Recent comparisons between two leading artificial intelligence systems, ChatGPT and Gemini, reveal that ChatGPT currently outperforms Gemini in several key benchmarks. As the field of AI rapidly evolves, measuring the effectiveness of these systems has become paramount for users and developers alike.
Understanding Benchmark Performance
Evaluating the capabilities of AI systems is a complex task, especially considering the rapid advancements in technology. In December 2025, speculation arose regarding whether OpenAI was falling behind in the AI competition. Just days later, the release of ChatGPT-5.2 demonstrated a significant leap in performance, allowing it to reclaim its position at the forefront of AI development.
The comparative analysis of ChatGPT and Gemini often involves subjective assessments, but a more objective approach focuses on standardized benchmarks that test various aspects of AI, such as reasoning, logic, and problem-solving. For this discussion, we will examine three benchmarks where ChatGPT shows a notable advantage.
The first benchmark, known as GPQA Diamond, aims to evaluate PhD-level reasoning in disciplines like physics, chemistry, and biology. This benchmark, which stands for Google-Proof Questions and Answers, includes complex questions requiring intricate reasoning rather than simple recall. ChatGPT-5.2 achieved a score of 92.4%, marginally ahead of Gemini 3 Pro, which scored 91.9%. In contrast, a PhD graduate is expected to score around 65%, while non-expert individuals typically score about 34%.
Software Engineering and Visual Reasoning
Another critical benchmark is the SWE-Bench Pro (Private Dataset), which assesses an AI’s ability to resolve real-world software engineering tasks sourced from GitHub. This benchmark presents challenges that require a deep understanding of complex codebases and the ability to interpret bug reports accurately. ChatGPT-5.2 resolved approximately 24% of the issues, compared to Gemini’s 18%. While these figures may appear modest, it is essential to recognize that this particular test is designed to be especially challenging.
Additionally, the ARC-AGI-2 test measures visual reasoning and abstract problem-solving capabilities. This benchmark, updated in March 2025, challenges AI to identify patterns based on minimal data. ChatGPT-5.2 Pro scored 54.2%, whereas Gemini 3 Pro managed only 31.1%. This stark difference illustrates not only ChatGPT’s superiority in this area but also highlights the ongoing challenges AI faces in replicating human-like reasoning.
While these benchmarks indicate areas where ChatGPT excels, it is essential to note that AI performance is continually evolving. The results discussed here are based on the most current versions of the systems, specifically ChatGPT-5.2 and Gemini 3. As new iterations are released, these scores may shift, and user preferences may vary according to different benchmarks.
In conclusion, while both ChatGPT and Gemini have their strengths, current data suggests that ChatGPT holds an edge in critical areas of reasoning, problem-solving, and abstract thinking. As AI technology progresses, ongoing evaluations and comparisons will be necessary to provide users with the most accurate insights into these powerful systems.
