Oct 15, 2026 · Artificial Intelligence

TB-Scale LLM Inference: Zero-Redundancy Weight Deployment & 80% KV Cache Compression

Baidu Baige presents extreme VRAM optimization for TB-scale model inference: zero-redundancy weight deployment via DP Attn-sharding (releasing 16–30 GiB/card) and full-route CPP (50% throughput gain), plus KV Cache compression via LU-KV (80% reduction, 0.52% accuracy loss), Draft SWA, and PD handshake optimization (20% VRAM release).

KV Cache CompressionLLM inferenceLU-KV

0 likes · 27 min read

TB-Scale LLM Inference: Zero-Redundancy Weight Deployment & 80% KV Cache Compression

Zero-Redundancy Deployment

TB-Scale LLM Inference: Zero-Redundancy Weight Deployment & 80% KV Cache Compression