split up pricing info

Author: msakande

articles/ai-studio/how-to/deploy-models-cohere-rerank.md

@@ -30,10 +30,6 @@ Cohere offers rerank models in [Azure AI Foundry](https://ai.azure.com). These m
 
 You can browse the Cohere family of models in the [Model Catalog](model-catalog.md) by filtering on the Cohere collection.
 
-#### Pricing for Cohere Rerank models
-
-*Queries*, not to be confused with a user's query, is a pricing meter that refers to the cost associated with the tokens used as input for inference of a Cohere Rerank model. Cohere counts a single search unit as a query with up to 100 documents to be ranked. Documents longer than 4096 tokens when including the length of the search query are split up into multiple chunks, where each chunk counts as a single document.
-
 # [Cohere Rerank v3.5](#tab/cohere-rerank-3-5)
 
 Cohere Rerank 3.5 provides a significant boost to the relevancy of search results. This AI model, also known as a cross-encoder, precisely sorts lists of documents according to their semantic similarity to a provided query. This action allows information retrieval systems to go beyond keyword search, and also outperform traditional embedding models, surfacing the most contextually relevant data within end-user applications.  
@@ -43,6 +39,10 @@ Businesses use Cohere Rerank 3.5 to improve their enterprise search and retrieva
 - Context window of the model is 4,096 tokens
 - Max query length is 4,096 tokens
 
+#### Pricing for Cohere Rerank v3.5
+
+*Queries*, not to be confused with a user's query, is a pricing meter that refers to the cost associated with the tokens used as input for inference of a Cohere Rerank model. Cohere counts a single search unit as a query with up to 100 documents to be ranked. Documents longer than 500 tokens when including the length of the search query are split up into multiple chunks, where each chunk counts as a single document.
+
 # [Cohere Rerank v3 - English](#tab/cohere-rerank-3-en)
 
 Cohere Rerank English is a reranking model used for semantic search and retrieval-augmented generation (RAG). Rerank enables you to significantly improve search quality by augmenting traditional keyword-based search systems with a semantic-based reranking system that can contextualize the meaning of a user's query beyond keyword relevance. Cohere's Rerank delivers higher quality results than embedding-based search, lexical search, and even hybrid search, and it requires only adding a single line of code into your application.
@@ -56,6 +56,10 @@ Rerank supports JSON objects as documents where users can specify, at query time
 
 Rerank English works well for code retrieval, semi-structured data retrieval, and long context.
 
+#### Pricing for Cohere Rerank v3 English
+
+*Queries*, not to be confused with a user's query, is a pricing meter that refers to the cost associated with the tokens used as input for inference of a Cohere Rerank model. Cohere counts a single search unit as a query with up to 100 documents to be ranked. Documents longer than 4096 tokens when including the length of the search query are split up into multiple chunks, where each chunk counts as a single document.
+
 # [Cohere Rerank v3 - Multilingual](#tab/cohere-rerank-3-multi)
 
 Cohere Rerank Multilingual is a reranking model used for semantic search and retrieval-augmented generation (RAG). Rerank Multilingual supports more than 100 languages and can be used to search within a language (for example, to search with a French query on French documents) and across languages (for example, to search with an English query on Chinese documents). Rerank enables you to significantly improve search quality by augmenting traditional keyword-based search systems with a semantic-based reranking system that can contextualize the meaning of a user's query beyond keyword relevance. Cohere's Rerank delivers higher quality results than embedding-based search, lexical search, and even hybrid search, and it requires only adding a single line of code into your application.
@@ -69,6 +73,9 @@ Rerank supports JSON objects as documents where users can specify, at query time
 
 Rerank multilingual performs well on multilingual benchmarks such as Miracl.
 
+#### Pricing for Cohere Rerank v3 Multilingual
+
+*Queries*, not to be confused with a user's query, is a pricing meter that refers to the cost associated with the tokens used as input for inference of a Cohere Rerank model. Cohere counts a single search unit as a query with up to 100 documents to be ranked. Documents longer than 4096 tokens when including the length of the search query are split up into multiple chunks, where each chunk counts as a single document.
 ---
 
 ## Deploy Cohere Rerank models as serverless APIs