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How to Run Qwen3.5-35B-A3B-GPTQ-Int4

Running this model locally is fastest when deployed through Docker.

Use the instructions provided below to complete the setup.

The automated installation script takes care of everything by tailoring the setup perfectly to your system specs.

🔍 Hash-sum: 7d9bbf7bb3ba93da6655e427581c6e6c | 🕓 Last update: 2026-06-28



  • Processor: 6-core 3.5 GHz minimum required
  • RAM: required: 16 GB absolute minimum for small models
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • Graphics: TensorRT-LLM / vLLM inference engine compatible chip

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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