Large reasoning models (LRMs) build on large language models, but add elements that emulate aspects of thinking especially chain of thought reasoning and self-reflection. They substantially outperform LLMs on logical, mathematical and coding problems. However, research from Apple showed that LRMs (as available in 2025) tended to fail dramatically as problem complexity increased.