Instructions to use deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16 with MLX:

# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm

# Generate text with mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16")

prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True
)

text = generate(model, tokenizer, prompt=prompt, verbose=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

How to use deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16 with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16"

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": "deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16 with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16 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 "deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16"

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 deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16 with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16"

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 "deepsweet/Qwen3.5-35B-A3B-MLX-oQ4-FP16" \
  --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"

Thanks to you, M1 users cheered!

by felkf - opened Apr 17

Discussion

felkf

Apr 17

The qwen 3.6 model came out, so could you do the fp16-oq8 version?

felkf changed discussion status to closed Apr 17

deepsweet

Owner Apr 17

Hi!

Uploading oQ8-FP16, and oQ4-FP16 is ready.

felkf

Apr 17

Thank you so mucHH!!

deepsweet

Owner Apr 17

Done.

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment