AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit

AX DiffusionGemma 26B-A4B IT MLX 4-bit

Parameter count: approximately 25.82B logical parameters (26B total, approximately 4B active per token). 4-bit is the quantization precision, not a 4B model-size claim.

Transparent upstream mirror — AutomatosX made no model changes.

This is a revision-pinned, transparent mirror of mlx-community/diffusiongemma-26B-A4B-it-4bit at commit a7a81407613811e8ba63af92ac0d852b809e191f.

AutomatosX did not train, fine-tune, merge, convert, quantize, re-quantize, or otherwise alter the weights, configuration, tokenizer, processor, chat template, or generation settings. The MLX conversion and quantization were performed upstream by MLX Community with mlx-vlm 0.6.3. AutomatosX adds only this mirror documentation, the preserved upstream model card, a copy of the declared license, machine-readable provenance, and a total_parameters field in the shard index so the Hub does not mistake packed 4-bit storage for the logical model size.

Model details

• Base model: google/diffusiongemma-26B-A4B-it
• Upstream MLX source: mlx-community/diffusiongemma-26B-A4B-it-4bit
• Format: MLX Safetensors for Apple Silicon
• Architecture: DiffusionGemmaForBlockDiffusion, mixture of experts
• Quantization: upstream 4-bit affine, group size 64, with the upstream 8-bit exceptions unchanged
• Weight shards: 4, totaling 16,543,055,405 bytes
• Generation: block-autoregressive discrete diffusion with a 256-token canvas
• MTP: not applicable; this is not an autoregressive next-token model

Download

hf download AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit \
  --local-dir ./AX-DiffusionGemma-26B-A4B-IT-MLX-4bit

Use with MLX-VLM

pip install -U mlx-vlm
python -m mlx_vlm.generate \
  --model AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit \
  --max-tokens 100 \
  --temperature 0.0 \
  --prompt "Describe this image." \
  --image <path_to_image>

Try with AX Engine

AX Engine has an experimental native MLX path for DiffusionGemma. Its download workflow generates the local runtime manifest without changing the published model artifacts:

ax-engine serve AutomatosX/AX-DiffusionGemma-26B-A4B-IT-MLX-4bit \
  --download --port 31418

DiffusionGemma support in AX Engine is experimental and is not recommended for production use. Its first visible output is a committed diffusion block, so ordinary autoregressive TTFT and decode-throughput comparisons do not apply.

Mirror policy and provenance

UPSTREAM_README.md preserves the original MLX Community model card. ax_provenance.json pins the source commit and records SHA-256 values and sizes for every mirrored artifact. All weight shards and all source artifacts other than the replaced model card and shard index are byte-identical to the pinned upstream revision. In the index, weight_map and total_size remain unchanged; only the logical total_parameters metadata field was added.

This repository exists for revision-pinned cataloging and convenient discovery; it does not represent a new model, conversion, quantization, or benchmark claim from AutomatosX.

License and responsible use

The upstream MLX repository and Google base model declare Apache License 2.0. See LICENSE, the preserved upstream card, and the Google base-model card for usage limitations, safety guidance, and responsible-use considerations.