Ornith-1.0-35B-JANG_6M

JANGQ-AI/Ornith-1.0-35B-JANG_6M

Ornith-1.0-35B-JANG_6M is a image-text-to-text model from JANGQ-AI. 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 mit.

<p align="center" <img src="mlx-studio-logo.png" alt="MLX Studio" width="400"/ </p

Downloads · 30 days

3% of all-time downloads

All-time downloads

1.4K

Public

Parameters

35.1B

28.2 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors28.2 GB · 100%

Parameter types

How the weights are stored.

U3234.6B · 99%

Try a prompt

Base models

Model card

From the Hugging Face model README

<p align="center"> <img src="mlx-studio-logo.png" alt="MLX Studio" width="400"/> </p> <p align="center"> <img src="jangq-logo.png" alt="JANGQ" width="200"/> </p> <p align="center"> <a href="https://vmlx.net"><img src="vmlx-app.png" alt="vMLX — run JANG models on Apple Silicon" width="820"></a> </p> <h3 align="center">⚡ All JANG models are meant to be run in <a href="https://vmlx.net">vMLX</a></h3> <div align="center">

Ornith-1.0-35B · JANG_6M

Vision-language · Qwen3.5 hybrid backbone · 6-bit near-lossless mixed precision · ~26 GB

</div>

⚠️ Requires MLX Studio (or the vMLX runtime) to run. Standard mlx_lm cannot load JANG bundles correctly — they store the Qwen3.5 RMSNorm un-shifted and rely on the runtime's +1 scale_shift + per-layer bit detection. MLX Studio includes the JANG loader.

JANG_6M = 8-bit attention + 6-bit routed experts (affine mixed precision, group-size 64); vision tower kept fp16. A near-lossless JANG profile from JANGQ-AI.

Architecture


Family	`qwen3_5_moe` (hybrid)
Text layers	40 — 30 Gated-DeltaNet + 10 full-attention
MoE / dims	256 routed experts (stacked switch_mlp) · hidden 2048
Vision	ViT tower (`model.visual`) preserved fp16
Cache	hybrid (GDN state + KV for attention layers)
Parsers	reasoning `qwen3` · tools `qwen`

Provenance

Quantization: JANG · JANG_6M (8-bit attention + 6-bit routed experts, group-size 64; vision tower fp16) · [email protected]

Task: Image-Text-to-Text
Library: mlx
Type: qwen3_5_moe
License: mit
Created: Jun 27, 2026
Updated: Sep 8, 2026