If you want the fastest local installation for this model, use standard pip packages.
Check out the detailed setup guide below to begin.
The script takes care of fetching the multi-gigabyte model weights.
There is no manual tuning required; the builder deploys the best matching configuration.
The Qwen3-VL-235B-A22B-Instruct model combines a massive 235āÆbillion parameters with an A22B architecture to deliver stateāofātheāart multimodal understanding. It processes text and images simultaneously, enabling highāfidelity visionālanguage tasks such as caption generation, visual question answering, and diagram interpretation. The model was fineātuned on a diverse corpus of webāscale text and imageācaption pairs, which improves its contextual reasoning and visual grounding. Its context window extends to 32āÆk tokens, allowing it to retain longārange 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 instructionātuned variant ensures reliable performance on userācentric prompts, making it suitable for productionāgrade AI assistants.
| Metric | Value |
|---|---|
| Parameters | 235āÆB |
| Context Length | 32āÆk tokens |
| Modalities | Text + Image |
| Training Data | Webāscale text & imageācaption pairs |
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