How to Autostart Qwen3.5-35B-A3B-GPTQ-Int4 Windows 10 No Python Required Local Guide

How to Autostart Qwen3.5-35B-A3B-GPTQ-Int4 Windows 10 No Python Required Local Guide

Running this model locally is fastest when deployed through Docker.

Please follow the instructions listed below to get started.

The client handles the setup, pulling gigabytes of data automatically.

The automated installation script takes care of everything by tailoring the setup perfectly to your system specs.

🧩 Hash sum → 0d126d8c1dedc05ad4b242270dfb36cc — Update date: 2026-06-27



  • Processor: next-gen chip for heavy context processing
  • RAM: enough space for background apps and OS overhead
  • Disk Space: 100 GB for multi-modal model vision components
  • Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

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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  • Qwen3.5-35B-A3B-GPTQ-Int4 Locally via LM Studio

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