This page showcases the diverse collection of machine learning models and datasets provided by Arcee AI on Hugging Face. The collections include the advanced Trinity family of models, such as Trinity-Large-Thinking and Trinity-Mini, designed for various text generation tasks. Additionally, the repository features specialized datasets like Teacher Logits for distillation, the AFM 4.5B series, and various quantized flagship models like Virtuoso and SuperNova. These resources cater to researchers and developers looking for high-performance, specialized AI models ranging from small-scale nano versions to massive 399B parameter models, supporting tasks like feature extraction and text generation.
Arcee AI is a US-based Open Intelligence Lab focused on developing frontier, open-weight models that provide high performance without the massive costs of closed-source alternatives. Through their Trinity model series, they offer scalable architectures designed for continuous improvement using online reinforcement learning. The lab emphasizes rapid iteration and practical utility, releasing significant models like Trinity-Large-Thinking to support complex, long-horizon agents and multi-turn tool calling. By prioritizing open weights and efficient scaling, Arcee AI aims to lead the next wave of agentic and reasoning-capable artificial intelligence.
