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

Use the instructions provided below to complete the setup.

After that, launch the environment using docker-compose.

🧾 Hash-sum — f3b9369d9e28b0956e40350c133d752d • 🗓 Updated on: 2026-06-27 Verify Processor: high single-core performance needed for token latency RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space: 100 GB for multi-modal model vision components Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

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.

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