How to Run Qwen3.5-35B-A3B-GPTQ-Int4 Windows 10 For Low VRAM (6GB/8GB) Easy Build

How to Run Qwen3.5-35B-A3B-GPTQ-Int4 Windows 10 For Low VRAM (6GB/8GB) Easy Build

To install this model locally in the shortest time, opt for Docker.

Follow the sequence of steps detailed below.

The system automatically triggers a cloud download for all heavy weights.

You don’t need to tweak anything, as the installer will automatically pick the highest performing setup for you.

📊 File Hash: ed9dc7798710f598c21037bd82270c04 — Last update: 2026-06-23



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: 32 GB or higher for smooth 32k context lengths
  • Disk Space:70 GB free space for full FP16 weights storage
  • GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

The Qwen3.5-35B-A3B-GPTQ-Int4 is a large language model delivering advanced reasoning and multilingual capabilities. Built on the A3B architecture, it leverages a 35‑billion parameter foundation to achieve high performance across diverse tasks. By employing GPTQ Int4 quantization, the model maintains a compact footprint while preserving much of its original accuracy. State‑of‑the‑art inference efficiency is realized through optimized kernel implementations and reduced memory bandwidth requirements. The following table summarizes key technical specifications for quick reference.

Specification Value
Model Name Qwen3.5-35B-A3B-GPTQ-Int4
Parameters 35 B
Quantization GPTQ Int4
Architecture A3B
Context Length 8192 tokens
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