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

June 28, 2026
By:  dev
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How to Install Qwen3.5-35B-A3B-GPTQ-Int4 Locally via Ollama 2

Deploying this model locally is quickest when done via Docker.

Review and follow the instructions below.

After cloning, fire up the application using Docker.

💾 File hash: 6221aa07986ac0b1bd1bb2ce36a89801 (Update date: 2026-06-27)
  • Processor: 6-core 3.5 GHz minimum required
  • RAM: high-speed DDR5 memory preferred for CPU offloading
  • Disk Space: 100 GB for multi-modal model vision components
  • Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

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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