Instructions to use OpenVINO/Qwen3.5-35B-A3B-int4-ov with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OpenVINO/Qwen3.5-35B-A3B-int4-ov with Transformers:

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

pipe = pipeline("image-text-to-text", model="OpenVINO/Qwen3.5-35B-A3B-int4-ov")
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, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("OpenVINO/Qwen3.5-35B-A3B-int4-ov")
model = AutoModelForImageTextToText.from_pretrained("OpenVINO/Qwen3.5-35B-A3B-int4-ov")
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

vLLM

How to use OpenVINO/Qwen3.5-35B-A3B-int4-ov with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OpenVINO/Qwen3.5-35B-A3B-int4-ov"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OpenVINO/Qwen3.5-35B-A3B-int4-ov",
		"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/OpenVINO/Qwen3.5-35B-A3B-int4-ov

SGLang

How to use OpenVINO/Qwen3.5-35B-A3B-int4-ov 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 "OpenVINO/Qwen3.5-35B-A3B-int4-ov" \
    --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": "OpenVINO/Qwen3.5-35B-A3B-int4-ov",
		"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 "OpenVINO/Qwen3.5-35B-A3B-int4-ov" \
        --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": "OpenVINO/Qwen3.5-35B-A3B-int4-ov",
		"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 OpenVINO/Qwen3.5-35B-A3B-int4-ov with Docker Model Runner:
```
docker model run hf.co/OpenVINO/Qwen3.5-35B-A3B-int4-ov
```

Qwen3.5-35B-A3B-int4-ov

File size: 2,695 Bytes

0585c4e

{
  "dtype": "int4_int8_int8",
  "input_info": null,
  "optimum_version": "2.1.0.dev0",
  "output_attentions": false,
  "quantization_config": {
    "_dataset_kwargs": {},
    "dataset": null,
    "default_config": null,
    "ignored_scope": null,
    "num_samples": null,
    "processor": "/nfs/ov-share-01/data/cv_bench_cache/NATIVE_GEN-AI_MODELS/qwen3.5-35b-a3b/pytorch/NATIVE",
    "quantization_configs": {
      "lm_model": {
        "_dataset_kwargs": {},
        "all_layers": null,
        "backup_precision": null,
        "bits": 4,
        "dataset": null,
        "dq_group_size": null,
        "dtype": "int4",
        "gptq": null,
        "group_size": 128,
        "group_size_fallback": null,
        "ignored_scope": {
          "patterns": [
            ".*shared_expert.*",
            ".*attn.*"
          ]
        },
        "lora_correction": null,
        "num_samples": null,
        "processor": null,
        "quant_method": "default",
        "ratio": 1.0,
        "scale_estimation": null,
        "sensitivity_metric": null,
        "statistics_path": null,
        "sym": false,
        "tokenizer": null
      },
      "text_embeddings_model": {
        "_dataset_kwargs": {},
        "all_layers": null,
        "backup_precision": null,
        "bits": 8,
        "dataset": null,
        "dq_group_size": null,
        "dtype": "int8",
        "gptq": null,
        "group_size": null,
        "group_size_fallback": null,
        "ignored_scope": null,
        "lora_correction": null,
        "num_samples": null,
        "processor": null,
        "quant_method": "default",
        "ratio": 1.0,
        "scale_estimation": null,
        "sensitivity_metric": null,
        "statistics_path": null,
        "sym": true,
        "tokenizer": null,
        "weight_only": true
      },
      "vision_embeddings_merger_model": {
        "_dataset_kwargs": {},
        "all_layers": null,
        "backup_precision": null,
        "bits": 8,
        "dataset": null,
        "dq_group_size": null,
        "dtype": "int8",
        "gptq": null,
        "group_size": null,
        "group_size_fallback": null,
        "ignored_scope": null,
        "lora_correction": null,
        "num_samples": null,
        "processor": null,
        "quant_method": "default",
        "ratio": 1.0,
        "scale_estimation": null,
        "sensitivity_metric": null,
        "statistics_path": null,
        "sym": true,
        "tokenizer": null,
        "weight_only": true
      }
    },
    "tokenizer": "/nfs/ov-share-01/data/cv_bench_cache/NATIVE_GEN-AI_MODELS/qwen3.5-35b-a3b/pytorch/NATIVE"
  },
  "save_onnx_model": false,
  "transformers_version": "5.2.0"
}