qwen/qwen3-coder-next

Qwen3-Coder-Next is the flagship code intelligence model launched by Alibaba Cloud’s Qwen team. Its core positioning is an “efficient model that leverages 3B activated parameters to achieve top-tier programming intelligence capabilities,” specifically designed for on-premises deployment and low-cost agent applications.

• Key upgrades: Built upon Qwen3-Next-80B-A3B-Base, it integrates hybrid attention and MoE architectures, trained via executable task synthesis and reinforcement learning.
• Applicable scenarios: Real-world programming repair tasks such as SWE-Bench, web development, CLI automation, browser proxy, and other dynamic interactive coding tasks.
• Product value: With only 3B activated parameters (out of a total of 80B), it achieves performance on SWE-Bench-Pro comparable to models with 10–20 times more activated parameters.
• Evaluation data: Scores exceed 70% on SWE-Bench Verified, maintaining strong competitiveness across multiple languages and in the Pro version.
• Training innovation: Employs a three-stage agent training approach: continuous pre-training + high-quality trajectory fine-tuning + multi-domain expert distillation, enhancing error recovery and tool-use capabilities.

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Core Capabilities

⚡ Ultimate cost-effectiveness

3B activated parameters deliver agent performance close to that of ultra-large models, significantly reducing inference costs.

🧠 Real-world environment learning

Trained through executable environment feedback, directly optimizing code-generation strategies from runtime results.

🛠️ Robust agent behavior

Excel at long-term planning, tool invocation, and autonomous correction after execution failures, adapting well to complex development workflows.

🌐 Multi-platform real-world implementation

Already integrated into IDEs and agent frameworks such as Qwen Code, Claude Code, Cline, and OpenClaw.

📊 Pareto-optimal trade-offs

Significantly outperforms similar open-source models on the efficiency-performance curve, making it ideal for low-cost, large-scale deployment.

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Selected Test Data