Qwen3-VL

Vision-Language (VL) models are advanced AI systems designed to process and understand both visual inputs, like images and videos, and textual information. Qwen3-VL developed by Alibaba Cloud Dev Team will be one of this models. By combining these two modalities, VL models can perform tasks such as image captioning, visual question answering, and multimodal content generation.

Qwen3-VL
Qwen3-VL

What to expect in Qwen3-VL

Key Enhancements:

  • State-of-the-Art Image Understanding: Qwen3-VL will set new benchmarks in visual understanding across various resolutions and ratios, further improving on tasks like MathVista, DocVQA, RealWorldQA, and MTVQA.
  • Enhanced Video Understanding for Extended Durations: Qwen3-VL will be able to process videos longer than 20 minutes, providing higher-quality capabilities in video-based question answering, dialogue, and content creation.
  • Advanced Agent Capabilities for Device Integration: With even more complex reasoning and decision-making abilities, Qwen3-VL will be designed to seamlessly integrate with mobile devices, robots, and other systems, enabling automated operations based on visual and textual inputs.
  • Expanded Multilingual Support: Qwen3-VL will enhance its ability to understand text embedded in images, extending beyond English and Chinese to support a broader range of languages, including European languages, Japanese, Korean, Arabic, and Vietnamese.

In the future, Qwen3-VL will enhance its capabilities by supporting a broad range of image resolutions for improved performance. By default, the model will utilize native resolutions, but users will have the flexibility to adjust resolution settings for performance optimization. Higher resolutions will boost accuracy, though at the cost of increased computation.

Users will be able to fine-tune configurations by setting minimum and maximum pixel counts, such as a token count range between 256 and 1280, to achieve a balance between speed and memory usage. Additionally, Qwen3-VL will offer two methods for precise control over image size input: setting pixel ranges to maintain aspect ratios or specifying exact dimensions for resizing, rounded to the nearest multiple of 28.

Explore Qwen models on HuggingFace.