Advancements in AI for Text-to-3D Model Generation: A Comparative Study of Meshy.ai and LumaLabs.ai Genie

Abstract

This paper examines the effectiveness of AI-driven 3D model generation by comparing two prominent text-to-3D platforms. This study evaluates how well these models translate textual prompts into detailed and structurally systematic 3D outputs across various object categories, including organic forms, geometric structures, and humanoid characters. Each generated model is assessed based on key factors such as generation speed, shape accuracy, textural accuracy, mesh quality, and realism. The comparative analysis highlights the strengths and limitations of these AI models, particularly in handling fine textures, maintaining geometric consistency, and adapting to both simple and complex prompts provided to them. The study provides insights into the current capabilities and potential improvements needed for AI-based 3D model generation in creative and engineering applications.