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Zonghang Li

2 accepted papers

2026

Prima.cpp: Fast 30-70B LLM Inference on Heterogeneous and Low-Resource Home Clusters

ICLR 2026poster

On-device inference offers privacy, offline use, and instant response, but consumer hardware restricts large language models (LLMs) to low throughput and capability. To overcome this challenge, we present prima.cpp, a distributed on-device inference system that runs 30-70B LLMs on consumer home clus…

Cited by 0SourcecodeScholar
2026

Tequila: Deadzone-free Ternary Quantization for Large Language Models

ICLR 2026poster

Quantization techniques are essential for the deployment of Large Language Models (LLMs) on edge devices. However, prevailing methods often rely on mixed-precision multiplication that lacks efficient hardware support, making it not feasible. Ternary weight quantization addresses this by constraining…

Cited by 0SourcecodeScholar