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Author: msakande

articles/ai-foundry/concepts/model-benchmarks.md

@@ -19,9 +19,10 @@ author: msakande
 
 
 Model leaderboards in Azure AI Foundry portal allow you to streamline the model selection process in the Azure AI Foundry [model catalog](../how-to/model-catalog-overview.md). The model leaderboards, backed by industry-standard benchmarks can help you to find the best model for your custom AI solution. From the model leaderboards section of the model catalog, you can [browse leaderboards](https://aka.ms/model-leaderboards) to compare available models as follows:
-- [Quality, cost, and performance leaderboards](#quality-cost-and-performance-leaderboards) to quickly identify the model leaders along a single metric (quality, cost, or throughput);
-- [Trade-off charts](#trade-off-charts) to see how models perform on one metric versus another, such as quality versus cost;
-- [Leaderboards by scenario](#leaderboards-by-scenario) to find the best leaderboards that suite your scenario.
+
+- **Quality, cost, and performance leaderboards** to quickly identify the model leaders along a single metric (quality, cost, or throughput);
+- **Trade-off charts** to see how models perform on one metric versus another, such as quality versus cost;
+- **Leaderboards by scenario** to find the best leaderboards that suite your scenario.
 
 Whenever you find a model to your liking, you can select it and zoom into the [detailed benchmarking results](../how-to
 /benchmark-model-in-catalog.md) of the model within the model catalog. If satisfied with the model, you can deploy it, try it in the playgorund, or evaluate it on your data. The leaderboards support benchmarking across text language models (large language models (LLMs) and small language models (SLMs)) and embedding models.
@@ -138,5 +139,5 @@ Prompt construction follows best practices for each dataset, as specified by the
 
 ## Related content
 
-- [How to benchmark models in Azure AI Foundry portal](../how-to/benchmark-model-in-catalog.md)
+- [Select models using the model leaderboard in Azure AI Foundry portal](../how-to/benchmark-model-in-catalog.md)
 - [Model catalog and collections in Azure AI Foundry portal](../how-to/model-catalog-overview.md)

articles/ai-foundry/how-to/benchmark-model-in-catalog.md

@@ -36,7 +36,7 @@ In this article, you learn to streamline your model selection process in the Azu
 
 4. Go to the **Model leaderboards** section of the model catalog. This section displays the top three model leaders ranked along [quality](#quality), [cost](#cost), and [performance](#cost). You can select any of these models to check out more details.
 
-    :::image type="content" source="../media/how-to/model-benchmarks/leaderboard-entry-select-model.png" alt-text="Screenshot showing the selected model from entry point of leaderboards on model catalog." lightbox="../media/how-to/model-benchmarks/leaderboard-entry-select-model.png":::
+    :::image type="content" source="../media/how-to/model-benchmarks/leaderboard-entry-select-model.png" alt-text="Screenshot showing the selected model from entry point of leaderboards on model catalog homepage." lightbox="../media/how-to/model-benchmarks/leaderboard-entry-select-model.png":::
 
 1. From the **Model leaderboards** section of the model catalog, select **Browse leaderboards**  to go to the [model leaderboards landing page](https://aka.ms/model-leaderboards) to see the full suite of leaderboards that are available. [Quality](#quality) is the most common criterion for model selection, followed by cost and performance.
 
@@ -109,6 +109,6 @@ The previous sections showed the benchmark results calculated by Microsoft, usin
 
 ## Related content
 
-- [Model benchmarks in Azure AI Foundry portal](../concepts/model-benchmarks.md)
+- [Model leaderboards in Azure AI Foundry portal](../concepts/model-benchmarks.md)
 - [How to evaluate generative AI apps with Azure AI Foundry](evaluate-generative-ai-app.md)
 - [How to view evaluation results in Azure AI Foundry portal](evaluate-results.md)

articles/ai-foundry/media/how-to/model-benchmarks/leaderboard-by-scenario.png

@@ -42,11 +42,11 @@ items:
     href: how-to/concept-data-privacy.md
   - name: Model lifecycle and retirement
     href: concepts/model-lifecycle-retirement.md
-  - name: Model benchmarking
+  - name: Model leaderboards and benchmarking
     items:
-    - name: Model benchmarks
+    - name: Model leaderboards
       href: concepts/model-benchmarks.md
-    - name: How to use model benchmarking
+    - name: How to use model leaderboards
       href: how-to/benchmark-model-in-catalog.md
   - name: Model deployment in Azure AI Foundry
     items: