Setup Qwen3-VL-235B-A22B-Instruct on Copilot+ PC Quantized GGUF

If you want the fastest local installation for this model, use standard pip packages.

Follow the guidelines below to continue.

The system automatically triggers a cloud download for all heavy weights.

The installer diagnoses your environment to deploy the most compatible profile.

🔗 SHA sum: d0841d7b3310c3b39e604e889141f56e | Updated: 2026-07-02 Verify Processor: 6-core 3.5 GHz minimum required RAM: enough space for background apps and OS overhead Disk Space: free: 80 GB on system drive for scratch space Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

The Qwen3-VL-235B-A22B-Instruct model combines a massive 235 billion parameters with an A22B architecture to deliver state‑of‑the‑art multimodal understanding. It processes text and images simultaneously, enabling high‑fidelity vision‑language tasks such as caption generation, visual question answering, and diagram interpretation. The model was fine‑tuned on a diverse corpus of web‑scale text and image‑caption pairs, which improves its contextual reasoning and visual grounding. Its context window extends to 32 k tokens, allowing it to retain long‑range dependencies across documents and complex scenes. In benchmark evaluations, Qwen3-VL-235B-A22B-Instruct consistently outperforms prior large multimodal models on both accuracy and efficiency metrics. The accompanying instruction‑tuned variant ensures reliable performance on user‑centric prompts, making it suitable for production‑grade AI assistants.

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