with baseline evals, model selection, and result review.

Advanced Configs

Multi-environment training, online evals, and W&B integration.

Models & Pricing

Supported models and pricing details.

What is Lab?

Understand the full platform and how everything fits together.