Zen Designer GGUF: 235B Vision-Language Model (Abliterated)

235B MoE | Vision-Language | GGUF Quantized | Abliterated

GGUF quantized and abliterated version of Zen Designer — the 235B flagship vision-language model from Zen LM. Supports images, video, documents, charts, GUIs, and spatial reasoning with 256K context.


Model Specifications

Attribute Value
Parameters 235B total / 22B active (MoE)
Architecture Vision-language transformer (Mixture of Experts)
Context Window 256K tokens
Modalities Text, Images, Video, Documents
OCR Languages 32 scripts
License Apache 2.0

Available Formats

Format Size Description Recommended Use
Q2_K (split) ~60 GB 2-bit quantization, 15-part split Servers with 64+ GB RAM, maximum scale
Q4_K_M ~142 GB 4-bit quantization, single or split Best quality/size tradeoff for local inference

Quick Start

llama.cpp

# Download a split (Q2_K example — replace with Q4_K_M filename as appropriate)
# Then run:
llama-cli \
  --model zen-designer-235b-a22b-instruct-abliterated-Q2_K-00001-of-00015.gguf \
  --mmproj mmproj-zen-designer-235b-a22b-instruct-abliterated-f16.gguf \
  --image your_image.jpg \
  --prompt "Describe this image in detail." \
  -n 1024 \
  --ctx-size 8192 \
  --temp 0.7

For multi-part files, place all split parts in the same directory and point --model to part 00001.

Vision Tasks

Zen Designer handles a broad range of visual inputs:

  • Image analysis and description
  • Document and PDF parsing
  • Chart and table extraction
  • GUI navigation and screen understanding
  • Video understanding with temporal reasoning
  • Bounding box and spatial grounding

Abliteration

This model has been abliterated — a technique that removes refusal behaviors encoded in the model weights without fine-tuning. The process works by identifying the refusal direction in the model's residual stream and projecting it out of the weight matrices.

What abliteration does:

  • Removes hardcoded refusal responses
  • Preserves all other capabilities and knowledge
  • Does not alter factual knowledge or reasoning ability

What abliteration does not do:

  • Add harmful knowledge the base model lacked
  • Guarantee any specific behavior
  • Replace a system prompt or application-level safety policy

Users are responsible for appropriate deployment and use of abliterated models. Apply system prompts and application-layer controls to define model behavior for your use case.


Model Family

Model Format Parameters Context
zen-designer-235b-a22b-instruct SafeTensors 235B / 22B active 256K
zen-designer-gguf GGUF 235B / 22B active 256K

Links

Zen LM | Hanzo AI | GitHub | All Models


Part of the Zen model family (zenlm.org) by Hanzo AI (Techstars '17) and Zoo Labs Foundation (zoo.ngo).

Downloads last month
186
GGUF
Model size
235B params
Architecture
qwen3vlmoe
Hardware compatibility
Log In to add your hardware

4-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support