INTELLECT-2 has been launched as the first decentralized Reinforcement Learning framework with 32 billion parameters, allowing anyone to contribute compute resources. It introduces a new asynchronous training paradigm that supports heterogeneous nodes and focuses on efficient validation and communication, while enabling the training of state-of-the-art reasoning models under controlled thinking budgets. The initiative aims to create a sovereign open-source AI ecosystem with mechanisms to ensure honest participation and verify contributions.

INTELLECT-2 is a groundbreaking 32 billion parameter model trained using a decentralized reinforcement learning framework called PRIME-RL, enabling fully asynchronous training across a global network of contributors. The model demonstrates significant improvements in reasoning tasks and is open-sourced to foster further research in decentralized AI training methodologies.