Canonical default of the Zen5 family. Multimodal sparse MoE (image + text in → text out) with 35B total / 3B active parameters per token, 256K context. The everyday Zen5 model — agentic-trained, fast at scale, frontier-quality vision-language reasoning at a 3B-active compute budget.

Repackaged from Qwen/Qwen3.6-35B-A3B (apache-2.0, Alibaba Qwen) — quantized to GGUF from the abliterated huihui-ai/Huihui-Qwen3.6-35B-A3B-abliterated variant. 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)	← 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

Files

File	Format
main GGUF (`*-Q4_K.gguf`)	GGUF Q4_K (text + vision)
`mmproj-model-f16.gguf`	multimodal vision projector — load alongside the main GGUF for image input

Run

Hosted via the Hanzo gateway (api.hanzo.ai) as zen5.

Local with llama.cpp (CLI / server) or zen5-engine:

hf download zenlm/zen-5-gguf --local-dir gguf
MAIN=$(ls gguf/*-Q4_K.gguf | head -1)

# text-only chat
llama-cli -m "$MAIN" -p "Explain MoE inference."

# vision-language (image input)
llama-cli -m "$MAIN" \
          --mmproj gguf/mmproj-model-f16.gguf \
          --image path/to/screenshot.png \
          -p "Describe this UI and propose a fix."

License

apache-2.0. Upstream: Qwen/Qwen3.6-35B-A3B by Alibaba Qwen; abliterated variant by huihui-ai. This repository redistributes a quantized derivative under the same license.

zenlm/zen5-gguf

Zen5

Files

Run

License

zenlm/
zen5-gguf