SigmaCore Study: LLMs Hit 63.5% Precision on Financial Math
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Alpharetta – November 03, 2026 -- Generative large language models (LLMs) computing financial figures directly achieved an exact precision rate of 63.5%, against 100% for SigmaCore.ai's deterministic Eliza engine, according to a benchmark study released by the Georgia-based AI developer.
Code execution lifts LLM accuracy to 94.7% but adds formula-selection risk
The study, titled "Can We Trust the AI to Do the Math?", covered 3,400 financial test cases. LLMs with code execution enabled reached 94.7% exact precision.
The company says the augmented models reduced minor arithmetic slips but introduced logic errors, because they picked the wrong formula. In two retail financial scenarios, accuracy fell to 18% with code tools active. The models generated flawed formulas "with high structural confidence," per the study.