Qwen-Image-3.0 is the third-generation foundational image generation model in the Qwen-Image series. The core focus of this release is 'Real' (实), emphasizing authenticity across three dimensions, building upon previous versions that focused on precision, variety, completeness, beauty, and authenticity. It represents a significant advancement in rich content generation, authentic details, and deep knowledge.

Qwen released Qwen-AgentWorld, a native language world model that simulates agent environments across seven domains. It features native world modeling where environment modeling is the training objective from continual pre-training onward (CPT → SFT → RL), not a post hoc adaptation. A single model simulates text-based environments including MCP, Search, Terminal, and SWE.

Qwen released the Qwen-Robot Suite, a collection of three foundation models for physical world intelligence: Qwen-RobotNav for agentic navigation, Qwen-RobotManip for robotic manipulation, and Qwen-RobotWorld for embodied world modeling. These models bridge the gap between vision-language understanding and physical control for embodied intelligence. The suite enables open-ended instruction following and generalization across real-robot platforms and tasks.

Qwen3.7-Plus is a multimodal agent model that unifies vision and language into a single, versatile agent foundation. It builds on Qwen3.7's strong text backbone and delivers a comprehensive upgrade in vision-language capabilities. It is designed to function as a versatile multimodal agent.

Qwen-VLA is a new embodied intelligence model that goes beyond understanding images and videos to enable real-world action. It builds on multimodal large language model capabilities to support embodied agents that can act in the world, not just understand it. This represents a significant expansion from perception to physical action for the Qwen family.