How to Deploy Qwen3.5-35B-A3B-GPTQ-Int4 on AMD/Nvidia GPU Uncensored Edition Full Method

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

Please follow the instructions listed below to get started.

Hands-free setup: the system self-downloads the heavy model files.

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

📡 Hash Check: d648a47da1c116eb90bc29b6726ddb1c | 📅 Last Update: 2026-06-28



  • Processor: high single-core performance needed for token latency
  • RAM: 32 GB or higher for smooth 32k context lengths
  • Disk Space: free: 80 GB on system drive for scratch space
  • Graphics: CUDA Compute Capability 8.0+ required for flash-attention

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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