Instructions to use abenzerps/Holotron4-30B-A3B-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 abenzerps/Holotron4-30B-A3B-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 abenzerps/Holotron4-30B-A3B-GGUF:Q4_0
# Run inference directly in the terminal:
llama cli -hf abenzerps/Holotron4-30B-A3B-GGUF:Q4_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf abenzerps/Holotron4-30B-A3B-GGUF:Q4_0
# Run inference directly in the terminal:
llama cli -hf abenzerps/Holotron4-30B-A3B-GGUF:Q4_0

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 abenzerps/Holotron4-30B-A3B-GGUF:Q4_0
# Run inference directly in the terminal:
./llama-cli -hf abenzerps/Holotron4-30B-A3B-GGUF:Q4_0

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 abenzerps/Holotron4-30B-A3B-GGUF:Q4_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf abenzerps/Holotron4-30B-A3B-GGUF:Q4_0

Use Docker

docker model run hf.co/abenzerps/Holotron4-30B-A3B-GGUF:Q4_0

LM Studio
Jan

vLLM

How to use abenzerps/Holotron4-30B-A3B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "abenzerps/Holotron4-30B-A3B-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": "abenzerps/Holotron4-30B-A3B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/abenzerps/Holotron4-30B-A3B-GGUF:Q4_0

Ollama
How to use abenzerps/Holotron4-30B-A3B-GGUF with Ollama:
```
ollama run hf.co/abenzerps/Holotron4-30B-A3B-GGUF:Q4_0
```
Unsloth Desktop

How to use abenzerps/Holotron4-30B-A3B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf abenzerps/Holotron4-30B-A3B-GGUF:Q4_0

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": "abenzerps/Holotron4-30B-A3B-GGUF:Q4_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use abenzerps/Holotron4-30B-A3B-GGUF with Docker Model Runner:
```
docker model run hf.co/abenzerps/Holotron4-30B-A3B-GGUF:Q4_0
```

Lemonade

How to use abenzerps/Holotron4-30B-A3B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull abenzerps/Holotron4-30B-A3B-GGUF:Q4_0

Run and chat with the model

lemonade run user.Holotron4-30B-A3B-GGUF-Q4_0

List all available models

lemonade list

Hermes Agent

How to use abenzerps/Holotron4-30B-A3B-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 abenzerps/Holotron4-30B-A3B-GGUF:Q4_0

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 abenzerps/Holotron4-30B-A3B-GGUF:Q4_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use abenzerps/Holotron4-30B-A3B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf abenzerps/Holotron4-30B-A3B-GGUF:Q4_0

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 "abenzerps/Holotron4-30B-A3B-GGUF:Q4_0" \
  --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"

Holotron4-30B-A3B GGUF

GGUF quantizations of Hcompany/Holotron4-30B-A3B, a 30B hybrid NemotronH MoE vision-language model (VLM) for Computer Use, tool-driven work, and agentic workflows.

For vision and audio input, use the included F16 multimodal projector (mmproj-Holotron4-30B-f16.gguf).

Upstream benchmarks

Holotron4 improves over its base model, Nemotron 3 Nano Omni, on GUI workflows and in environments with MCP tools, APIs, or code sandboxes. Gains are absolute percentage points.

Benchmark	Interface	Nemotron 3 Nano Omni	Holotron4-30B-A3B	Gain
OSWorld	GUI	21.0	76.3	+55.3
OSWorld 2.0	GUI and code	0.2	7.9	+7.7
AutomationBench	MCP	19.4	35.6	+16.2
PinchBench	Terminal	84.7	88.6	+3.9
ALE (Linux, code)	Terminal	0.6	8.5	+7.9

GGUF files

Due to the model's MoE intermediate dimensions (1856), standard K-quants (Q4_K, Q6_K) trigger internal fallbacks in llama.cpp to Q5/Q8 types. Therefore, clean 32-block quantizations (Q4_0 and Q8_0) are provided for optimal efficiency and accuracy.

Quantization	File	Size	Notes
Q4_0	Holotron4-30B-Q4_0.gguf	18.0 GB	Recommended balanced default (clean 4-bit)
Q8_0	Holotron4-30B-Q8_0.gguf	33.6 GB	Near-lossless high-precision reference
Multimodal projector	mmproj-Holotron4-30B-f16.gguf	2.99 GB	Required for image and audio input

Usage

Use a current llama.cpp build with the included chat template.

llama-cli \
  -m Holotron4-30B-Q4_0.gguf \
  -c 4096 -n 512 --temp 0.6 --top-p 0.95 \
  --jinja --chat-template-file chat_template.jinja \
  -p "<|im_start|>user\nWhat is computer use in AI?<|im_end|>\n<|im_start|>assistant\n"

For multimodal / vision and audio input:

llama-mtmd-cli \
  -m Holotron4-30B-Q4_0.gguf \
  -mm mmproj-Holotron4-30B-f16.gguf \
  --image screenshot.png \
  -p "Describe the interface in this screenshot."