diff --git a/blogs/12_bfcl_v2_live.html b/blogs/12_bfcl_v2_live.html
index e072f870d..e3a23d609 100644
--- a/blogs/12_bfcl_v2_live.html
+++ b/blogs/12_bfcl_v2_live.html
@@ -213,6 +213,10 @@ <h3 id="intro">Introduction</h3>
                         demand for making parallel function calls in a single turn (parallel functions). Further, this
                         dataset helps us pin-point contamination in different models!
                     </p>
+                    <P>
+                        On Sept 19th, we released the BFCL V3 dataset, featuring multi-turn & multi-step function calling evaluation.
+                        Checkout the <a href="https://gorilla.cs.berkeley.edu/blogs/13_bfcl_v3_multi_turn.html">BFCL V3 Blog Post</a> for more details!
+                    </P>
                     <p>
                         Quick Links:
                         <ul>
diff --git a/blogs/13_bfcl_v3_multi_turn.html b/blogs/13_bfcl_v3_multi_turn.html
index e1e11f035..2c28526e5 100644
--- a/blogs/13_bfcl_v3_multi_turn.html
+++ b/blogs/13_bfcl_v3_multi_turn.html
@@ -209,7 +209,7 @@ <h3 id="intro">Introduction</h3>
             file, and list the directory again... You will ask LLM to make a social media post.
             LLM will force you to spell your username and password to login despite the fact that you are already
             browsing other people's posts! This is only possible with <strong>multi-turn</strong>,
-            and <strong>multi-step</strong> function calling (tool usage). <i>Note that BFCL V3 contains the Expert Curated (Non-live) dataset introduced in <a href="https://gorilla.cs.berkeley.edu/blogs/8_berkeley_function_calling_leaderboard.html">BFCL V1</a> and User Contributed (Live) dataset introduced in <a href="https://gorilla.cs.berkeley.edu/blogs/8_berkeley_function_calling_leaderboard.html">BFCL V2</a> and the multi-turn, and multi-step category introduced in BFCL V3.</i>
+            and <strong>multi-step</strong> function calling (tool usage). <i>Note that BFCL V3 contains the Expert Curated (Non-live) dataset introduced in <a href="https://gorilla.cs.berkeley.edu/blogs/8_berkeley_function_calling_leaderboard.html">BFCL V1</a> and User Contributed (Live) dataset introduced in <a href="https://gorilla.cs.berkeley.edu/blogs/12_bfcl_v2_live.html">BFCL V2</a> and the multi-turn, and multi-step category introduced in BFCL V3.</i>
           </p>
           <p>
               Understanding these more advanced interactions builds on the foundation of single-turn single-step function calling, where models takes an user input prompt and selects one or more functions with appropriately filled parameters from a set of provided function options, without further interaction. If you're unfamiliar with single-turn single-step function calling and the evaluation metrics we used, check out our <a href="https://gorilla.cs.berkeley.edu/blogs/8_berkeley_function_calling_leaderboard.html">earlier blog</a> on single-turn single-step function calling for a deeper dive.
diff --git a/blogs/8_berkeley_function_calling_leaderboard.html b/blogs/8_berkeley_function_calling_leaderboard.html
index f51a2b934..f99cdecaa 100644
--- a/blogs/8_berkeley_function_calling_leaderboard.html
+++ b/blogs/8_berkeley_function_calling_leaderboard.html
@@ -129,6 +129,9 @@ <h4 class="text-center" style="margin: 0px;">
                         On Aug 19th, 2024, we released the BFCL V2 dataset, featuring enterprise-contributed data, 
                         tackling issues like bias and data contamination, and focuses on dynamic, real-world scenarios. 
                         Check out the <i>BFCL V2 · Live </i><a href="https://gorilla.cs.berkeley.edu/blogs/12_bfcl_v2_live.html">Blog Post</a> for more details.
+                        <br>
+                        On Sept 19th, we released the BFCL V3 dataset, featuring multi-turn & multi-step function calling evaluation.
+                        Checkout the <a href="https://gorilla.cs.berkeley.edu/blogs/13_bfcl_v3_multi_turn.html">BFCL V3 Blog Post</a> for more details!
                     </p>
                     <p>
                         Quick Links: