JANGQ AI

JANGQ-AI/gemma-4-31B-it-qat-JANG_4M

JANG_4M MLX affine bundle converted from google/gemma-4-31B-it-qat-q4_0-unquantized.

This bundle keeps Gemma 4 bookends and media-sensitive components coherent: token embeddings/output projection, norms, media towers/embedders, and Gemma 4 per-layer embedding/gate/projector tensors are fp16 passthrough; self-attention and MoE router projections are 8-bit affine; decoder MLP/expert bulk is 4-bit affine.

Bundle

Field Value
Source google/gemma-4-31B-it-qat-q4_0-unquantized
Architecture gemma4 / Gemma4ForConditionalGeneration
Text layers 60
Hidden size 5376
Weight format jang_affine
Top-level quantization bits=8, group_size=32, mode=affine
Tier bits attention=8, router=8, mlp=4, embed=16, per_layer_media=16
Quantized modules 410 affine bases with .scales and .biases sidecars
Shards 25 safetensors shards
Capabilities vision

Modalities

Modality Status
Text supported
Vision source config present and preserved
Audio audio_config is empty/not active for this variant; this card does not claim audio support.
Video No video_config is present, so this card does not claim a verified video runtime path.

Runtime support depends on a Gemma 4 compatible MLX/vMLX loader that understands config.json quantization overrides, jang_config.json, and Gemma 4 processor/chat-template files.

Runtime Metadata

  • config.json has source-derived has_vision, has_audio, has_video, modalities, and capabilities.
  • tokenizer_config.json includes bos_token_id, eos_token_id, pad_token_id, and the patched Gemma 4 chat template.
  • processor_config.json is preserved for Gemma 4 multimodal processing.
  • MTP/speculative drafter weights are not present in the source checkpoint; metadata is mtp: none / mtp_policy: none.
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