Instructions to use Youssofal/Qwen3.6-27B-MTPLX-Optimized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Youssofal/Qwen3.6-27B-MTPLX-Optimized 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("Youssofal/Qwen3.6-27B-MTPLX-Optimized")

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
LM Studio

Pi new

How to use Youssofal/Qwen3.6-27B-MTPLX-Optimized with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "Youssofal/Qwen3.6-27B-MTPLX-Optimized"

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": "Youssofal/Qwen3.6-27B-MTPLX-Optimized"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use Youssofal/Qwen3.6-27B-MTPLX-Optimized 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 "Youssofal/Qwen3.6-27B-MTPLX-Optimized"

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 Youssofal/Qwen3.6-27B-MTPLX-Optimized

Run Hermes

hermes

MLX LM

How to use Youssofal/Qwen3.6-27B-MTPLX-Optimized with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "Youssofal/Qwen3.6-27B-MTPLX-Optimized"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "Youssofal/Qwen3.6-27B-MTPLX-Optimized"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "Youssofal/Qwen3.6-27B-MTPLX-Optimized",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Qwen3.6-27B-MTPLX-Optimized / mtplx_runtime.json

Youssofal

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	{
	"mtplx_version": "0.1.0-preview",
	"arch_id": "qwen3-next-mtp",
	"mtp_depth_max": 3,
	"recommended_profile": "stable",
	"exactness_baseline": {
	"gate": "Phase 0H paged-verifier smoke",
	"context": 2048,
	"attention_impl": "mlx_vector_paged",
	"max_abs_diff": 0.0,
	"evidence": "LOG.md records Phase 0H exactness gates at max_diff=0.0 for the champion stack"
	},
	"verified_on": {
	"timestamp": "2026-05-02T02:23:23+0100",
	"hardware": "Apple M5 Max, 128 GB unified memory",
	"machine_arch": "arm64",
	"macos": "26.3.1",
	"model": "Qwen3.6-27B-MTPLX-GDN8-Speed4-CyanKiwiMTP",
	"sampler": {
	"temperature": 0.6,
	"top_p": 0.95,
	"top_k": 20
	}
	}
	}