Qwen3-32B

Qwen3-32B shows 34% latency gain but factual score plummets to 35

The current benchmark window reveals a mixed performance picture for Qwen3-32B deployed on OVH AI Endpoints. While latency has improved substantially with p50 dropping from 24595ms to 16206ms, representing a 34% speed increase, the overall quality score has declined slightly from 73.4 to 72.3. The most concerning development is the dramatic collapse in factual performance, now scoring just 35 compared to the previous window where factual capabilities weren't measured but coding achieved 94. This suggests a significant regression in knowledge accuracy and reliability. On the positive side, multilingual capabilities have strengthened from 86 to 95, and reasoning performance stands strong at 83. Creative writing has rebounded impressively from 40 to 76, reversing the sharp decline noted in the previous period. The model appears to have shifted its strengths, excelling at multilingual tasks and creative generation while struggling with factual accuracy. Users requiring precise factual responses should exercise caution, while those focused on creative multilingual applications may find the current configuration more suitable. The latency improvements make the service more responsive overall, but the factual performance gap represents a critical weakness for general-purpose deployments.