Assessing Frontier LLMs in Solving Game Development Problems: Preliminary Findings Across Three Game Engines
This paper evaluates three frontier LLMs (ChatGPT-4o, o3, and Gemini 2.5 Pro) against expert-rated human answers for 30 technical questions collected from online Q&A forums about three popular game engines: Unreal, Unity, and Godot. Our results reveal significant performance variance, with o3 demonstrating superior capabilities over Gemini 2.5 Pro and ChatGPT-4o. A primary weakness identified across all models was response completeness, where AI-generated answers often lacked the comprehensive detail of the human baseline. These findings suggest that although LLMs are powerful assistants, they are not yet a substitute for human expertise in engine-based game development tasks.
Authors
- Nabor C. Mendonça (ORCID: https://orcid.org/0000-0002-2972-9423)
- Maria Andréia Formico Rodriguês (ORCID: https://orcid.org/0000-0003-1181-2971)
- T. Vasconcelos (ORCID: https://orcid.org/0000-0001-6911-6309)
- Guadalupe Prado Saldanha Ribeiro (ORCID: https://orcid.org/0009-0005-2923-1501)
- Adams Amaral de Castro Filho
Publication Details
- Published
- 2025-09-18
- DOI
- https://doi.org/10.5753/se4games.2025.14869
- Primary Topic
- Digital Games and Media
- Type
- article
- Field-Weighted Citation Impact
- 0.00