qwen3-5-9b

Qwen3.5 represents a significant leap forward, integrating breakthroughs in multimodal learning, architectural efficiency, reinforcement learning scale, and global accessibility. This is a 9B parameter dense model, supporting a native context length of 262,144 tokens.

Highlights Unified Vision-Language Foundation. Early fusion training on multimodal tokens achieves cross-generational parity with Qwen3 and outperforms Qwen3-VL models across reasoning, coding, agents, and visual understanding benchmarks.

Scalable RL Generalization. Reinforcement learning scaled across million-agent environments with progressively complex task distributions for robust real-world adaptability.

Global Linguistic Coverage. Expanded support to 201 languages and dialects, enabling inclusive, worldwide deployment with nuanced cultural and regional understanding.