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ZSE: Ultra Memory-Efficient LLM Inference Engine for Running Large Models on Consumer GPUs

By

zyoralabs

3mo ago· 9 min readenCode

Summary

ZSE (Z Server Engine) is an ultra memory-efficient LLM inference engine with native INT4 CUDA kernels that enables running large language models on consumer-grade GPUs. It allows running 32B models on 24GB GPUs and 7B models on 8GB GPUs, featuring fast cold starts and single-file deployment. The latest version v1.4.1 adds Model Hub and Pull Commands functionality, and it supports training 7B models on 8GB GPUs and 70B models on 48GB GPUs. The article includes verified benchmarks showing performance metrics for various models like Qwen 7B and Qwen 14B on H200 GPUs.

Key quotes

· 5 pulled
Ultra memory-efficient LLM inference engine with native INT4 CUDA kernels.
Run 32B models on 24GB GPUs. Run 7B models on 8GB GPUs. Fast cold starts, single-file deployment.
Train 7B models on 8GB GPUs. Train 70B models on 48GB GPUs.
ZSE Custom Kernel (Default)
Qwen 7B: 5.57 GB file size, 5.67 GB VRAM, 37.2 tok/s speed, 5.7s cold start on H200 GPU
Snippet from the RSS feed
The inference engine the open-source world built for itself. - Zyora-Dev/zse

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