edits, review

Author: dlepow

articles/api-management/media/openai-compatible-google-gemini-api/gemini-test.png

@@ -15,7 +15,7 @@ ms.custom: template-how-to
 
 [!INCLUDE [api-management-availability-all-tiers](../../includes/api-management-availability-all-tiers.md)]
 
-This article shows you how to import an OpenAI-compatible Google Gemini API to access models such as `gemini-2.5 -flash`. For these models, Azure API Management can manage an OpenAI-compatible chat completions endpoint.
+This article shows you how to import an OpenAI-compatible Google Gemini API to access models such as `gemini-2.5-flash-lite`. For these models, Azure API Management can manage an OpenAI-compatible chat completions endpoint.
 
 Learn more about managing AI APIs in API Management:
 
@@ -65,11 +65,11 @@ After importing the API, you can test the chat completions endpoint for the API.
 1. Select the API that you created in the previous step.
 1. Select the **Test** tab.
 1. Select the `POST  Creates a model response for the given chat conversation` operation, which is a `POST` request to the `/chat/completions` endpoint.
-1. In the **Request body** section, enter the following JSON to specify the model and an example prompt. In this example, the `gemini-2.5-flash` model is used.
+1. In the **Request body** section, enter the following JSON to specify the model and an example prompt. In this example, the `gemini-2.5-flash-lite` model is used.
 
     ```json
     {
-        "model": "gemini-2.5-flash",
+        "model": "gemini-2.5-flash-lite",
         "messages": [
             {
                 "role": "system",

articles/api-management/openai-compatible-google-gemini-api.md

@@ -15,15 +15,15 @@ ms.custom: template-how-to
 
 [!INCLUDE [api-management-availability-all-tiers](../../includes/api-management-availability-all-tiers.md)]
 
-You can import OpenAI-compatible language model endpoints or non-compatible models as passthrough APIs to your API Management instance. For example, manage self-hosted LLMs or those hosted on inference providers other than Azure AI services. Use AI gateway policies and other API Management capabilities to simplify integration, improve observability, and enhance control over model endpoints.
+You can import OpenAI-compatible language model endpoints to your API Management instance, or import non-compatible models as passthrough APIs. For example, manage self-hosted LLMs or those hosted on inference providers other than Azure AI services. Use AI gateway policies and other API Management capabilities to simplify integration, improve observability, and enhance control over model endpoints.
 
 Learn more about managing AI APIs in API Management:
 
 * [AI gateway capabilities in Azure API Management](genai-gateway-capabilities.md)
 
 ## Language model API types
 
-API Management supports two language model API types. Choose the option that matches your model deployment, which determines how clients call the API and how requests route to the AI service.
+API Management supports two language model API types. Choose the option that matches your model deployment, which determines how clients call the API and how requests get route to the AI service.
 
 * **OpenAI-compatible** - Language model endpoints compatible with OpenAI's API. Examples include [Hugging Face Text Generation Inference (TGI)](https://huggingface.co/docs/text-generation-inference/en/index) and [Google Gemini API](openai-compatible-google-gemini-api.md).