How to use from the
Use from the
MLX library
# Make sure mlx-vlm is installed
# pip install --upgrade mlx-vlm

from mlx_vlm import load, generate
from mlx_vlm.prompt_utils import apply_chat_template
from mlx_vlm.utils import load_config

# Load the model
model, processor = load("nabi-chan/Qwen3.6-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled-MLX-8bit")
config = load_config("nabi-chan/Qwen3.6-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled-MLX-8bit")

# Prepare input
image = ["http://images.cocodataset.org/val2017/000000039769.jpg"]
prompt = "Describe this image."

# Apply chat template
formatted_prompt = apply_chat_template(
    processor, config, prompt, num_images=1
)

# Generate output
output = generate(model, processor, formatted_prompt, image)
print(output)

Working in Progress!

This model is a version of hesamation/Qwen3.6-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled converted via MLX 0.31.2

I do not recommend its use for practical applications as I have not yet completed testing on quantization for now.

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·
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