By 2026, Large Language Models Expected to Break Through in Training and Memory

CICC analysts forecast significant changes in the field of large language models (LLMs) by 2026. In 2025, we saw considerable progress in this area, particularly in reasoning, programming, agentic systems and multimodality. However, models still struggle with stability and a tendency to hallucinate.

A breakthrough is expected next year in several key areas. First, reinforcement learning, which should let models adapt better to complex tasks and make better decisions. Model memory is also expected to improve, allowing models to process more information and better retain prior experience. Finally, context optimization should let models use the available information more efficiently to solve tasks.

These improvements will have several important consequences. First, models will be better at tasks that require long chains of reasoning. Second, there will be a shift from text-based interaction to more natural multimodal approaches that combine different types of data, such as text, images and audio. Ultimately, these improvements will bring us closer to the long-term goal: artificial general intelligence (AGI).

The forecast highlights how fast LLMs are developing. Companies and researchers around the world are actively working to improve these models, and we can expect new breakthroughs in the coming years. This may lead to significant changes in a range of industries, from automation to healthcare.

For users, this means smarter and more useful tools that can handle complex tasks and interact with the world more naturally. For the industry, it opens new opportunities for innovation and for new products and services. In the long run, the development of LLMs will continue to have a profound impact on our lives.