---

license: apache-2.0

base_model: Qwen/Qwen3-Next-80B-A3B-Instruct

library_name: gguf

pipeline_tag: text-generation

language:

• en
• zh

tags:

• zen5
• zen5-coder
• zenlm
• hanzo
• gguf
• moe
• code
• agentic
• zen-5

---

Zen5 Coder

Code-specialized member of the Zen5 family. 80B-parameter sparse MoE tuned for repo-scale code understanding, agentic refactoring, and tool-use coding loops.

Repackaged from Qwen/Qwen3-Next-80B-A3B-Instruct (apache-2.0, Alibaba Qwen) — a code-tuned redistribution from the abliterated variant by huihui-ai. Not trained from scratch — a permissively-licensed redistribution for the OSS-clean Zen model line.

Part of the canonical Zen5 ladder:

| SKU | Hardware fit | This repo |

|---|---|---|

| zen5-flash | anything (4 GB VRAM) | zen-5-flash-gguf |

| zen5-mini | 32 GB | zen-5-mini-gguf |

| zen5 (default) | 24 GB+ VRAM (Q4_K) | zen-5-gguf |

| zen5-coder | 48 GB+ VRAM (Q4_K_M) | ← you are here |

| zen5-pro | Mac M4 Max / DGX Spark / H100 80GB | zen-5-pro-gguf |

| zen5-max | Mac Studio M3 Ultra 512GB / 8x H100 | zen-5-max-gguf |

Weights

A first-party zenlm GGUF mirror is staged for this repo. Until it lands, the recommended path is to use the hosted zen5-coder endpoint (see below) or pull a community 80B-class coder GGUF Q4_K_M into a local gguf/ directory.

Run

Hosted via the Hanzo gateway (api.hanzo.ai) as zen5-coder — preferred until the first-party GGUF mirror lands.

Local with llama.cpp or a compatible runtime, once you have a GGUF in gguf/:

MAIN=$(ls gguf/*Q4_K_M*.gguf | head -1)
llama-cli -m "$MAIN" -p "Refactor this Python function to use async/await."

License

apache-2.0. Upstream: Qwen/Qwen3-Next-80B-A3B-Instruct by Alibaba Qwen; abliterated variant by huihui-ai. This repository redistributes a derivative under the same license.