Researchers have introduced Kimi k1.5, a next-generation multimodal large language model (LLM) that utilizes reinforcement learning (RL) to enhance scalable multimodal reasoning. This development aims to improve benchmark performance in AI applications. In a related advancement, DeepSeek’s R1 model demonstrates the capability to learn reasoning through pure RL, albeit with high computational costs. Both models represent significant strides in the integration of RL with LLMs, focusing on improving reasoning capabilities and performance metrics in artificial intelligence.