Instructions to use ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16 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("ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16") 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
- Pi
How to use ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16 with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16"
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": "ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16 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 "ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16"
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 ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16 with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16"
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 "ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16" \ --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"
Qwen3.8-Flash-Next-MTP-bf16
Qwen/Qwen3.8-Flash-Next の公式 bf16
チェックポイントに内蔵された MTP ヘッド(mtp.* 31 テンソル)を切り出した、
投機デコード用ドラフター。単体では使わない。
- 変換元:
Qwen/Qwen3.8-Flash-Next(revision de4b8e4) - 変換ツール: mlx-vlm main(0.7.0rc0)の
Qwen4ExpMTPSplitter - サイズ: 4.9 GiB(bf16)
必要環境
qwen4_exp_mtp の抽出・実行は mlx-vlm 0.7.0 以降(リリース版 0.6.17 には未収録)。
pip install "mlx-vlm @ git+https://github.com/Blaizzy/mlx-vlm@main"
使い方
python -m mlx_vlm generate --model ToPo-ToPo/Qwen3.8-Flash-Next-mlx-4bit \
--draft-model ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16 \
--draft-kind mtp --draft-block-size 2 \
--prompt "..." --max-tokens 512
量子化版リポジトリ(4bit /
8bit)の mtp/
サブフォルダにも同じものが入っているので、本体を落とせばドラフターも付いてくる。
抽出コマンド
from mlx_vlm.speculative.drafters.qwen4_exp_mtp.split import Qwen4ExpMTPSplitter
Qwen4ExpMTPSplitter().split("Qwen/Qwen3.8-Flash-Next", "Qwen3.8-Flash-Next-MTP-bf16")
量子化後のリポジトリからは mtp.* が落ちている(mlx-vlm の sanitize が除外する)ので、
必ず公式 bf16 から切り出すこと。
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Model size
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