Image-Text-to-Text
MLX
Safetensors
qwen3_5
mtplx
qwen3.6
speculative-decoding
multi-token-prediction
conversational
4-bit precision
Instructions to use Youssofal/Qwen3.6-27B-MTPLX-Optimized-Quality with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Youssofal/Qwen3.6-27B-MTPLX-Optimized-Quality 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("Youssofal/Qwen3.6-27B-MTPLX-Optimized-Quality") config = load_config("Youssofal/Qwen3.6-27B-MTPLX-Optimized-Quality") # 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
- LM Studio
- Pi new
How to use Youssofal/Qwen3.6-27B-MTPLX-Optimized-Quality 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-Quality"
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-Quality" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Youssofal/Qwen3.6-27B-MTPLX-Optimized-Quality 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-Quality"
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-Quality
Run Hermes
hermes
File size: 1,308 Bytes
2293023 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | {
"arch_id": "qwen3-next-mtp",
"artifact_role": "optimized-quality",
"benchmark_summary": {
"acceptance_by_depth": [
0.9556737588652481,
0.852575488454707,
0.7406749555950266
],
"artifact": "/tmp/mtplx-flat8-maxfan-bakeoff-20260510-040405/flat8-int8-flappy2k.json",
"peak_gib": 27.615886019542813,
"suite": "flappy 2k depth3 max-fan",
"tok_s": 33.6276837588148,
"verify_ms_per_call": 88.13897531140259
},
"exactness_baseline": {
"gate": "flat8-quality-mtp-bakeoff",
"notes": "Validated with mtplx inspect and local Flappy 2k max-fan bakeoff; 2k Flappy validator truncates before balanced delimiter completion, so code-shape validator is the meaningful capped-run gate.",
"status": "candidate-promoted-by-user-decision"
},
"mtp_depth_max": 3,
"mtp_sidecar": "CyanKiwi calibrated INT8 affine group128, BF16 aux preserved",
"mtplx_version": "0.1.0-preview",
"recommended_profile": "performance-cold",
"sampler": {
"temperature": 0.6,
"top_k": 20,
"top_p": 0.95
},
"target_precision": "flat8 affine group64",
"verified_on": {
"hardware": "M5 Max local max-fan bakeoff",
"model": "Qwen3.6-27B-MTPLX-Optimized-Quality",
"status": "validated-candidate",
"timestamp": "2026-05-10T04:16:00+01:00"
}
}
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