Qwen3-Next-80B-A3B-Thinking

Qwen3-Next-80B-A3B-Thinking is a next-generation foundation model from Alibaba's Qwen team, specifically designed for complex reasoning tasks. It is built on the innovative Qwen3-Next architecture, which combines a Hybrid Attention mechanism (Gated DeltaNet and Gated Attention) with a High-Sparsity Mixture-of-Experts (MoE) structure to achieve ultimate training and inference efficiency. As an 80-billion-parameter sparse model, it activates only about 3 billion parameters during inference, significantly reducing computational costs and delivering over 10 times higher throughput than the Qwen3-32B model on long-context tasks exceeding 32K tokens. This 'Thinking' version is optimized for demanding multi-step problems like mathematical proofs, code synthesis, logical analysis, and agentic planning, and it outputs structured 'thinking' traces by default. In terms of performance, it surpasses more costly models like Qwen3-32B-Thinking and has outperformed Gemini-2.5-Flash-Thinking on multiple benchmarks