LLM Developments 2025: How Efficiency and RLVR Broke the Scaling Obsession

★The State of LLMs in 2025: Technical Evolution, Practical Reflections, and Future Paths★ What were the most significant developments in large language models during 2025, and how do they reshape our approach to AI development? 2025 marked a pivotal shift in language model progress. Rather than relying solely on scaling model parameters, the field advanced through sophisticated post-training methods like RLVR (Reinforcement Learning with Verifiable Rewards), inference-time scaling that allows models to “think longer,” and architectural efficiency gains. The year also exposed critical flaws in public benchmarking while validating that AI augmentation, not replacement, defines the future of technical work. …