Qwen3.5-35B-A3B-GPTQ-Int4 on AMD/Nvidia GPU with 1M Context Full Method

For an instant local deployment, running a pre-configured shell script is ideal.

Follow the guidelines below to continue.

The installer automatically pulls the model (could be multiple GBs).

Your resources are automatically evaluated to lock in the premium configuration.

🖹 HASH-SUM: 239ee4e0218656b33b44b76846f923a1 | 📅 Updated on: 2026-06-25



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: 64 GB to avoid OOM crashes on large contexts
  • 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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