Qwen 3.6-Plus is now available, featuring enhanced code development capabilities and improved efficiency in multimodal recognition and inference, making the Vibe Coding experience even better.
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency.
qwen-image-2 coming soon
Qwen3-VL-32B is the 32-billion-parameter dense variant in Alibaba’s Qwen3 vision-language model family. It is a multimodal (vision + language + video) transformer designed for unified perception, long-context reasoning, robust OCR and visual grounding, and agentic/toolified workflows.
Qwen3 Coder Plus stable version, released on July 22, 2025, provides higher stability, suitable for production deployment.
Explore the qwen3-8b API.
Explore the qwen3-32b API.
Has 3 billion parameters, balancing performance and resource requirements, suitable for enterprise-level applications. - This model may employ MoE or other optimized architectures, suitable for scenarios requiring efficient processing of complex tasks, such as intelligent customer service and content generation.
Explore the qwen3-14b API.
Explore the qwen3-coder-plus API.
Explore the qwen3-coder-480b-a35b-instruct API.
Explore the qwen3-coder API.
Qwen3-235B-A22B is the flagship model of the Qwen3 series, with 23.5 billion parameters, using a Mixture of Experts (MoE) architecture. - Particularly suitable for complex tasks requiring high-performance Inference, such as coding, mathematics, and Multimodal applications.
Qwen3.7-Max's core strength lies in the breadth and depth of its agentic capabilities. In coding, it handles everything from front-end prototyping to complex multi-file engineering projects. For office and productivity work, it enables workflow automation through MCP integration and multi-agent collaboration. In long-horizon autonomous execution, it maintained coherent reasoning throughout a 35-hour, fully autonomous kernel optimization experiment involving over 1,000 tool calls — convincingly demonstrating its sustained, stable execution. Furthermore, it delivers consistently strong cross-framework generalization, performing reliably whether deployed in Claude Code, OpenClaw, Qwen Code, or other frameworks.
Qwen3.6-Max-Preview Compared with Qwen3.6-Plus, this preview version brings stronger world knowledge and instruction compliance capabilities, as well as significantly improved agent programming performance on multiple benchmarks