Popular LLMs share strengths and weaknesses when it comes to creating code

Increasing pressure to build and launch applications quickly has seen a rise in the use of AI to generate code. New analysis from Sonar, looking at the quality and security of software code produced by top Large Language Models (LLMs), finds significant strengths as well as material challenges across the tested models. The study used a proprietary analysis framework for assessing LLM-generated code, tasking the LLMs with over 4,400 Java programming assignments. The LLMs evaluated in the study include Anthropic's Claude Sonnet 4 and 3.7, OpenAI's GPT-4o, Meta's Llama-3.2-vision:90b, and OpenCoder-8B. 'The rapid adoption of LLMs for writing code is… [Continue Reading]