Instructions to use Shiftedx/qwen3.8-27b-aeon-ultimate-uncensored-mxfp8-vision-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Shiftedx/qwen3.8-27b-aeon-ultimate-uncensored-mxfp8-vision-mlx with MLX:

# 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("Shiftedx/qwen3.8-27b-aeon-ultimate-uncensored-mxfp8-vision-mlx")
config = load_config("Shiftedx/qwen3.8-27b-aeon-ultimate-uncensored-mxfp8-vision-mlx")

# 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)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

How to use Shiftedx/qwen3.8-27b-aeon-ultimate-uncensored-mxfp8-vision-mlx with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "Shiftedx/qwen3.8-27b-aeon-ultimate-uncensored-mxfp8-vision-mlx"

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Shiftedx/qwen3.8-27b-aeon-ultimate-uncensored-mxfp8-vision-mlx"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent

How to use Shiftedx/qwen3.8-27b-aeon-ultimate-uncensored-mxfp8-vision-mlx with Hermes Agent:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "Shiftedx/qwen3.8-27b-aeon-ultimate-uncensored-mxfp8-vision-mlx"

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default Shiftedx/qwen3.8-27b-aeon-ultimate-uncensored-mxfp8-vision-mlx

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Shiftedx/qwen3.8-27b-aeon-ultimate-uncensored-mxfp8-vision-mlx with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "Shiftedx/qwen3.8-27b-aeon-ultimate-uncensored-mxfp8-vision-mlx"

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "Shiftedx/qwen3.8-27b-aeon-ultimate-uncensored-mxfp8-vision-mlx" \
  --custom-provider-id mlx-lm \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

qwen3.8-27b-aeon-ultimate-uncensored-mxfp8-vision-mlx

Independent MXFP8 MLX conversion of AEON-7/Qwen3.8-27B-AEON-ULTIMATE-UNCENSORED-BF16, pinned at a6775a9a8ebb65cab3f707b4ab087fc7aa698634. This is a community conversion, not an official AEON-7 or Qwen release.

Format

Language quantization: MXFP8, 8-bit, group size 32
Vision: 333 source BF16 tensors preserved; patch embedding converted to MLX axes
Indexed artifact size: 26.71 GiB
Architecture: dense Qwen3.5-family hybrid attention/GDN, 64 language layers
Configured context: 262,144 tokens (not exhaustively qualified here)
Tokenizer, chat template, processor metadata, and Apache-2.0 lineage preserved

This standard MLX artifact deliberately contains no MTP sidecar or active MTP metadata.

Qualification and limitations

Pinned source metadata and all safetensors headers were checked.
Quantization used the fixture-matched Qwen3.5 streaming adapter from MLX-LM 0.31.3.
MXFP4 and MXFP8 were each produced directly from the same BF16 parent.
Structural inspection and strict local load are required release gates.

This is an experimental quantization of an abliterated, intentionally unaligned checkpoint. Quantization does not restore safety alignment. The source publisher warns that the model can produce unsafe or illegal material and places downstream safety and legal responsibility on operators. Review the source model card before use and add access controls, logging, moderation, and human review appropriate to your deployment.

Basic use

python -m mlx_vlm.generate --model <repo-or-path> --image image.jpg --prompt "Describe this image." --max-tokens 256

Downloads last month: 829

Safetensors

Model size

27B params

Tensor type

U32

BF16

MLX

Hardware compatibility

8-bit

Model tree for Shiftedx/qwen3.8-27b-aeon-ultimate-uncensored-mxfp8-vision-mlx

Base model

Qwen/Qwen3.8-27B

Finetuned

AEON-7/Qwen3.8-27B-AEON-ULTIMATE-UNCENSORED-BF16

Quantized

(29)

this model

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Collection

AEON Qwen3.8 27B MLX text/vision quants: MXFP4, MXFP8, native-MTP, and the benchmark-selected attention8 + BF16-recurrence hybrid. • 7 items • Updated 18 days ago