Quant Audit reveals leaderboard scores

Short summary

Leaderboard scores don't predict real-world agent performance—a model's tool-calling accuracy can degrade significantly with lower quantization levels. The Quant Audit approach measures performance drop-off across compression levels to find the largest quantization that retains reasoning integrity, not just the smallest that fits in VRAM. Stop optimizing for load time and start measuring what matters for your application's capabilities.

• •Leaderboard rankings are poor proxies for agent performance under quantization
• •Measure performance degradation across compression levels to find optimal balance
• •Prioritize reasoning integrity over VRAM footprint in quantization decisions

Generated with AI, which can make mistakes.