86% of all LLM usage is driven by ChatGPT

ChatGPT remains the most widely used LLM among New Relic customers, making up over 86% of all tokens processed. Developers and enterprises are shifting to OpenAI’s latest models, such as GPT-4o and GPT-4o mini, even when more affordable alternatives are available.

Why ChatGPT dominates

Speed, reliability, and enterprise readiness are driving ChatGPT’s dominance. Many organizations prefer deploying proven models rather than investing time and resources into training or fine-tuning their own. That said, monitoring remains essential, even for the most trusted models. Teams need to track usage, benchmark performance, and detect anomalies to manage costs and maintain reliability.

Most companies are still in early AI adoption phases, so they lean on generalist models. However, the data shows that developers are also testing a wide variety of models, including domain-specific and task-specific, although at a smaller scale.

“AI is moving from innovation labs and pilot programs into the core of business operations,” said Nic Benders, Chief Technical Strategist at New Relic.

Developers shift to latest ChatGPT versions

Enterprises are quick to embrace OpenAI’s updates. Since April, New Relic users have shifted from ChatGPT-3.5 Turbo to the newer ChatGPT-4.1 mini, prioritizing better performance and features over cost.

While ChatGPT remains on top, data shows rising model diversity. Meta’s Llama emerged as the second-most-used model, and overall, the number of unique models in use across AI apps rose 92% in Q1 2025. Developers are clearly exploring alternatives, including open-source and specialized solutions, even if at smaller scale.

AI monitoring adoption grows

AI adoption is driving demand for monitoring. As AI becomes operational, observability tools must go beyond LLMs to cover the full AI stack. Without monitoring, companies face risks like performance degradation, security gaps, and uncontrolled costs.

That could slow the pace of AI innovation and can undermine confidence in scaling AI.

Python dominates, but Java follows

With the most momentum, support, and tooling, the data shows Python continues to dominate AI applications, with customer adoption growing nearly 45% since last quarter.

In terms of both the scale of requests and customer adoption, Node.js followed Python. However, Java usage has grown rapidly at 34% since last quarter, signaling more production-grade, Java-based LLM applications are to come from large enterprises.