AI Models Produce Conflicting 2026 Market Forecasts

In early 2026, a finance professional asked three large language models—ChatGPT (5.2), Gemini (3) and Claude (Sonnet 4.5)—for point forecasts on ten market targets including the S&P 500, ten-year Treasury yield, Brent crude, bitcoin and gold. The models produced divergent numerical estimates (for example, S&P 7,700 vs 6,800; gold $4,500 vs $3,100), showed internal inconsistencies, and initially resisted point forecasts, suggesting limited reliability for precise market timing.