How many tokens does a Qwen2.5 VL image use?

Count tokens for one Qwen2.5 VL image at common resolutions, or measure your own image with the Qwen2.5 VL processor.

Image token counts depend on the model and its image processor. The table and code below are for Qwen2.5 VL.

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Common resolution token counts

The following table shows the token counts for a single image for Qwen2.5 VL at different image resolutions:

Resolution	Token Count
336×336	144
672×672	576
1024×1024	1,369
1280×720	1,196
1920×1080	2,769
2560×1440	4,641
3840×2160	10,549

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Calculating exact token count for your images

You can determine exact token usage by processing your images through the model’s tokenizer. For instance, for Qwen2.5 VL, you can use the following code:

1. Install dependencies

   pip install torch torchvision transformers pillow
   
2. Tokenize your image

   Tokenizing your image

   import requests
   from PIL import Image
   from transformers import AutoProcessor
   import os
   
   # Your image source - can be URL or local path
   IMAGE_URL_OR_PATH = "https://images.unsplash.com/photo-1519125323398-675f0ddb6308"
   
   def load_image(source):
       """Load image from URL or local file path"""
       if source.startswith(('http://', 'https://')):
           print(f"Downloading image from URL: {source}")
           response = requests.get(source)
           response.raise_for_status()
           return Image.open(requests.get(source, stream=True).raw)
       else:
           print(f"Loading image from path: {source}")
           if not os.path.exists(source):
               raise FileNotFoundError(f"Image file not found: {source}")
           return Image.open(source)
   
   def count_image_tokens(image):
       """Count how many tokens an image takes using Qwen 2.5 VL processor"""
       processor = AutoProcessor.from_pretrained("Qwen/Qwen2.5-VL-3B-Instruct")
       
       messages = [
           {
               "role": "user",
               "content": [
                   {"type": "image", "image": image},
                   {"type": "text", "text": "What's in this image?"},
               ],
           }
       ]
       
       text = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
       inputs = processor(text=text, images=[image], return_tensors="pt")
       input_ids = inputs["input_ids"][0]
       
       # Count the image pad tokens (151655 is Qwen2.5 VL's image token ID)
       image_tokens = (input_ids == 151655).sum().item()
       
       return image_tokens, input_ids
   
   def main():
       import sys
       
       image_source = sys.argv[1] if len(sys.argv) > 1 else IMAGE_URL_OR_PATH
       
       print(f"Processing image: {image_source}")
       image = load_image(image_source)
       print(f"Image size: {image.size}")
       print(f"Image mode: {image.mode}")
       
       print("\nCalculating tokens...")
       image_tokens, input_ids = count_image_tokens(image)
       
       print(f"Total tokens: {len(input_ids)}")
       print(f"Image tokens: {image_tokens}")
       print(f"Text tokens: {len(input_ids) - image_tokens}")
       
   if __name__ == "__main__":
       main()
   

   Usage

   # Calculate tokens for an image URL
   python token_calculator.py "https://example.com/image.jpg"
   
   # Calculate tokens for a local image
   python token_calculator.py "path/to/your/image.png"