How to Deploy Qwen3.5-35B-A3B-GPTQ-Int4 Windows 11 Quantized GGUF Offline Setup

Deploying this model locally is quickest when done via Docker.

Use the instructions provided below to complete the setup.

The setup auto-downloads all needed files (several GBs).

Once launched, the setup wizard will detect your specs to configure the model for maximum efficiency.

📦 Hash-sum → 6736d6ca0f874d8e3e541aaecc2935f2 | 📌 Updated on 2026-06-27 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 32 GB or higher for smooth 32k context lengths Disk Space: at least 100 GB for multiple local LLM variants Graphics: 12 GB VRAM minimum required for basic quantization

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.

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