Qwen: Qwen3 Coder Next
Provided by OpenRouter
Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per token, delivering performance comparable to models with 10 to 20x higher active compute, which makes it well suited for cost-sensitive, always-on agent deployment. The model is trained with a strong agentic focus and performs reliably on long-horizon coding tasks, complex tool usage, and recovery from execution failures. With a native 256k context window, it integrates cleanly into real-world CLI and IDE environments and adapts well to common agent scaffolds used by modern coding tools. The model operates exclusively in non-thinking mode and does not emit <think> blocks, simplifying integration for production coding agents.
Specifications
262,144 tokens$0.120/M$0.750/MAbout Qwen: Qwen3 Coder Next
Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per token, delivering performance comparable to models with 10 to 20x higher active compute, which makes it well suited for cost-sensitive, always-on agent deployment. The model is trained with a strong agentic focus and performs reliably on long-horizon coding tasks, complex tool usage, and recovery from execution failures. With a native 256k context window, it integrates cleanly into real-world CLI and IDE environments and adapts well to common agent scaffolds used by modern coding tools. The model operates exclusively in non-thinking mode and does not emit <think> blocks, simplifying integration for production coding agents.
Strengths
- •Large context window (262k tokens) for long conversations
- •Strong coding performance across multiple languages
Use Cases
- •Software development and debugging
- •Content creation and writing assistance
- •General conversations and Q&A
Limitations
Performance may vary based on query complexity, context length, and task type. Consider using higher-tier models for production-critical applications.
Sample Prompts
Try these prompts to explore Qwen: Qwen3 Coder Next's capabilities:
Write a function to sort an array of objects by a specific property in JavaScript
Explain how to implement a binary search tree and discuss its time complexity
Debug this code and explain the issues: [paste your code here]
Tip: Customize these prompts to fit your specific needs and use cases.
Premium Model
This model requires credits to use. Qwen: Qwen3 Coder Next offers advanced capabilities and high-performance features for production-grade applications.
Credits required for premium models. Free models are available without credits.
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