Instructions to use ServiceNow/GroundNext-7B-V0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ServiceNow/GroundNext-7B-V0 with Transformers:

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

pipe = pipeline("image-text-to-text", model="ServiceNow/GroundNext-7B-V0")
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 AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("ServiceNow/GroundNext-7B-V0")
model = AutoModelForMultimodalLM.from_pretrained("ServiceNow/GroundNext-7B-V0", device_map="auto")
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?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ServiceNow/GroundNext-7B-V0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ServiceNow/GroundNext-7B-V0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ServiceNow/GroundNext-7B-V0",
		"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/ServiceNow/GroundNext-7B-V0

SGLang

How to use ServiceNow/GroundNext-7B-V0 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 "ServiceNow/GroundNext-7B-V0" \
    --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": "ServiceNow/GroundNext-7B-V0",
		"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 "ServiceNow/GroundNext-7B-V0" \
        --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": "ServiceNow/GroundNext-7B-V0",
		"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"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use ServiceNow/GroundNext-7B-V0 with Docker Model Runner:
```
docker model run hf.co/ServiceNow/GroundNext-7B-V0
```

feiziaarash commited on Nov 11, 2025

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@@ -48,20 +48,21 @@ For more details about the training methodology, dataset, and comprehensive benc
 ### Desktop Grounding Benchmarks
-|  | Qwen2.5-VL-7B | UI-TARS-72B | **GroundNext-7B-V0** |
-|--- | --- | --- | --- |
-| **ScreenSpot-Pro** | 27.6 | 38.1 | **48.9** |
-| **OSWorld-G** | 31.4 | 57.1 | **55.6** |
-| **UI-Vision** | 0.85 | 25.5 | **31.3** |
-| **Avg (Desktop)** | 19.9 | 40.2 | **45.3** |
-### Cross-Platform Generalization (Mobile & Web)
-|  | Qwen2.5-VL-7B | UI-TARS-72B | **GroundNext-7B-V0** |
-|--- | --- | --- | --- |
-| **MMBench-GUI** | 72.3 | 78.5 | **83.7** |
-| **ScreenSpot-v2** | 88.8 | 90.3 | **92.8** |
-| **Avg (Mobile/Web)** | 80.6 | 84.4 | **88.3** |
 ### Agentic Performance on OSWorld

 ### Desktop Grounding Benchmarks
+|                    | Qwen2.5-VL-7B | UI-TARS-72B | **GroundNext-7B-V0** |
+| ------------------ | ------------- | ----------- | ----------------- |
+| **ScreenSpot-Pro** | 29.7          | 38.1        | **52.9**          |
+| **OSWorld-G**      | 42.7          | 57.1        | **67.7**          |
+| **UI-Vision**      | 16.5          | 25.5        | **60.3**          |
+| **Avg**            | 29.6          | 40.2        | **60.3**          |
+### Cross-Platform Generalization (Desktop, Mobile & Web)
+|                      | Qwen2.5-VL-7B | UI-TARS-72B | **GroundNext-7B** |
+| -------------------- | ------------- | ----------- | ----------------- |
+| **MMBench-GUI**      | 33.9          | 74.3        | **81.1**          |
+| **ScreenSpot-v2**    | 88.8          | 90.3        | **90.4**          |
+| **Avg**              | 61.4          | 82.3        | **85.8**          |
 ### Agentic Performance on OSWorld