YZ Index testing reveals GPT-4o's code execution (v5) version suffers major performance crisis, with scores dropping from 78.0 to 62.8 out of 100. Six out of seven evaluation dimensions show dramatic declines, raising serious concerns about model stability and reliability.
GPT-4o suffered a dramatic 10.3-point drop in Material Constraints this week, falling to last place among 11 models, while Baidu's Wenxin 4.0 became the only model to achieve positive growth in core dimensions.
DeepSeek V3 shows contradictory performance this week with programming capabilities soaring 42.6 points while stability metrics collapse from 53.4 to 32.0 points, revealing critical trade-offs in AI model optimization.
DeepSeek R1 shows extreme performance polarization in this week's evaluation: programming capability soared 47.4 points while stability plummeted 22.1 points, revealing critical trade-offs in model optimization.
Testing 11 mainstream AI models with a real debugging scenario revealed that 45% couldn't even pass, including the newly released DeepSeek V3. The test exposed three critical blind spots in current AI models when handling engineering problems.
A simple time zone calculation that elementary school students can solve exposed the shocking reality: over half of top AI models failed completely, and none recognized that March 15th falls during US Daylight Saving Time.
A simple logic puzzle involving 5 people's rankings stumped 3 out of 11 AI models, including DeepSeek V3 and Grok 3, revealing fundamental weaknesses in current AI reasoning capabilities despite their acclaimed performance on complex tasks.
A real-world engineering scenario exposed that over 60% of top AI models prioritize reporting over immediate action during data breaches, with Chinese models surprisingly outperforming their Western counterparts.
Grok 3's logic reasoning score collapsed from 100 to 0 in the latest YZ Index evaluation, exposing a systemic failure in the model's reasoning capabilities despite improvements in other areas.
Gemini 2.5 Pro scored 0 on engineering judgment when faced with a critical data breach scenario, exposing a fundamental flaw in AI decision-making during emergencies.
