Qwen3.5

Qwen3.5 is an innovative open-weight, native vision-language model designed for complex, long-horizon agentic tasks. Leveraging a hybrid architecture that combines linear attention with Mixture of Experts (MoE), it delivers the power of a massive 397-billion-parameter model while maintaining inference speeds comparable to a 17-billion-parameter model. Its multimodal capabilities make it highly effective for tasks that require understanding and generating both visual and textual data, making it ideal for developers, AI researchers, and organizations seeking advanced AI solutions. What sets Qwen3.5 apart is its open-source nature, enabling customization and integration without vendor lock-in, and its efficient design that balances scale with performance. This makes it suitable for a range of demanding applications where speed and scalability are critical, all while being accessible for those willing to explore open AI models.