Text Generation
MLX
Safetensors
qwen3_5
apple-silicon
speculative-decoding
qwen
qwen3
mtp
mtplx
local-ai
q4
conversational
4-bit precision
Instructions to use Youssofal/Qwen3.5-4B-MTPLX-Optimized-Speed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Youssofal/Qwen3.5-4B-MTPLX-Optimized-Speed 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/Qwen3.5-4B-MTPLX-Optimized-Speed") 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/Qwen3.5-4B-MTPLX-Optimized-Speed 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/Qwen3.5-4B-MTPLX-Optimized-Speed"
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/Qwen3.5-4B-MTPLX-Optimized-Speed" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Youssofal/Qwen3.5-4B-MTPLX-Optimized-Speed 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/Qwen3.5-4B-MTPLX-Optimized-Speed"
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/Qwen3.5-4B-MTPLX-Optimized-Speed
Run Hermes
hermes
- MLX LM
How to use Youssofal/Qwen3.5-4B-MTPLX-Optimized-Speed 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/Qwen3.5-4B-MTPLX-Optimized-Speed"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "Youssofal/Qwen3.5-4B-MTPLX-Optimized-Speed" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Youssofal/Qwen3.5-4B-MTPLX-Optimized-Speed", "messages": [ {"role": "user", "content": "Hello"} ] }'
File size: 1,887 Bytes
28ac31a 5d19867 28ac31a 5d19867 28ac31a 5d19867 28ac31a 5d19867 28ac31a 5d19867 28ac31a 5d19867 28ac31a 5d19867 28ac31a 5d19867 28ac31a 5d19867 28ac31a | 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 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 | {
"arch_id": "qwen3-next-mtp",
"artifact_role": "small-q4-speed-test",
"base_trunk": "mlx-community/Qwen3.5-4B-MLX-4bit",
"exactness_baseline": {
"artifact": "/Users/youssof/.mtplx/qwen35_4b_final_mtp1_gate.json",
"gate": "mtp1-greedy-ar-equivalence",
"max_tokens": 16,
"matches": 1,
"scope": "greedy AR and MTP1 generated identical token sequence on the warm_code_continuation prompt",
"seed": 0,
"status": "passed",
"total": 1
},
"mtp_depth_max": 2,
"mtp_sidecar": "official Qwen/Qwen3.5-4B MTP tensors; quantization recorded in config.json",
"mtplx_version": "0.1.0-preview",
"recommended_draft_lm_head": {
"bits": 4,
"group_size": 64,
"mode": "affine"
},
"recommended_draft_sampler": {
"temperature": 0.6,
"top_k": 20,
"top_p": 0.95
},
"recommended_profile": "performance-cold",
"sampler": {
"temperature": 0.6,
"top_k": 20,
"top_p": 0.95
},
"speed_evidence": {
"acceptance_by_depth": [
0.6666666666666666,
0.2222222222222222
],
"accepted_drafts": 16,
"ar_tok_s": 108.4050622912913,
"artifact": "/Users/youssof/.mtplx/qwen35_4b_depth_grid_q4_body4_draftt0p6.json",
"draft_lm_head": "tied embedding reused as 4-bit affine group64 draft head",
"draft_temperature": 0.6,
"enable_thinking": false,
"generated_tokens": 48,
"mtp_depth": 2,
"mtp_tok_s": 120.05572596536466,
"note": "Qwen3.5-4B measured fastest at depth 2. Depth 3 over-drafts this small native-MTP head and can lose to AR.",
"sampler": {
"temperature": 0.6,
"top_k": 20,
"top_p": 0.95
},
"speedup_vs_ar": 1.1074734281575087
},
"verified_on": {
"hardware": "Apple Silicon local MTPLX workstation",
"machine_arch": "arm64",
"model": "Qwen3.5-4B-MTPLX-Optimized-Speed",
"timestamp": "2026-05-04T06:17:00+0100"
}
}
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