Instructions to use mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF # Run inference directly in the terminal: llama cli -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF # Run inference directly in the terminal: llama cli -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF # Run inference directly in the terminal: ./llama-cli -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF # Run inference directly in the terminal: ./build/bin/llama-cli -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
Use Docker
docker model run hf.co/mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
- LM Studio
- Jan
- Ollama
How to use mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF with Ollama:
ollama run hf.co/mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
- Unsloth Desktop
- Pi
How to use mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF with Docker Model Runner:
docker model run hf.co/mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
- Lemonade
How to use mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
Run and chat with the model
lemonade run user.Qwopus3.6-35B-A3B-v1-APEX-GGUF-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
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 mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF
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 "mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
will there be a MTP version?
to speed up with mtp
yes, totally. I'm following up llama.cpp upstream closely. Once that's merged I'll create an MTP version right away!
You can use the script I created to experience the MTP effect firsthand :)
I have tested it, and it can run on the APEX model.
https://www.modelscope.cn/models/HereIsMark/Qwen3.6-35B-A3B-MTP-Donor
yes, totally. I'm following up llama.cpp upstream closely. Once that's merged I'll create an MTP version right away!
Tons of MTP-refined models are popping up now. We’ve already pulled the branch locally and it’s stable. Reddit is buzzing with discussions. I’d recommend getting started with the new models right away—things are happening way too fast.
Really excited for the MTP version, @mudler ! Great to hear you're tracking the llama.cpp upstream so closely — that dedication shows in the quality of your work. This model is already fantastic, and with MTP support it's going to be even better. Keep it up, can't wait!
是的 非常期待您这款优秀模型的MTP版本, 还有谷歌模型的草稿版本
yes, totally. I'm following up llama.cpp upstream closely. Once that's merged I'll create an MTP version right away!
MTP has just been merged.