Instructions to use ToPo-ToPo/Qwen3.8-Flash-Next-mlx-8bit 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-mlx-8bit 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("ToPo-ToPo/Qwen3.8-Flash-Next-mlx-8bit") config = load_config("ToPo-ToPo/Qwen3.8-Flash-Next-mlx-8bit") # 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 Settings
- LM Studio
- Pi
How to use ToPo-ToPo/Qwen3.8-Flash-Next-mlx-8bit 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-mlx-8bit"
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-mlx-8bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent
How to use ToPo-ToPo/Qwen3.8-Flash-Next-mlx-8bit 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-mlx-8bit"
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-mlx-8bit
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use ToPo-ToPo/Qwen3.8-Flash-Next-mlx-8bit 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-mlx-8bit"
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-mlx-8bit" \ --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-mlx-8bit
Qwen/Qwen3.8-Flash-Next を MLX 形式へ変換したもの(8bit 量子化)。
- 変換元:
Qwen/Qwen3.8-Flash-Next(bf16 公式重み, revision de4b8e4) - 変換ツール: mlx-vlm 0.6.17 / mlx 0.32.0
- サイズ: 186 GiB(9.018 bits per weight)
変換コマンド
python -m mlx_vlm convert --hf-path Qwen/Qwen3.8-Flash-Next \
--mlx-path Qwen3.8-Flash-Next-mlx-8bit \
-q --q-bits 8 --q-group-size 32
--q-group-size 32 は必須。n-gram 埋め込みの最終次元が 160 で、既定の 64 では
weight.shape[-1] % group_size != 0 により 128 シャード(51B パラメータ)が
量子化対象から外れ、bf16 のまま残る。
使い方
pip install -U mlx-vlm
python -m mlx_vlm generate --model ToPo-ToPo/Qwen3.8-Flash-Next-mlx-8bit \
--prompt "この画像を説明してください" --image path/to/image.jpg --max-tokens 512
MTP ドラフター(投機デコード)
ドラフターは別リポジトリ
Qwen3.8-Flash-Next-MTP-bf16。
mlx-vlm 0.7.0 以降が必要(qwen4_exp_mtp はリリース版 0.6.17 に未収録):
pip install "mlx-vlm @ git+https://github.com/Blaizzy/mlx-vlm@main"
python -m mlx_vlm generate --model ToPo-ToPo/Qwen3.8-Flash-Next-mlx-8bit \
--draft-model ToPo-ToPo/Qwen3.8-Flash-Next-MTP-bf16 \
--draft-kind mtp --draft-block-size 2 --prompt "..." --max-tokens 512
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Model size
56B params
Tensor type
BF16
·
U32 ·
I64 ·
Hardware compatibility
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8-bit
Model tree for ToPo-ToPo/Qwen3.8-Flash-Next-mlx-8bit
Base model
Qwen/Qwen3.8-Flash-Next