diff --git a/modules/search/pages/field-data-types-reference.adoc b/modules/search/pages/field-data-types-reference.adoc
index ed9f776fc..6ffbc595b 100644
--- a/modules/search/pages/field-data-types-reference.adoc
+++ b/modules/search/pages/field-data-types-reference.adoc
@@ -80,9 +80,17 @@ For example:
 
 |vector a|
 
-The field contains an array of floating point numbers. 
+The field contains an array of floating point numbers or an array of arrays that represent a vector embedding. 
 
 Use the `vector` type to perform vector similarity searches with Vector Search. 
 
+For more information about Vector Search, see xref:vector-search:vector-search.adoc[].
+
+|(Server version 7.6.2 and later) vector_base64 a|
+
+The field contains an array of floating point numbers formatted as a base64 encoded string that represent a vector embedding.
+
+Use the `vector_base64` type to perform vector similarity searches with Vector Search. 
+
 For more information about Vector Search, see xref:vector-search:vector-search.adoc[].
 |====
\ No newline at end of file
diff --git a/modules/search/pages/search-index-params.adoc b/modules/search/pages/search-index-params.adoc
index b4d4cb49e..647d898bc 100644
--- a/modules/search/pages/search-index-params.adoc
+++ b/modules/search/pages/search-index-params.adoc
@@ -1049,6 +1049,7 @@ The child field's type. Can be one of:
 * `disabled`
 * `ip`
 * `vector`
+* (Server version 7.6.2 and later) `vector_base64`
 
 For more information about the available field data types, see xref:field-data-types-reference.adoc[].
 
diff --git a/modules/search/pages/search-request-params.adoc b/modules/search/pages/search-request-params.adoc
index 4104a12a9..4fc372424 100644
--- a/modules/search/pages/search-request-params.adoc
+++ b/modules/search/pages/search-request-params.adoc
@@ -167,7 +167,7 @@ An object in the `knn` array can contain the following properties:
 
 Enter the total number of results that you want to return from your Vector Search query. 
 
-The Search Service returns the `k` closest vectors to the vector given in `vector`.
+The Search Service returns the `k` closest vectors to the vector given in `vector` or, if your database is running Couchbase Server version 7.6.2 or later, `vector_base64`.
 
 NOTE: The <<size-limit,size or limit property>> overrides any value set in `k`.
 
@@ -175,7 +175,7 @@ NOTE: The <<size-limit,size or limit property>> overrides any value set in `k`.
 
 The name of the field that contains the vector data you want to search. 
 
-|vector |Array of Floats |Yes a| 
+|vector |Array of Floats |Must have `vector` or `vector_base64` a| 
 
 Enter the vector that you want to compare to the vector data in `field`.
 
@@ -185,6 +185,16 @@ NOTE: The vector in your Search query must match the dimension of the vectors st
 If the dimensions do not match, your Search query does not return any results.
 For more information about the dimension value, see the xref:search-index-params.adoc#dims[dims property] or the xref:child-field-options-reference.adoc#dimension[Dimension option] in the UI. 
 
+|vector_base64 |Base64 Encoded String |Must have `vector` or `vector_base64` a|
+
+If your database is running Couchbase Server version 7.6.2 or later, enter a vector, encoded as a base64 string, that you want to compare to the vector data in `field`. 
+
+The Search Service uses the similarity metric defined in the xref:search-index-params.adoc#similarity[Search index definition] to return the `k` closest vectors from the Search index.
+
+NOTE: The vector in your Search query must match the dimension of the vectors stored in your Search index. 
+If the dimensions do not match, your Search query does not return any results.
+For more information about the dimension value, see the xref:search-index-params.adoc#dims[dims property] or the xref:child-field-options-reference.adoc#dimension[Dimension option] in the UI. 
+
 |====
 
 [#query-object]
diff --git a/modules/vector-search/examples/run-vector-search-payload-base64-ui.jsonc b/modules/vector-search/examples/run-vector-search-payload-base64-ui.jsonc
new file mode 100644
index 000000000..b340251f1
--- /dev/null
+++ b/modules/vector-search/examples/run-vector-search-payload-base64-ui.jsonc
@@ -0,0 +1,10 @@
+{
+    "fields": ["*"],
+    "knn": [
+      {
+        "field": "embedding_vector_dot",
+        "k": 3,
+        "vector_base64": "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"
+      }
+    ]
+}
\ No newline at end of file
diff --git a/modules/vector-search/examples/vector-search-base64-document-example.json b/modules/vector-search/examples/vector-search-base64-document-example.json
new file mode 100644
index 000000000..6a76dc8e9
--- /dev/null
+++ b/modules/vector-search/examples/vector-search-base64-document-example.json
@@ -0,0 +1,15 @@
+{
+    "id": "#000080",
+    "color": "navy",
+    "brightness": 14.592,
+    "colorvect_l2": "AACA",
+    "wheel_pos": "other",
+    "verbs": [
+        "deep",
+        "rich",
+        "sophisticated"
+    ],
+    "description": "Navy is a deep, rich color that exudes sophistication. It is a dark shade of blue that is often associated with authority, stability, and elegance. Navy is a versatile color that can be both bold and understated, making it a popular choice in fashion and interior design. It is a timeless color that never goes out of style and adds a touch of sophistication to any look or space.",
+    "embedding_model": "text-embedding-ada-002-v2",
+    "embedding_vector_dot": "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"
+},
\ No newline at end of file
diff --git a/modules/vector-search/pages/create-vector-search-index-ui.adoc b/modules/vector-search/pages/create-vector-search-index-ui.adoc
index c1662c2a5..44256ec1b 100644
--- a/modules/vector-search/pages/create-vector-search-index-ui.adoc
+++ b/modules/vector-search/pages/create-vector-search-index-ui.adoc
@@ -22,6 +22,7 @@ For more information about how to deploy a new node and Services on your databas
 For more information about how to create a bucket, see xref:server:manage:manage-buckets/create-bucket.adoc[]. 
 
 * You have documents in a keyspace inside your bucket that contain vector embeddings.
+Embeddings can be an array of floats or a base64 encoded string. 
 +
 [TIP]
 --
@@ -61,15 +62,17 @@ You cannot have 2 indexes with the same name inside the same bucket and scope.
 .. In the *Field* field, enter the name of the field in your documents that contains your vector embeddings.
 +
 Vectors must be represented as an array of floating point numbers. 
-.. In the *Type* list, select *vector*. 
+.. In the *Type* list, do one of the following:
+... If your child field contains vector embeddings as an array, click *vector*.
+... (Couchbase Server version 7.6.2 or later) If your child field contains vector embeddings formatted as a base64 encoded string, click *vector_base64*. 
 .. In the *Dimension* field, enter the total number of elements in the array that holds the vector embeddings for your documents.
 + 
 The Search Service supports arrays up to 2048 elements.
 Arrays can be an array of arrays.  
-.. In the *Similarity metric* list, select the method to use to calculate the similarity between search term and Search index vectors.
+.. In the *Similarity metric* list, choose the method to use to calculate the similarity between search term and Search index vectors.
 + 
 For more information, see xref:search:child-field-options-reference.adoc[].
-.. In the *Optimized for* list, select whether the Search Service should optimize Search queries for accuracy (*recall*) or speed (*latency*).
+.. In the *Optimized for* list, choose whether the Search Service should optimize Search queries for accuracy (*recall*) or speed (*latency*).
 +
 For more information, see xref:search:child-field-options-reference.adoc[].
 .. Select *Index*.
@@ -77,6 +80,7 @@ For more information, see xref:search:child-field-options-reference.adoc[].
 . (Optional) xref:search:create-child-field.adoc[Create another child field] on the new collection type mapping for any additional fields you want to return in your search results.
 +
 For example, you could add the text field that you used to generate your vector embeddings. 
+. Next to the `default` dynamic type mapping, clear the checkbox. 
 . Click btn:[Create Index].
 
 [#example]
@@ -105,6 +109,9 @@ If you choose to add additional child fields and enable *Include in search resul
 
 For more information about how to add additional child fields to your index, see xref:search:create-quick-index.adoc[] or xref:search:create-child-field.adoc[].
 
+For example, if you used the Vector Search sample data, you might want to add another child field for the *color* string field to your Vector Search index, to return color names with your Search query.
+For more information about how to add additional child fields to your index, see xref:search:create-child-field.adoc[].
+
 You can customize your Vector Search index like any other Search index to add additional data and improve search results. 
 For more information about how to customize an index, see xref:search:customize-index.adoc[].
 
diff --git a/modules/vector-search/pages/run-vector-search-ui.adoc b/modules/vector-search/pages/run-vector-search-ui.adoc
index 6ac775605..fd573b11a 100644
--- a/modules/vector-search/pages/run-vector-search-ui.adoc
+++ b/modules/vector-search/pages/run-vector-search-ui.adoc
@@ -102,6 +102,27 @@ Click btn:[View on GitHub] to view and copy the entire Vector Search query paylo
 Make sure you remove the lines for `// tag::partial[]` and `// end::partial[]`.
 ==== 
 
+[#base64]
+=== Example: Running a Semantic Search Query with a base64 Encoded String 
+
+If your database is running Couchbase Server version 7.6.2 or later, you can use vectors encoded as base64 strings with Vector Search. 
+For example, the following document describes the color `navy`, with base64 encoded strings in the `embedding_vector_dot` and `colorvect_l2` fields instead of arrays: 
+
+[source,json]
+----
+include::example$vector-search-base64-document-example.json[]
+----
+
+The following query uses a base64 encoded string for the same query as <<large,Running a Semantic Search Query with a Large Embedding Vector>> to return the document for `navy`: 
+
+[source,json]
+----
+include::example$run-vector-search-payload-base64-ui.jsonc[]
+----
+
+NOTE: You can use base64 encoded strings in your Vector Search queries only if your documents use base64 encoded strings, indexed with the *vector_base64* field data type.
+You cannot search for and return vectors you indexed as arrays with the *vector* field data type by using a Search query with a base64 encoded string. 
+
 == Next Steps 
 
 If you do not get the search results you were expecting, you can change the xref:search:search-request-params.adoc[JSON payload for your Search query].