| Paper | Documentation | Ask DeepWiki | 🤗 Models & Data | WeChat Group | AReaL (Ant Reasoning RL) is an open-source fully asynchronous reinforcement learning training system for large reasoning models developed at the RL Lab, Ant Research. Built upon the open-source project RealHF, we are fully committed to open-source by providing training details, data, and infrastructure required to reproduce results along with the model itself. AReaL aims to help everyone build their own AI agents easily and affordably....

News May 30, 2025: PromptCoT-Mamba released! Introducing an attention-free foundation model for reasoning tasks. Apr 11, 2025: PromptCoT-QwQ-32B model and its training data released, achieving new state-of-the-art results. Mar 7, 2025: PromptCoT project launched, including the problem generation model, distilled models (PromptCoT-DS series), and associated datasets. Overview This repository unifies two synergistic projects aimed at advancing the frontiers of mathematical and code reasoning in Large Language Models (LLMs): PromptCoT and PromptCoT-Mamba....

🤗 Hugging Face   |   🤖 ModelScope News [2025-06]:🎉 Add Ring-lite Model [2025-04]:🎉 Add Ring-lite-linear-preview Model Introduction Ring is a reasoning MoE LLM provided and open-sourced by InclusionAI, derived from Ling. We introduce Ring-lite-distill-preview, which has 16.8 billion parameters with 2.75 billion activated parameters. This model demonstrates impressive reasoning performance compared to existing models in the industry. Model Downloads You can download the following table to see the various parameters for your use case....