Qwen2.5-VL-72B-Instruct

Quality drops 10 points with slower response times and factual weakness

Qwen2.5-VL-72B-Instruct experienced a notable decline in this benchmark window, with overall quality falling from 98.8 to 88.8 points while latency increased by 37 percent to 8.9 seconds at the median. The model demonstrates exceptional strength in multilingual and reasoning tasks, both scoring perfect 100s, and maintains outstanding creative capabilities at 98 points. However, factual accuracy emerged as a significant weakness, scoring just 57 points and representing a substantial gap in the model's performance profile. The previous window included coding benchmarks where the model scored 98, but this category was not tested in the current window, making direct comparison incomplete. Thelatency increase from 6.5 to 8.9 seconds suggests either infrastructure changes or increased processing complexity. Despite the quality decline, the model retains strong capabilities in three of four tested categories. Users should be aware of the factual accuracy limitations when deploying this model for knowledge-intensive applications, while the model remains well-suited for creative, multilingual, and reasoning-heavy workloads where it continues to excel.