Zidane29/Qwen_Qwen3-Coder-30B-A3B-Instruct-GGUF overview
<div style="width: auto; margin left: auto; margin right: auto" <img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min width: 40…
Runs locally from ~10.49 GB disk (12 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
| Model ID | Zidane29/Qwen_Qwen3-Coder-30B-A3B-Instruct-GGUF |
|---|---|
| Author | Zidane29 |
| Pipeline | text-generation |
| License | apache-2.0 |
| Base model | Qwen/Qwen3-Coder-30B-A3B-Instruct |
| Last modified | 2026-08-30T11:31:13.000Z |
Model README
---
library_name: transformers
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct/blob/main/LICENSE
pipeline_tag: text-generation
base_model: Qwen/Qwen3-Coder-30B-A3B-Instruct
tags:
- TensorBlock
- GGUF
---
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<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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Qwen/Qwen3-Coder-30B-A3B-Instruct - GGUF
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<a href="https://discord.com/invite/Ej5NmeHFf2" style="display: inline-block; padding: 10px 20px; background-color: #5865F2; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
Join our Discord to learn more about what we're building ↗
</a>
</div>
This repo contains GGUF format model files for Qwen/Qwen3-Coder-30B-A3B-Instruct.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5753.
Our projects
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<th colspan="2" style="font-size: 25px;">Forge</th>
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<img src="https://imgur.com/faI5UKh.jpeg" alt="Forge Project" width="900"/>
</th>
</tr>
<tr>
<th colspan="2">An OpenAI-compatible multi-provider routing layer.</th>
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<th colspan="2">
<a href="https://github.com/TensorBlock/forge" target="_blank" style="
display: inline-block;
padding: 8px 16px;
background-color: #FF7F50;
color: white;
text-decoration: none;
border-radius: 6px;
font-weight: bold;
font-family: sans-serif;
">🚀 Try it now! 🚀</a>
</th>
</tr>
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<th style="font-size: 25px;">Awesome MCP Servers</th>
<th style="font-size: 25px;">TensorBlock Studio</th>
</tr>
<tr>
<th><img src="https://imgur.com/2Xov7B7.jpeg" alt="MCP Servers" width="450"/></th>
<th><img src="https://imgur.com/pJcmF5u.jpeg" alt="Studio" width="450"/></th>
</tr>
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<th>A comprehensive collection of Model Context Protocol (MCP) servers.</th>
<th>A lightweight, open, and extensible multi-LLM interaction studio.</th>
</tr>
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<th>
<a href="https://github.com/TensorBlock/awesome-mcp-servers" target="_blank" style="
display: inline-block;
padding: 8px 16px;
background-color: #FF7F50;
color: white;
text-decoration: none;
border-radius: 6px;
font-weight: bold;
font-family: sans-serif;
">👀 See what we built 👀</a>
</th>
<th>
<a href="https://github.com/TensorBlock/TensorBlock-Studio" target="_blank" style="
display: inline-block;
padding: 8px 16px;
background-color: #FF7F50;
color: white;
text-decoration: none;
border-radius: 6px;
font-weight: bold;
font-family: sans-serif;
">👀 See what we built 👀</a>
</th>
</tr>
</table>
Prompt template
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Model file specification
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| Qwen3-Coder-30B-A3B-Instruct-Q2_K.gguf | Q2_K | 11.259 GB | smallest, significant quality loss - not recommended for most purposes |
| Qwen3-Coder-30B-A3B-Instruct-Q3_K_S.gguf | Q3_K_S | 13.292 GB | very small, high quality loss |
| Qwen3-Coder-30B-A3B-Instruct-Q3_K_M.gguf | Q3_K_M | 14.712 GB | very small, high quality loss |
| Qwen3-Coder-30B-A3B-Instruct-Q3_K_L.gguf | Q3_K_L | 15.901 GB | small, substantial quality loss |
| Qwen3-Coder-30B-A3B-Instruct-Q4_0.gguf | Q4_0 | 17.304 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| Qwen3-Coder-30B-A3B-Instruct-Q4_K_S.gguf | Q4_K_S | 17.456 GB | small, greater quality loss |
| Qwen3-Coder-30B-A3B-Instruct-Q4_K_M.gguf | Q4_K_M | 18.557 GB | medium, balanced quality - recommended |
| Qwen3-Coder-30B-A3B-Instruct-Q5_0.gguf | Q5_0 | 21.081 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| Qwen3-Coder-30B-A3B-Instruct-Q5_K_S.gguf | Q5_K_S | 21.081 GB | large, low quality loss - recommended |
| Qwen3-Coder-30B-A3B-Instruct-Q5_K_M.gguf | Q5_K_M | 21.726 GB | large, very low quality loss - recommended |
| Qwen3-Coder-30B-A3B-Instruct-Q6_K.gguf | Q6_K | 25.093 GB | very large, extremely low quality loss |
| Qwen3-Coder-30B-A3B-Instruct-Q8_0.gguf | Q8_0 | 32.484 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/Qwen_Qwen3-Coder-30B-A3B-Instruct-GGUF --include "Qwen3-Coder-30B-A3B-Instruct-Q2_K.gguf" --local-dir MY_LOCAL_DIR
If you wanna download multiple model files with a pattern (e.g., Q4_Kgguf), you can try:
huggingface-cli download tensorblock/Qwen_Qwen3-Coder-30B-A3B-Instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'Run Zidane29/Qwen_Qwen3-Coder-30B-A3B-Instruct-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models