Instructions to use Hcompany/Holo-3.1-35B-A3B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Hcompany/Holo-3.1-35B-A3B-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="Hcompany/Holo-3.1-35B-A3B-GGUF")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Hcompany/Holo-3.1-35B-A3B-GGUF", dtype="auto")

llama-cpp-python

How to use Hcompany/Holo-3.1-35B-A3B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Hcompany/Holo-3.1-35B-A3B-GGUF",
	filename="imatrix.gguf",
)

llm.create_chat_completion(
	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"
					}
				}
			]
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Hcompany/Holo-3.1-35B-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 Hcompany/Holo-3.1-35B-A3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Hcompany/Holo-3.1-35B-A3B-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 Hcompany/Holo-3.1-35B-A3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Hcompany/Holo-3.1-35B-A3B-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 Hcompany/Holo-3.1-35B-A3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Hcompany/Holo-3.1-35B-A3B-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 Hcompany/Holo-3.1-35B-A3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Hcompany/Holo-3.1-35B-A3B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Hcompany/Holo-3.1-35B-A3B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use Hcompany/Holo-3.1-35B-A3B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Hcompany/Holo-3.1-35B-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": "Hcompany/Holo-3.1-35B-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/Hcompany/Holo-3.1-35B-A3B-GGUF:Q4_K_M

SGLang

How to use Hcompany/Holo-3.1-35B-A3B-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Hcompany/Holo-3.1-35B-A3B-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Hcompany/Holo-3.1-35B-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 images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Hcompany/Holo-3.1-35B-A3B-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Hcompany/Holo-3.1-35B-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"
						}
					}
				]
			}
		]
	}'

Ollama
How to use Hcompany/Holo-3.1-35B-A3B-GGUF with Ollama:
```
ollama run hf.co/Hcompany/Holo-3.1-35B-A3B-GGUF:Q4_K_M
```

Unsloth Studio

How to use Hcompany/Holo-3.1-35B-A3B-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 Hcompany/Holo-3.1-35B-A3B-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 Hcompany/Holo-3.1-35B-A3B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Hcompany/Holo-3.1-35B-A3B-GGUF to start chatting

How to use Hcompany/Holo-3.1-35B-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 Hcompany/Holo-3.1-35B-A3B-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": "Hcompany/Holo-3.1-35B-A3B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use Hcompany/Holo-3.1-35B-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 Hcompany/Holo-3.1-35B-A3B-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 Hcompany/Holo-3.1-35B-A3B-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use Hcompany/Holo-3.1-35B-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 Hcompany/Holo-3.1-35B-A3B-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 "Hcompany/Holo-3.1-35B-A3B-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"

Docker Model Runner
How to use Hcompany/Holo-3.1-35B-A3B-GGUF with Docker Model Runner:
```
docker model run hf.co/Hcompany/Holo-3.1-35B-A3B-GGUF:Q4_K_M
```

Lemonade

How to use Hcompany/Holo-3.1-35B-A3B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Hcompany/Holo-3.1-35B-A3B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Holo-3.1-35B-A3B-GGUF-Q4_K_M

List all available models

lemonade list

maxime-hcompany commited on Jun 2

Commit

95dd544

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1 Parent(s): 7369368

Create README.md

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	@@ -0,0 +1,80 @@

+---
+license: apache-2.0
+language:
+- en
+base_model:
+- Qwen/Qwen3.6-35B-A3B
+- Qwen/Qwen3.5-9B
+- Qwen/Qwen3.5-4B
+- Qwen/Qwen3.5-0.8B
+pipeline_tag: image-text-to-text
+library_name: transformers
+tags:
+- multimodal
+- action
+- agent
+- pytorch
+- computer use
+- gui agents
+- moe
+---
+# **Holo3.1: Fast & Local Computer Use Agents**
+## **Model Description**
+**Holo3.1** is our latest family of Vision-Language Models (VLMs) for computer use agents. Building on Holo3, it expands support beyond browser and desktop automation to mobile environments, introduces native function-calling support for seamless integration with agent frameworks, and enables local deployment through optimized quantized checkpoints.
+The Holo3.1 family spans model sizes from 0.8B to 35B-A3B parameters.
+Across computer use, UI grounding, mobile automation, and business workflows, Holo3.1 delivers strong performance while improving deployment flexibility and cost efficiency.
+* **Developed by:** [**H Company**](https://www.hcompany.ai/)
+* **Model type:** Vision-Language Models for Navigation and Computer Use Agents
+* **Available models:** Holo3.1-0.8B, Holo3.1-4B, Holo3.1-9B, Holo3.1-35B-A3B
+* **Base models:** Qwen 3.5 family
+* **Supported environments:** Web, Desktop, Mobile
+* **Available quantizations for Holo3.1-35B-A3B:** BF16, FP8, NVFP4, Q4 GGUF
+* **Blog Post:** [hcompany.ai/holo3.1](https://www.hcompany.ai/holo3.1)
+* **Quickstart:** [hub.hcompany.ai/quickstart](https://hub.hcompany.ai/quickstart)
+* **License:** Apache 2.0 License
+### Performance vs Cost
+The figure below compares the overall performance and inference cost of the Holo3.1 and Qwen 3.5 families. Overall performance averages computer use, mobile automation, enterprise workflows, and UI grounding benchmarks.
+<p align="center">
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/69ce2739f4b9146a31e99a2f/0uU-6v68tSl3Kvd9jHWfS.png" width="700"/>
+</p>
+Holo3.1 establishes a strong Pareto frontier across model sizes, from lightweight local agents to state-of-the-art enterprise deployments.
+---
+## Benchmark Results
+Holo3.1 delivers strong performance across computer use, mobile automation, enterprise workflows, and UI grounding benchmarks.
+<div align="center">
+**Table 1: Evaluation results across computer use, mobile automation, enterprise workflows, and grounding benchmarks.**
+<img width="800" src="https://cdn-uploads.huggingface.co/production/uploads/69ce2739f4b9146a31e99a2f/eKbMPsY32AF4PCNzumeZQ.png"/>
+</div>
+## Get Started
+Explore our [Quickstart guide](https://hub.hcompany.ai/quickstart) to learn how to integrate Holo3.1 into your applications, deploy local agents, or run optimized inference on NVIDIA hardware.
+---
+## Citation
+```bibtex
+@misc{hai2026holo31,
+      title={Holo3.1: Fast & Local Computer Use Agents},
+      author={H Company},
+      year={2026},
+      url={https://huggingface.co/Hcompany/Holo3.1-35B-A3B},
+}