club-3090 / qengine / RedHatAI/Qwen3.8-27B-INT4

Reddit r/LocalLLaMA Models

Summary

A user reports that running the quantized RedHatAI/Qwen3.8-27B-INT4 model with QEngine on dual RTX 3090s is significantly faster than their previous FP8 vLLM setup, sharing links to the config and model repo.

This thing https://github.com/noonghunna/club-3090/blob/master/models/qwen3.8-27b/qengine/compose/dual/redhat-int4/mtp.yml https://github.com/bpx03/QEngine https://huggingface.co/RedHatAI/Qwen3.8-27B-INT4#accuracy i'm on 2x3090, and dual VLLM qwen3.8-27b fp8 was my daily. some of my buddies were yakkin about local AI so i figured i'd try another preset. HOLY HELL is it way faster than fp8! (i mean of course it will be) but its SIGNIFICANTLY faster than i remember the last int4 i tried when qwen3.8-27b first came out. have any of yall kicked the tires on this? https://preview.redd.it/nnns4wsq6fyh1.png?width=913&format=png&auto=webp&s=db487304d8d7b3e1fd1dc0c62173793e6050f033
Original Article

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Wow! Qwen 3.6:35b-a3b on a 3090... pretty amazing.

Reddit r/artificial

A user shares impressive results running a quantized Qwen 3.6:35b-a3b model on a used RTX 3090, achieving 160 tokens per second output after fitting the model into VRAM, and demonstrates vision capabilities with a 75-second video processing time.