Setup Qwen3.6-35B-A3B No-Internet Version Step-by-Step Windows

Deploying this model locally is quickest when done via Docker.

Follow the guidelines below to continue.

The client handles the setup, pulling gigabytes of data automatically.

To guarantee smooth performance, the installation process auto-selects the best possible options for your PC.

🗂 Hash: 6ae589530c4171ca7bd1eab6d5a34165 • Last Updated: 2026-06-23 Verify CPU: multi-threading optimized for fast prompt processing RAM: 64 GB to avoid OOM crashes on large contexts Disk: 150+ GB for high-context vector database storage Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

The Qwen3.6-35B-A3B is a large language model featuring 35 billion parameters and an advanced A3B architecture designed for superior reasoning and instruction following. It supports an extended context window of 128K tokens, enabling the model to understand and generate long‑form content with high coherence. Trained on a diverse corpus of web‑scale text and curated academic resources, the model demonstrates state‑of‑the‑art performance across a wide range of benchmarks, from language understanding to code generation. The model also incorporates multimodal capabilities, allowing it to process and generate text alongside images, which expands its utility in creative and analytical tasks. In practical applications, Qwen3.6-35B-A3B excels in complex problem solving, delivering accurate answers while maintaining low latency and efficient memory usage, as shown in the following technical overview.

Parameters	35 B
Context Length	128K tokens
Training Data	Web‑scale + academic corpora
Peak FLOPs	≈2.1×10^20
Model Type	Autoregressive transformer with A3B blocks

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