If you want the fastest local installation for this model, use Docker.
Refer to the instructions below to proceed.
The installer will automatically analyze your hardware and select the optimal configuration for your system.
The Qwen3-VL-235B-A22B-Instruct model combines a massive 235âŻbillion parameters with an A22B architecture to deliver stateâofâtheâart multimodal understanding. It processes text and images simultaneously, enabling highâfidelity visionâlanguage tasks such as caption generation, visual question answering, and diagram interpretation. The model was fineâtuned on a diverse corpus of webâscale text and imageâcaption pairs, which improves its contextual reasoning and visual grounding. Its context window extends to 32âŻk tokens, allowing it to retain longârange 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 instructionâtuned variant ensures reliable performance on userâcentric prompts, making it suitable for productionâgrade AI assistants.
| Metric | Value |
|---|---|
| Parameters | 235âŻB |
| Context Length | 32âŻk tokens |
| Modalities | Text + Image |
| Training Data | Webâscale text & imageâcaption pairs |
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