The Best AI Models for Coding: Accuracy, Integration, and Developer Fit | The JetBrains AI Blog

AI coding models have become integral to modern software development, with large language models (LLMs) like GPT-5, Claude, and Gemini leading the way in providing code completion, refactoring, debugging, and documentation assistance. These models, as reported in the JetBrains Developer Ecosystem Report 2025, are chosen based on factors like accuracy, speed, integration, cost, and security, with developers prioritizing models that seamlessly integrate into their workflows. While proprietary cloud-based models offer ease and scalability, open-source or locally deployed models are favored for greater data control and customization. The report highlights the diverse preferences among developers, with individual developers focusing on usability and cost, while organizations emphasize compliance and governance. The choice of AI model is critical, depending on specific needs such as data privacy, integration with tools like JetBrains IDEs, and enterprise requirements. As AI capabilities continue to expand, these models are increasingly adopted across the industry, transforming how developers approach coding tasks.