The author discusses how continuously scaling data and model size can improve model intelligence, especially for large models like Qwen2.5-Max, a MoE model pre-trained on over 20 trillion tokens. Qwen2.5-Max outperforms DeepSeek V3 in various benchmarks, showcasing its prowess in chat and coding applications. The API for Qwen2.5-Max is available through Alibaba Cloud, allowing users to interact with the model directly or use artifacts and search features. The future work focuses on enhancing large language models through scaled reinforcement learning to exceed human intelligence. This groundbreaking research opens up new possibilities for exploring uncharted territories of knowledge and understanding.
https://qwenlm.github.io/blog/qwen2.5-max/