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Jiunsong/supergemma4-26b-abliterated-multimodal-mlx-4bit

sourceHugging Facegemmaupdated 5mo agoView on Hugging Face
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SuperGemma4-26B-Abliterated-Multimodal MLX 4bit

This is the lighter-weight MLX build of Jiunsong/supergemma4-26b-abliterated-multimodal.

It preserves multimodal behavior while reducing local storage and memory demand for Apple Silicon setups that want a smaller package.

Important note on the Hugging Face size badge

If the Hub UI shows this repo as a smaller class such as 5B or 8B, that is a Hub-side auto-inference artifact from the exported MLX quantized config.

This repo is still a quantized release of the full SuperGemma4-26B-Abliterated-Multimodal line derived from the Gemma 4 26B-A4B multimodal family. The smaller badge does not mean the model was accidentally converted into a different 5B or 8B model.

Why this variant

  • —Smaller MLX footprint for local use
  • —Keeps text + vision support
  • —Preserves the abliterated / low-refusal behavior of the main release
  • —Good option when you want better fit on-device without dropping multimodality
  • —Verified with both text-only and image-grounded prompts

April 18 Stability Sync

  • —Synced this quantized child repo to the latest hardened parent chat template.
  • —Updated exact JSON-only formatting, long-context extraction, false-premise correction, and prompt-hygiene behavior.
  • —This refresh does not change the quantized weights themselves; it updates the serving template and release notes so downstream runtimes inherit the same behavior fixes.
  • —Parent validation snapshot after the refresh: capability audit 9 / 9, reliability audit 20 / 20.

Validation

  • —Text check: returned READY
  • —Image check: returned red for a solid red test image
  • —Disk footprint: about 15 GB

Recommended use

Pick this version when you want a smaller MLX package and are willing to trade a bit of precision for a lighter local deployment.

Quick start

bash
python3 -m mlx_vlm.server \
  --model /absolute/path/to/supergemma4-26b-abliterated-multimodal-mlx-4bit \
  --host 127.0.0.1 \
  --port 8091
python
from mlx_vlm import load

model, processor = load("/absolute/path/to/supergemma4-26b-abliterated-multimodal-mlx-4bit")
print("Loaded.")