How to Install Qwen3.5-35B-A3B-GPTQ-Int4 Locally via Ollama 2 No Python Required Step-by-Step Windows

The fastest method for installing this model locally is by using Docker.

Refer to the action plan below to initialize the model.

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

The smart installation system will instantly find the perfect configuration.

📎 HASH: 76227e5e1a2e25981a279e1e5bf69d39 | Updated: 2026-06-29



  • CPU: multi-threading optimized for fast prompt processing
  • RAM: 48 GB needed to prevent memory swapping to disk
  • Disk Space: free: 80 GB on system drive for scratch space
  • 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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