Instructions to use stamsam/Qwen3.6-28B-REAP-oQ4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use stamsam/Qwen3.6-28B-REAP-oQ4 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("stamsam/Qwen3.6-28B-REAP-oQ4")

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 stamsam/Qwen3.6-28B-REAP-oQ4 with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "stamsam/Qwen3.6-28B-REAP-oQ4"

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "stamsam/Qwen3.6-28B-REAP-oQ4"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use stamsam/Qwen3.6-28B-REAP-oQ4 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 "stamsam/Qwen3.6-28B-REAP-oQ4"

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 stamsam/Qwen3.6-28B-REAP-oQ4

Run Hermes

hermes

MLX LM

How to use stamsam/Qwen3.6-28B-REAP-oQ4 with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "stamsam/Qwen3.6-28B-REAP-oQ4"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "stamsam/Qwen3.6-28B-REAP-oQ4"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "stamsam/Qwen3.6-28B-REAP-oQ4",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Qwen3.6-28B-REAP-oQ4

An oQ4 / MLX quant of 0xSero/Qwen3.6-28B-REAP, made to be easier to run locally on Apple Silicon.

This repo is just the quantized version. The model work, source release, and credit belong to 0xSero.

Go check out the original repo here:

0xSero/Qwen3.6-28B-REAP

Big shout out to 0xSero and Sybil Solutions for putting the original model out there. If this version is useful, please like and support the source model too.

Notes

Quantized for MLX-compatible local use.
No extra fine-tuning was done here.
No benchmark claims yet. Test it on your own prompts.

License

Apache 2.0, following the source checkpoint.

Downloads last month: 344

Safetensors

Model size

5B params

Tensor type

BF16

U32

MLX

Hardware compatibility

4-bit

Model tree for stamsam/Qwen3.6-28B-REAP-oQ4

Base model

Qwen/Qwen3.6-35B-A3B

Finetuned

0xSero/Qwen3.6-28B

Quantized

(7)

this model