Spqr.spqralive.18.var «FHD • 720p»

: It is the first method to allow 3-4 bit quantization with almost no measurable loss in perplexity compared to the 16-bit baseline.

: Optimization for specific GPU architectures (e.g., NVIDIA Ampere or Hopper). Conclusion SPQR.SPQRAlive.18.var

SpQR represents a shift from uniform quantization to . By treating weights differently based on their importance, it bridges the gap between massive model scales and accessible hardware. : It is the first method to allow

: Despite the hybrid structure, optimized kernels allow for faster inference compared to uncompressed models due to reduced memory bandwidth bottlenecks. 4. Implementation (SPQRAlive.18.var) By treating weights differently based on their importance,

: It uses a Hessian-based regularizer to identify which weights are most sensitive to quantization.

: These sensitive weights (usually less than 1% of the total) are extracted and stored in their original 16-bit precision.