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Qwen3-Coder-Next

LLMs#10AI Models & LLMsOpen source · Web

Qwen3-Coder-Next is an open-weight language model tailored for coding agents and local development. It excels in agentic training, offering strong coding capabilities with reduced inference costs.

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Qwen3-Coder-Next screenshot
Qwen3-Coder-Next screenshot

Qwen3-Coder-Next is an advanced language model specifically designed for coding agents and local development. Built on the Qwen3-Next-80B-A3B-Base architecture, it incorporates hybrid attention and mixture of experts (MoE) to enhance its performance. The model is trained using large-scale executable task synthesis, environment interaction, and reinforcement learning, which significantly boosts its coding and agentic capabilities while maintaining lower inference costs.

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The model emphasizes scaling agentic training signals rather than just parameter scaling. It learns from large collections of verifiable coding tasks paired with executable environments, allowing it to adapt and improve through direct environment feedback. This includes continued pretraining on code-centric data, supervised fine-tuning on high-quality agent trajectories, and domain-specialized expert training in areas like software engineering and web development.

Qwen3-Coder-Next performs exceptionally well on coding agent benchmarks such as SWE-Bench and TerminalBench 2.0. It achieves over 70% on SWE-Bench Verified and remains competitive across multilingual settings and more challenging benchmarks. Despite its smaller size, it matches or exceeds the performance of larger open-source models, demonstrating its efficiency in long-horizon reasoning and multi-turn agentic tasks.

The model's efficiency is highlighted by its improved Pareto tradeoff between performance and cost, making it a cost-effective solution for agent deployment. It can be integrated into various downstream applications, including web development, command-line interfaces, and browser use, showcasing its versatility and practical utility.

  • CategoryAI Models & LLMs
  • Pricing ModelOpen source
  • DeploymentCloud
  • PlatformsWeb

  • Open-weight language model

  • Hybrid attention architecture

  • Mixture of Experts (MoE)

  • Agentic training at scale

  • Reduced inference costs

  • High performance on coding benchmarks

  • Long-horizon reasoning

  • Cost-effective deployment

  1. Access model page: Visit the Qwen3-Coder-Next website

  2. Authenticate: Log in with your credentials

  3. Configure: Set up the model parameters

  4. Send prompts: Input your coding tasks

  5. Fine-tune: Adjust based on feedback

  • Coding Agents
  • Local Development
  • Web Development
  • Command-line Interfaces
  • Browser Automation

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