Instructions to use TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-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 TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M
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 TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M
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 TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M
Use Docker
docker model run hf.co/TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF with Ollama:
ollama run hf.co/TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M
- Unsloth Desktop
- Pi
How to use TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M
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": "TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF with Docker Model Runner:
docker model run hf.co/TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M
- Lemonade
How to use TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-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 TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M
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 TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M
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 "TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF:Q4_K_M" \ --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"
benchmarks
could you please test the model on benchmarks and make evaluations with scores please, thanks for your work btw
Yea sure. Will do them the same as the GLM distill benchmarks.
thank you so much, btw do you want to work together for making even more diverse and larger high quality datasets? I have 200$ in my google api key, we can use them to create gemini 3 flash best dataset
If you have discord I recommend joining the server. I am active on there and am working with multiple people in there. feel free to join and we can make something cool!