gemma-4-E4B-it-qat-JANG_4M

OsaurusAI/gemma-4-E4B-it-qat-JANG_4M

gemma-4-E4B-it-qat-JANG_4M is a image-text-to-text model from OsaurusAI. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as gemma.

<p align="center"<a href="https://osaurus.ai"<img src="./osaurus-x-banner.png" alt="Osaurus AI"</a</p

Downloads · 30 days

7% of all-time downloads

All-time downloads

504

Public

Parameters

7.9B

19.5 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors10.8 GB · 100%

Parameter types

How the weights are stored.

U323.9B · 49%

Try a prompt

Base models

google/gemma-4-E4B-it-qat-q4_0-unquantized

Model card

From the Hugging Face model README

OsaurusAI/gemma-4-E4B-it-qat-JANG_4M

JANG_4M MLX affine bundle converted from google/gemma-4-E4B-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-E4B-it-qat-q4_0-unquantized`
Architecture	`gemma4` / `Gemma4ForConditionalGeneration`
Text layers	42
Hidden size	2560
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	259 affine bases with `.scales` and `.biases` sidecars
Shards	6 safetensors shards
Capabilities	`multimodal`

Modalities

Modality	Status
Text	supported
Vision	source config present and preserved
Audio	`audio_config` is present and preserved.
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.

Task: Image-Text-to-Text
Library: mlx
Type: gemma4
License: gemma
Languages: en
Created: Jun 9, 2026
Updated: Aug 31, 2026