Global AI chat room · 15 online now Join now
Q
MODEL Listed

qwen3-coder-next

Qwen3-Coder-Next is a specialized open-weight model engineered specifically for high-autonomy coding agents and local development environments. Moving away from dense architectures, it utilizes a sparse Mixture-of-Experts (MoE) design with 80B total parameters, strategically activating only 3B parameters per token. For developers, this means you get the reasoning depth of a much larger model without the prohibitive latency or VRAM requirements typically associated with 80B-class models. With a massive 262k context window, it excels at codebase-wide reasoning, allowing you to feed entire repositories or long documentation sets into a single prompt. While many models struggle with the precision required for agentic loops, Qwen3-Coder-Next is optimized for the iterative 'plan-act-verify' cycle. It is an ideal choice for developers building local IDE extensions, automated refactoring tools, or autonomous CI/CD agents where inference speed and long-context retrieval are critical performance bottlenecks.

qwentext generation
01 / MODEL CARD

Model card

Qwen3-Coder-Next is a specialized open-weight model engineered specifically for high-autonomy coding agents and local development environments. Moving away from dense architectures, it utilizes a sparse Mixture-of-Experts (MoE) design with 80B total parameters, strategically activating only 3B parameters per token. For developers, this means you get the reasoning depth of a much larger model without the prohibitive latency or VRAM requirements typically associated with 80B-class models. With a massive 262k context window, it excels at codebase-wide reasoning, allowing you to feed entire repositories or long documentation sets into a single prompt. While many models struggle with the precision required for agentic loops, Qwen3-Coder-Next is optimized for the iterative 'plan-act-verify' cycle. It is an ideal choice for developers building local IDE extensions, automated refactoring tools, or autonomous CI/CD agents where inference speed and long-context retrieval are critical performance bottlenecks.

Model typetext generation
Providerqwen
LicenseAPI
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://openrouter.ai/qwen/qwen3-coder-next
View model source
Version informationUse the source repository for the latest version
—
03 / DOWNLOAD

Download this model

This entry does not include a recognizable ModelScope or Hugging Face repository URL. Open the source link and follow its official download instructions.
04 / WORKFLOW

How to use

  1. 01
    Step 1

    Read the model card and source information.

  2. 02
    Step 2

    Start with a small, non-sensitive evaluation.

  3. 03
    Step 3

    Review quality, licensing and usage limits.

  4. 04
    Step 4

    Adopt it only after validation.

05 / DISCUSSIONS

Discussions

Use this space to keep checking source information, usage experience and maintenance status.

Open source page
Email