The State Of LLMs 2025: Progress, Problems, and Predictions
Published:Dec 30, 2025 12:22
•1 min read
•Sebastian Raschka
Analysis
This article provides a concise overview of a 2025 review of large language models. It highlights key aspects such as recent advancements (DeepSeek R1, RLVR), inference-time scaling, benchmarking, architectures, and predictions for the following year. The focus is on summarizing the state of the field.
Key Takeaways
- •Covers the state of LLMs in 2025.
- •Mentions specific models and advancements (DeepSeek R1, RLVR).
- •Includes topics like inference-time scaling, benchmarks, and architectures.
- •Provides predictions for 2026.
Reference
“N/A”