What question did this study set out to answer?

The central aim is to provide a comprehensive overview of large language models, including their development, applications, and challenges.

June 7, 2026Open Access

The Evolution, Capabilities, Limitations, and Future of Large Language Models (2026): A Comprehensive Review

Key Points

The central aim is to provide a comprehensive overview of large language models, including their development, applications, and challenges.
Survey of major model families including GPT, Claude, Gemini, Llama, Qwen, and DeepSeek.
Analysis of transformer architectures and scaling laws.
Discussion of technical challenges and governance considerations.
Identified key reasoning capabilities and performance in coding tasks.
Exposed limitations in educational applications and enterprise adoption.
Outlined emerging trends and future research opportunities through 2026.

Abstract

This preprint presents a comprehensive review of the evolution, capabilities, limitations, and future directions of Large Language Models (LLMs). The paper surveys transformer architectures, scaling laws, reasoning capabilities, coding performance, educational applications, enterprise adoption, multimodal systems, AI agents, and emerging trends through 2026. It synthesizes findings from major model families including GPT, Claude, Gemini, Llama, Qwen, and DeepSeek, while discussing technical challenges, governance considerations, and future research opportunities.

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