The large language model series developed by Qwen (github.com)

The Qwen development team has unveiled the latest updates in their large language model series, introducing Qwen3-2507, which features two main variants: Qwen3-Instruct-2507 and Qwen3-Thinking-2507. These enhancements significantly improve capabilities in instruction following, logical reasoning, text comprehension, and response quality. Notably, both models now support ultra-long-context understanding with input capacities extendable up to 1 million tokens, enabling users to work with extensive documents seamlessly. This release is significant for the AI/ML community as it includes state-of-the-art advancements in reasoning tasks, achieving top performance on complex benchmarks typically requiring human expertise. Additionally, the Qwen3 series offers flexibility with dense and Mixture-of-Expert (MoE) models across various sizes, enhancing its usability for diverse applications. The integration of advanced training and quantization practices also broadens accessibility, paving the way for innovative deployments in industry settings. The public availability of Qwen3 weights further fosters collaboration and development within the open-source ecosystem, as researchers and developers can explore these cutting-edge models to address a wide array of challenges in natural language processing.