How to Install Qwen3.5-35B-A3B-GPTQ-Int4 Locally via Ollama 2 Windows

How to Install Qwen3.5-35B-A3B-GPTQ-Int4 Locally via Ollama 2 Windows

Setting up this model locally is incredibly fast if you use the native CMD prompt.

Follow the sequence of steps detailed below.

All large files and heavy weights are downloaded automatically by the script.

Once launched, the wizard detects your specs to configure the model for maximum efficiency.

📊 File Hash: d3086f4106869033decbe3e011a08d7e — Last update: 2026-07-03



  • Processor: 4.0 GHz+ boost clock recommended for CPU inference
  • RAM: 64 GB to avoid OOM crashes on large contexts
  • Disk: high-speed SSD 120 GB to cache model layers
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

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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  3. Installer configuring distributed tensor calculation grids across multiple local desktop systems configurations
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  5. Downloader for specialized AnimateDiff motion modules for local video AI
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  7. Setup tool initializing prefix-caching parameters inside production-tier vLLM system units
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  9. Installer optimizing local RAM offloading for massive model files
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  11. Downloader for specialized AnimateDiff v3 motion modules for local video
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