Update wording for image tokens in high res mode

Author: jamesmcroft

articles/ai-services/openai/overview.md

@@ -93,9 +93,9 @@ Azure OpenAI's image processing capabilities with GPT-4o, GPT-4o mini, and GPT-4
   - Low detail allows the API to return faster responses for scenarios that don't require high image resolution analysis. The tokens consumed for low detail images are:
     - **GPT-4o and GPT-4 Turbo with Vision**: Flat rate of **85 tokens per image**, regardless of size.
     - **GPT-4o mini**: Flat rate of **2833 tokens per image**, regardless of size.
-  - **Example: 4096 x 8192 image (low detail)**: The cost is a fixed 85 tokens, because it's a low detail image, and the size doesn't affect the cost in this mode.
+  - **Example: 4096 x 8192 image (low detail)**: The cost is a fixed 85 tokens with GPT-4o, because it's a low detail image, and the size doesn't affect the cost in this mode.
 - **High resolution mode**
-  - Low detail allows the API to analyze images in more detail. Image tokens are calculated based on the image's dimensions. The calculation involves the following steps:
+  - High detail allows the API to analyze images in more detail. Image tokens are calculated based on the image's dimensions. The calculation involves the following steps:
     1. **Image resizing**: The image is resized to fit within a 2048 x 2048 pixel square. If the shortest side is larger than 768 pixels, the image is further resized so that the shortest side is 768 pixels long. The aspect ratio is preserved during resizing.
     1. **Tile calculation**: Once resized, the image is divided into 512 x 512 pixel tiles. Any partial tiles are rounded up to a full tile. The number of tiles determines the total token cost.
     1. **Token calculation**:
@@ -139,4 +139,4 @@ Learn more about each model on our [models concept page](./concepts/models.md).
 
 ## Next steps
 
-Learn more about the [underlying models that power Azure OpenAI](./concepts/models.md).
+Learn more about the [underlying models that power Azure OpenAI](./concepts/models.md).