Instructions to use sugoitoolkit/Sugoi-32B-Ultra-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use sugoitoolkit/Sugoi-32B-Ultra-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="sugoitoolkit/Sugoi-32B-Ultra-GGUF",
	filename="Sugoi-32B-Ultra-F16.gguf",
)

llm.create_chat_completion(
	messages = "\"Меня зовут Вольфганг и я живу в Берлине\""
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use sugoitoolkit/Sugoi-32B-Ultra-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf sugoitoolkit/Sugoi-32B-Ultra-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf sugoitoolkit/Sugoi-32B-Ultra-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf sugoitoolkit/Sugoi-32B-Ultra-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf sugoitoolkit/Sugoi-32B-Ultra-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 sugoitoolkit/Sugoi-32B-Ultra-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf sugoitoolkit/Sugoi-32B-Ultra-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 sugoitoolkit/Sugoi-32B-Ultra-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf sugoitoolkit/Sugoi-32B-Ultra-GGUF:Q4_K_M

Use Docker

docker model run hf.co/sugoitoolkit/Sugoi-32B-Ultra-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use sugoitoolkit/Sugoi-32B-Ultra-GGUF with Ollama:
```
ollama run hf.co/sugoitoolkit/Sugoi-32B-Ultra-GGUF:Q4_K_M
```

Unsloth Studio new

How to use sugoitoolkit/Sugoi-32B-Ultra-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for sugoitoolkit/Sugoi-32B-Ultra-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for sugoitoolkit/Sugoi-32B-Ultra-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for sugoitoolkit/Sugoi-32B-Ultra-GGUF to start chatting

Pi new

How to use sugoitoolkit/Sugoi-32B-Ultra-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf sugoitoolkit/Sugoi-32B-Ultra-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "sugoitoolkit/Sugoi-32B-Ultra-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use sugoitoolkit/Sugoi-32B-Ultra-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf sugoitoolkit/Sugoi-32B-Ultra-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 sugoitoolkit/Sugoi-32B-Ultra-GGUF:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use sugoitoolkit/Sugoi-32B-Ultra-GGUF with Docker Model Runner:
```
docker model run hf.co/sugoitoolkit/Sugoi-32B-Ultra-GGUF:Q4_K_M
```

Lemonade

How to use sugoitoolkit/Sugoi-32B-Ultra-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull sugoitoolkit/Sugoi-32B-Ultra-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Sugoi-32B-Ultra-GGUF-Q4_K_M

List all available models

lemonade list

Sugoi LLM 32B Ultra (GGUF version)

Unleashing the full potential of the previous sugoi 32B model, Sugoi 32B Ultra. Benchmark soon.

Downloads last month: 251,036

GGUF

Model size

33B params

Architecture

qwen2

Hardware compatibility

2-bit

4-bit

8-bit

16-bit

Model tree for sugoitoolkit/Sugoi-32B-Ultra-GGUF

Base model

Qwen/Qwen2.5-32B

Finetuned

Qwen/Qwen2.5-32B-Instruct

Quantized

(139)

this model

Quantizations

1 model

Collection including sugoitoolkit/Sugoi-32B-Ultra-GGUF

SugoiLLM

Collection

Official public release collection • 3 items • Updated Aug 25, 2025 • 3