ORCA Benchmark Reveals Major Flaws in AI's Everyday Math Capabilities

ORCA Benchmark Uncovers Critical Deficiencies in AI Math

In a groundbreaking study released by Omni Calculator, the ORCA (Omni Research on Calculation in AI) Benchmark has revealed alarming statistics about the reliability of artificial intelligence (AI) in handling everyday math problems. Evaluating five leading AI models against 500 realistic scenarios, the results indicate that none of these systems are capable of delivering correct answers consistently. With an accuracy cap of just 63% for the top performer, Gemini 2.5 Flash, these findings call into question the trustworthiness of AI for basic arithmetic tasks.

Findings of the Study

The researchers at Omni Calculator discovered that nearly 40% of responses from leading AI chatbots were incorrect for common tasks such as splitting a bill or forecasting investment returns. The study became increasingly relevant as reliance on AI for routine calculations grows among everyday users.

"When we talk about mathematical calculations in AIs, it’s important to recognize they do not function like traditional calculators," explained Joanna Śmietańska-Nowak, the lead author of the study and a PhD holder in Physics with extensive knowledge in Machine Learning.

The report indicates that the most frequent areas of failure stem not from complex problems but from basic arithmetic errors and rounding mistakes. This highlights a fundamental issue: these AI models are primarily pattern recognizers trained on text rather than mathematical rule-based systems.

Key Insights

1. Performance of Different Models: None of the five tested models, including ChatGPT-5, Gemini 2.5 Flash, Claude 4.5 Sonnet, DeepSeek V3.2, and Grok-4, achieved an accuracy level higher than 63%. While some excelled in particular domains, the overall performance was subpar.
2. Nature of Errors: Mechanical errors accounted for 68% of mistakes, with calculation errors making up 33% and precision/rounding issues comprising 35%. This indicates serious drawbacks in the computational processes of AIs.
3. Variability of Accuracy: The results varied significantly depending on the subject area. For instance, in Finance & Economics, some models achieved accuracy levels ranging from 70% to 80%. Conversely, in Physics and Health & Sports, accuracy plummeted below 40% due to complex formula translations required.

Implications for Users

These findings underline an essential guideline for AI users: Always verify AI calculations. In critical scenarios involving significant real-world impact—like medical prescriptions, loan calculations, or recipe conversions—output from any AI should always be cross-checked with a reliable calculator.

With technology rapidly evolving, the findings of the ORCA Benchmark serve as a stark reminder of the limitations of current AI systems, particularly when it comes to basic numeric tasks. As users become more dependent on these technologies, understanding their strengths and weaknesses becomes increasingly crucial.

To delve deeper into these findings, you can download the full report from Omni Calculator’s official website. They have built a robust array of tools designed to solve daily problems for over ten years, aiming to make calculations clearer and more accurate for everyone.