Qwen3.6-35B-A3B Locally via Ollama 2 Windows

Qwen3.6-35B-A3B Locally via Ollama 2 Windows

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

Execute the commands and steps outlined below.

The installer auto-downloads and deploys the entire model pack.

The installer will automatically analyze your hardware and select the optimal configuration.

📡 Hash Check: 840c0b16b69ecc838f29607d3dea8f68 | 📅 Last Update: 2026-07-04



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Disk: 150+ GB for high-context vector database storage
  • GPU: high memory bandwidth GPU for next-gen local AI pipeline

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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  • Patch optimizing inference parameters and system prompt alignment locally
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