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MODEL Listed

Qwen3-Coder-30B-A3B-Instruct-GGUF

Qwen3 Coder 30B A3B Instruct is a specialized Mixture-of-Experts (MoE) model optimized for high-performance programming tasks. By utilizing an active parameter count of 3B within a 30B total parameter architecture, it delivers the reasoning capabilities of a large model with the inference speed and memory efficiency of a much smaller one. For developers, this means a significant reduction in VRAM requirements without sacrificing complex logic handling or multi-language syntax accuracy. It is particularly effective for autonomous code generation, refactoring legacy systems, and acting as a local copilot. This GGUF quantization makes it highly accessible for local deployment via llama.cpp or Ollama, allowing seamless integration into IDEs without relying on cloud APIs.

unslothtext generation
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01 / MODEL CARD

Model card

Qwen3 Coder 30B A3B Instruct is a specialized Mixture-of-Experts (MoE) model optimized for high-performance programming tasks. By utilizing an active parameter count of 3B within a 30B total parameter architecture, it delivers the reasoning capabilities of a large model with the inference speed and memory efficiency of a much smaller one. For developers, this means a significant reduction in VRAM requirements without sacrificing complex logic handling or multi-language syntax accuracy. It is particularly effective for autonomous code generation, refactoring legacy systems, and acting as a local copilot. This GGUF quantization makes it highly accessible for local deployment via llama.cpp or Ollama, allowing seamless integration into IDEs without relying on cloud APIs.

Model typetext generation
Providerunsloth
Licenseapache-2.0
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://huggingface.co/unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF
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Version informationUse the source repository for the latest version
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03 / DOWNLOAD

Download this model

We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.

This entry points to Hugging Face. The commands use the matching ModelScope repository format; confirm that the repository exists on ModelScope before running them. Model repository: unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF
Install ModelScope

Install the CLI and SDK dependency before downloading.

pip install modelscope
Download the full model repository

Download the complete weights, configuration and model card.

modelscope download --model unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF
Download one file to a local directory

README.md is used as an example; replace it with another repository file when needed.

modelscope download --model unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF README.md --local_dir ./dir
Download with the SDK

Useful in Python projects and automation scripts.

from modelscope import snapshot_download
model_dir = snapshot_download('unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF')
Clone with Git

Make sure Git LFS is installed correctly.

git lfs install
git clone https://www.modelscope.cn/unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF.git
Clone without downloading LFS blobs

Fetch the repository structure first, then pull large files when needed.

GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF.git
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.

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