Instructions to use deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use deucebucket/Qwen3.6-35B-A3B-Cerebellum-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 deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_K_M
# Run inference directly in the terminal:
llama cli -hf deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_K_M
# Run inference directly in the terminal:
llama cli -hf deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_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 deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_K_M
# Run inference directly in the terminal:
./llama-cli -hf deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_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 deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_K_M

Use Docker

docker model run hf.co/deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_K_M

LM Studio
Jan

vLLM

How to use deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_K_M

Ollama
How to use deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF with Ollama:
```
ollama run hf.co/deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_K_M
```
Unsloth Desktop

How to use deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_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": "deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF with Docker Model Runner:
```
docker model run hf.co/deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_K_M
```

Lemonade

How to use deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_K_M

Run and chat with the model

lemonade run user.Qwen3.6-35B-A3B-Cerebellum-GGUF-Q3_K_M

List all available models

lemonade list

Hermes Agent

How to use deucebucket/Qwen3.6-35B-A3B-Cerebellum-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 deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_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 deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_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 "deucebucket/Qwen3.6-35B-A3B-Cerebellum-GGUF:Q3_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"

Qwen 3.6 35B-A3B Cerebellum — 12 GB, fits 16 GB VRAM

by deucebucket - opened May 2

Discussion

deucebucket

Owner May 2

First Cerebellum release for Qwen 3.6 35B-A3B (hybrid SSM+MoE, 256 experts per layer, 8 active per token).

12 GB single file — fits in 16 GB VRAM with room for 8K context.

Benchmarks (measured on this file)

Benchmark	Score
ARC-Challenge	94.8%
HellaSwag	91.5%
MMLU-Redux	73.9%
HumanEval pass@1	75.0%
Perplexity (WikiText-2)	7.85

How it works

Cerebellum measures which tensor groups survive extreme compression and which don't. This file has 400 tensor-level overrides from group ablation, reverse ablation, and router surgery across all 40 layers.

Key finding: 10 of 11 tensor groups tolerated Q2_K with under 2% degradation. 7 of those actually performed better at Q2_K — imatrix-guided Q2_K acts as beneficial regularization on gate/mixing weights in this architecture.

Final BPW: 2.73

Usage

llama-server --model Qwen3.6-35B-A3B-Cerebellum.gguf --n-gpu-layers 99 --ctx-size 8192

Feedback welcome. More Cerebellum releases coming for other models.

cai2023

May 6

Thank you for providing such an excellent model.

deucebucket

Owner May 6

thanks for trying it. let me know where it falls over for you, what stuff it gets wrong, anything weird you notice. if i figure out how to fix that area in a future build ill ping you back.

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