diff --git a/docs/remote_inference_blueprints/bedrock_connector_nova_multimodal_model_blueprint.md b/docs/remote_inference_blueprints/bedrock_connector_nova_multimodal_model_blueprint.md
new file mode 100644
index 0000000000..09bd124d2d
--- /dev/null
+++ b/docs/remote_inference_blueprints/bedrock_connector_nova_multimodal_model_blueprint.md
@@ -0,0 +1,573 @@
+# Bedrock connector blueprint example for Nova MultiModal Model
+
+## 1. Create connector for Amazon Bedrock:
+
+Note: Different modality types require separate connectors. Create one connector for each modality you plan to use: text embedding, image embedding, video embedding, or audio embedding.
+
+
+### Text Embedding
+
+If you are using self-managed Opensearch, you should supply AWS credentials:
+
+```json
+POST /_plugins/_ml/connectors/_create
+{
+    "name": "Amazon Bedrock Nova multimodal model - text embedding",
+    "description": "Test connector for Amazon Bedrock Nova multimodal model - text embedding",
+    "version": 1,
+    "protocol": "aws_sigv4",
+    "credential": {
+        "access_key": "<PLEASE ADD YOUR AWS ACCESS KEY HERE>",
+        "secret_key": "<PLEASE ADD YOUR AWS SECRET KEY HERE>",
+        "session_token": "<PLEASE ADD YOUR AWS SECURITY TOKEN HERE>"
+    },
+    "parameters": {
+        "region": "<PLEASE ADD YOUR AWS REGION HERE>",
+        "service_name": "bedrock",
+        "model": "amazon.nova-2-multimodal-embeddings-v1:0",
+        "input_docs_processed_step_size": 1,
+        "dimensions": 1024,
+        "normalize": true,
+        "embeddingTypes": [
+            "float"
+        ],
+        "truncationMode": "<START|END|NONE>"
+    },
+    "actions": [
+        {
+            "action_type": "predict",
+            "method": "POST",
+            "headers": {
+                "content-type": "application/json",
+                "x-amz-content-sha256": "required"
+            },
+            "url": "https://bedrock-runtime.${parameters.region}.amazonaws.com/model/${parameters.model}/invoke",
+            "request_body": "{\n  \"taskType\": \"SINGLE_EMBEDDING\",\n  \"singleEmbeddingParams\": {\n  \"embeddingPurpose\": \"GENERIC_INDEX\",\n   \"embeddingDimension\": ${parameters.dimensions},\n    \"text\": {\n      \"truncationMode\": \"${parameters.truncationMode}\",\n      \"value\": \"${parameters.inputText}\"\n    }\n  }\n}",
+            "pre_process_function": "connector.pre_process.bedrock.nova.text_embedding",
+            "post_process_function": "connector.post_process.bedrock.nova.embedding"
+        }
+    ]
+}
+```
+
+If using the AWS Opensearch Service, you can provide an IAM role arn that allows access to the bedrock service.
+Refer to this [AWS doc](https://docs.aws.amazon.com/opensearch-service/latest/developerguide/ml-amazon-connector.html) 
+
+```json
+POST /_plugins/_ml/connectors/_create
+{
+    "name": "Amazon Bedrock Nova multimodal model - text embedding",
+    "description": "Test connector for Amazon Bedrock Nova multimodal model - text embedding",
+    "version": 1,
+    "protocol": "aws_sigv4",
+    "credential": {
+        "roleArn": "<PLEASE ADD YOUR AWS ROLE ARN HERE>"
+    },
+    "parameters": {
+        "region": "<PLEASE ADD YOUR AWS REGION HERE>",
+        "service_name": "bedrock",
+        "model": "amazon.nova-2-multimodal-embeddings-v1:0",
+        "input_docs_processed_step_size": 1,
+        "dimensions": 1024,
+        "normalize": true,
+        "embeddingTypes": [
+            "float"
+        ],
+        "truncationMode": "<START|END|NONE>"
+    },
+    "actions": [
+        {
+            "action_type": "predict",
+            "method": "POST",
+            "headers": {
+                "content-type": "application/json",
+                "x-amz-content-sha256": "required"
+            },
+            "url": "https://bedrock-runtime.${parameters.region}.amazonaws.com/model/${parameters.model}/invoke",
+            "request_body": "{\n  \"taskType\": \"SINGLE_EMBEDDING\",\n  \"singleEmbeddingParams\": {\n  \"embeddingPurpose\": \"GENERIC_INDEX\",\n   \"embeddingDimension\": ${parameters.dimensions},\n    \"text\": {\n      \"truncationMode\": \"${parameters.truncationMode}\",\n      \"value\": \"${parameters.inputText}\"\n    }\n  }\n}",
+            "pre_process_function": "connector.pre_process.bedrock.nova.text_embedding",
+            "post_process_function": "connector.post_process.bedrock.nova.embedding"
+        }
+    ]
+}
+```
+
+### Image Embedding
+
+If you are using self-managed Opensearch, you should supply AWS credentials:
+
+```json
+POST /_plugins/_ml/connectors/_create
+{
+    "name": "Amazon Bedrock Nova multimodal model - image embedding",
+    "description": "Test connector for Amazon Bedrock Nova multimodal model - image embedding",
+    "version": 1,
+    "protocol": "aws_sigv4",
+    "credential": {
+        "access_key": "<PLEASE ADD YOUR AWS ACCESS KEY HERE>",
+        "secret_key": "<PLEASE ADD YOUR AWS SECRET KEY HERE>",
+        "session_token": "<PLEASE ADD YOUR AWS SECURITY TOKEN HERE>"
+    },
+    "parameters": {
+        "region": "<PLEASE ADD YOUR AWS REGION HERE>",
+        "service_name": "bedrock",
+        "model": "amazon.nova-2-multimodal-embeddings-v1:0",
+        "input_docs_processed_step_size": 1,
+        "dimensions": 1024,
+        "normalize": true,
+        "embeddingTypes": [
+           "float"
+        ],
+        "imageFormat": "<png|jpeg|gif|webp>",
+        "detailLevel": "<STANDARD_IMAGE|DOCUMENT_IMAGE>"
+    },
+    "actions": [
+        {
+            "action_type": "predict",
+            "method": "POST",
+            "headers": {
+                "content-type": "application/json",
+                "x-amz-content-sha256": "required"
+            },
+            "url": "https://bedrock-runtime.${parameters.region}.amazonaws.com/model/${parameters.model}/invoke",
+            "request_body": "{\n  \"taskType\": \"SINGLE_EMBEDDING\",\n  \"singleEmbeddingParams\": {\n  \"embeddingPurpose\": \"IMAGE_RETRIEVAL\",\n \"embeddingDimension\": ${parameters.dimensions},\n    \"image\": {\n      \"format\": \"${parameters.imageFormat}\",\n      \"detailLevel\": \"${parameters.detailLevel}\",\n      \"source\": {\n        \"bytes\": \"${parameters.inputImage}\"\n      }\n    }\n  }\n}",
+            "pre_process_function": "connector.pre_process.bedrock.nova.image_embedding",
+            "post_process_function": "connector.post_process.bedrock.nova.embedding"
+        }
+    ]
+}
+```
+
+If using the AWS Opensearch Service, you can provide an IAM role arn that allows access to the bedrock service.
+Refer to this [AWS doc](https://docs.aws.amazon.com/opensearch-service/latest/developerguide/ml-amazon-connector.html)
+
+```json
+POST /_plugins/_ml/connectors/_create
+{
+    "name": "Amazon Bedrock Nova multimodal model - image embedding",
+    "description": "Test connector for Amazon Bedrock Nova multimodal model - image embedding",
+    "version": 1,
+    "protocol": "aws_sigv4",
+    "credential": {
+        "roleArn": "<PLEASE ADD YOUR AWS ROLE ARN HERE>"
+    },
+    "parameters": {
+        "region": "<PLEASE ADD YOUR AWS REGION HERE>",
+        "service_name": "bedrock",
+        "model": "amazon.nova-2-multimodal-embeddings-v1:0",
+        "input_docs_processed_step_size": 1,
+        "dimensions": 1024,
+        "normalize": true,
+        "embeddingTypes": [
+            "float"
+        ],
+        "imageFormat": "<png|jpeg|gif|webp>",
+        "detailLevel": "<STANDARD_IMAGE|DOCUMENT_IMAGE>"
+    },
+    "actions": [
+        {
+            "action_type": "predict",
+            "method": "POST",
+            "headers": {
+                "content-type": "application/json",
+                "x-amz-content-sha256": "required"
+            },
+            "url": "https://bedrock-runtime.${parameters.region}.amazonaws.com/model/${parameters.model}/invoke",
+            "request_body": "{\n  \"taskType\": \"SINGLE_EMBEDDING\",\n  \"singleEmbeddingParams\": {\n  \"embeddingPurpose\": \"IMAGE_RETRIEVAL\",\n \"embeddingDimension\": ${parameters.dimensions},\n    \"image\": {\n      \"format\": \"${parameters.imageFormat}\",\n      \"detailLevel\": \"${parameters.detailLevel}\",\n      \"source\": {\n        \"bytes\": \"${parameters.inputImage}\"\n      }\n    }\n  }\n}",
+            "pre_process_function": "connector.pre_process.bedrock.nova.image_embedding",
+            "post_process_function": "connector.post_process.bedrock.nova.embedding"
+        }
+    ]
+}
+```
+
+### Video Embedding
+
+If you are using self-managed Opensearch, you should supply AWS credentials:
+
+```json
+POST /_plugins/_ml/connectors/_create
+{
+    "name": "Amazon Bedrock Nova multimodal model - video embedding",
+    "description": "Test connector for Amazon Bedrock Nova multimodal model - video embedding",
+    "version": 1,
+    "protocol": "aws_sigv4",
+    "credential": {
+        "access_key": "<PLEASE ADD YOUR AWS ACCESS KEY HERE>",
+        "secret_key": "<PLEASE ADD YOUR AWS SECRET KEY HERE>",
+        "session_token": "<PLEASE ADD YOUR AWS SECURITY TOKEN HERE>"
+    },
+    "parameters": {
+        "region": "<PLEASE ADD YOUR AWS REGION HERE>",
+        "service_name": "bedrock",
+        "model": "amazon.nova-2-multimodal-embeddings-v1:0",
+        "input_docs_processed_step_size": 1,
+        "dimensions": 1024,
+        "normalize": true,
+        "embeddingTypes": [
+            "float"
+        ],
+        "videoFormat": "<mp4|mov|mkv|webm|flv|mpeg|mpg|wmv|3gp>",
+        "embeddingMode": "<AUDIO_VIDEO_COMBINED|AUDIO_VIDEO_SEPARATE>"
+    },
+    "actions": [
+        {
+            "action_type": "predict",
+            "method": "POST",
+            "headers": {
+                "content-type": "application/json",
+                "x-amz-content-sha256": "required"
+            },
+            "url": "https://bedrock-runtime.${parameters.region}.amazonaws.com/model/${parameters.model}/invoke",
+            "request_body": "{\n  \"taskType\": \"SINGLE_EMBEDDING\",\n  \"singleEmbeddingParams\": {\n \"embeddingPurpose\": \"VIDEO_RETRIEVAL\",       \"embeddingDimension\": ${parameters.dimensions},\n        \"video\": {\n            \"format\": \"${parameters.videoFormat}\",\n            \"embeddingMode\": \"${parameters.embeddingMode}\",\n            \"source\": {\n                \"bytes\": \"${parameters.inputVideo}\"\n            }\n        }\n    }\n}",
+            "pre_process_function": "connector.pre_process.bedrock.nova.video_embedding",
+            "post_process_function": "connector.post_process.bedrock.nova.embedding"
+        }
+    ]
+}
+```
+
+If using the AWS Opensearch Service, you can provide an IAM role arn that allows access to the bedrock service.
+Refer to this [AWS doc](https://docs.aws.amazon.com/opensearch-service/latest/developerguide/ml-amazon-connector.html)
+
+```json
+POST /_plugins/_ml/connectors/_create
+{
+    "name": "Amazon Bedrock Nova multimodal model - video embedding",
+    "description": "Test connector for Amazon Bedrock Nova multimodal model - video embedding",
+    "version": 1,
+    "protocol": "aws_sigv4",
+    "credential": {
+        "roleArn": "<PLEASE ADD YOUR AWS ROLE ARN HERE>"
+    },
+    "parameters": {
+        "region": "<PLEASE ADD YOUR AWS REGION HERE>",
+        "service_name": "bedrock",
+        "model": "amazon.nova-2-multimodal-embeddings-v1:0",
+        "input_docs_processed_step_size": 1,
+        "dimensions": 1024,
+        "normalize": true,
+        "embeddingTypes": [
+            "float"
+        ],
+        "videoFormat": "<mp4|mov|mkv|webm|flv|mpeg|mpg|wmv|3gp>",
+        "embeddingMode": "<AUDIO_VIDEO_COMBINED|AUDIO_VIDEO_SEPARATE>"
+    },
+    "actions": [
+        {
+            "action_type": "predict",
+            "method": "POST",
+            "headers": {
+                "content-type": "application/json",
+                "x-amz-content-sha256": "required"
+            },
+            "url": "https://bedrock-runtime.${parameters.region}.amazonaws.com/model/${parameters.model}/invoke",
+            "request_body": "{\n  \"taskType\": \"SINGLE_EMBEDDING\",\n  \"singleEmbeddingParams\": {\n \"embeddingPurpose\": \"VIDEO_RETRIEVAL\",       \"embeddingDimension\": ${parameters.dimensions},\n        \"video\": {\n            \"format\": \"${parameters.videoFormat}\",\n            \"embeddingMode\": \"${parameters.embeddingMode}\",\n            \"source\": {\n                \"bytes\": \"${parameters.inputVideo}\"\n            }\n        }\n    }\n}",
+            "pre_process_function": "connector.pre_process.bedrock.nova.video_embedding",
+            "post_process_function": "connector.post_process.bedrock.nova.embedding"
+        }
+    ]
+}
+```
+
+### Audio Embedding
+
+If you are using self-managed Opensearch, you should supply AWS credentials:
+
+```json
+POST /_plugins/_ml/connectors/_create
+{
+    "name": "Amazon Bedrock Nova multimodal model - audio embedding",
+    "description": "Test connector for Amazon Bedrock Nova multimodal model - audio embedding",
+    "version": 1,
+    "protocol": "aws_sigv4",
+    "credential": {
+        "access_key": "<PLEASE ADD YOUR AWS ACCESS KEY HERE>",
+        "secret_key": "<PLEASE ADD YOUR AWS SECRET KEY HERE>",
+        "session_token": "<PLEASE ADD YOUR AWS SECURITY TOKEN HERE>"
+    },
+    "parameters": {
+        "region": "<PLEASE ADD YOUR AWS REGION HERE>",
+        "service_name": "bedrock",
+        "model": "amazon.nova-2-multimodal-embeddings-v1:0",
+        "input_docs_processed_step_size": 1,
+        "dimensions": 1024,
+        "normalize": true,
+        "embeddingTypes": [
+            "float"
+        ],
+        "audioFormat": "<mp3|wav|ogg>"
+    },
+    "actions": [
+        {
+            "action_type": "predict",
+            "method": "POST",
+            "headers": {
+                "content-type": "application/json",
+                "x-amz-content-sha256": "required"
+            },
+            "url": "https://bedrock-runtime.${parameters.region}.amazonaws.com/model/${parameters.model}/invoke",
+            "request_body": "{\n  \"taskType\": \"SINGLE_EMBEDDING\",\n  \"singleEmbeddingParams\": {\n  \"embeddingPurpose\": \"AUDIO_RETRIEVAL\",      \"embeddingDimension\": ${parameters.dimensions},\n        \"audio\": {\n            \"format\": \"${parameters.audioFormat}\",\n\"source\": {\n                \"bytes\": \"${parameters.inputAudio}\"\n            }\n        }\n    }\n}",
+            "pre_process_function": "connector.pre_process.bedrock.nova.audio_embedding",
+            "post_process_function": "connector.post_process.bedrock.nova.embedding"
+        }
+    ]
+}
+```
+
+If using the AWS Opensearch Service, you can provide an IAM role arn that allows access to the bedrock service.
+Refer to this [AWS doc](https://docs.aws.amazon.com/opensearch-service/latest/developerguide/ml-amazon-connector.html)
+
+#### For AOS 2.17, 2.19, and 3.1:
+
+```json
+POST /_plugins/_ml/connectors/_create
+{
+    "name": "Amazon Bedrock Nova multimodal model - audio embedding",
+    "description": "Test connector for Amazon Bedrock Nova multimodal model - audio embedding",
+    "version": 1,
+    "protocol": "aws_sigv4",
+    "credential": {
+        "roleArn": "<PLEASE ADD YOUR AWS ROLE ARN HERE>"
+    },
+    "parameters": {
+        "region": "<PLEASE ADD YOUR AWS REGION HERE>",
+        "service_name": "bedrock",
+        "model": "amazon.nova-2-multimodal-embeddings-v1:0",
+        "input_docs_processed_step_size": 1,
+        "dimensions": 1024,
+        "normalize": true,
+        "embeddingTypes": [
+            "float"
+        ],
+        "audioFormat": "<mp3|wav|ogg>"
+    },
+    "actions": [
+        {
+            "action_type": "predict",
+            "method": "POST",
+            "headers": {
+                "content-type": "application/json",
+                "x-amz-content-sha256": "required"
+            },
+            "url": "https://bedrock-runtime.${parameters.region}.amazonaws.com/model/${parameters.model}/invoke",
+            "request_body": "{\n  \"taskType\": \"SINGLE_EMBEDDING\",\n  \"singleEmbeddingParams\": {\n  \"embeddingPurpose\": \"AUDIO_RETRIEVAL\",      \"embeddingDimension\": ${parameters.dimensions},\n        \"audio\": {\n            \"format\": \"${parameters.audioFormat}\",\n\"source\": {\n                \"bytes\": \"${parameters.inputAudio}\"\n            }\n        }\n    }\n}",
+            "pre_process_function": "connector.pre_process.bedrock.nova.video_embedding",
+            "post_process_function": "connector.post_process.bedrock.nova.embedding"
+        }
+    ]
+}
+```
+
+#### For AOS 3.3+:
+
+```json
+POST /_plugins/_ml/connectors/_create
+{
+    "name": "Amazon Bedrock Nova multimodal model - audio embedding",
+    "description": "Test connector for Amazon Bedrock Nova multimodal model - audio embedding",
+    "version": 1,
+    "protocol": "aws_sigv4",
+    "credential": {
+        "roleArn": "<PLEASE ADD YOUR AWS ROLE ARN HERE>"
+    },
+    "parameters": {
+        "region": "<PLEASE ADD YOUR AWS REGION HERE>",
+        "service_name": "bedrock",
+        "model": "amazon.nova-2-multimodal-embeddings-v1:0",
+        "input_docs_processed_step_size": 1,
+        "dimensions": 1024,
+        "normalize": true,
+        "embeddingTypes": [
+            "float"
+        ],
+        "audioFormat": "<mp3|wav|ogg>"
+    },
+    "actions": [
+        {
+            "action_type": "predict",
+            "method": "POST",
+            "headers": {
+                "content-type": "application/json",
+                "x-amz-content-sha256": "required"
+            },
+            "url": "https://bedrock-runtime.${parameters.region}.amazonaws.com/model/${parameters.model}/invoke",
+            "request_body": "{\n  \"taskType\": \"SINGLE_EMBEDDING\",\n  \"singleEmbeddingParams\": {\n  \"embeddingPurpose\": \"AUDIO_RETRIEVAL\",      \"embeddingDimension\": ${parameters.dimensions},\n        \"audio\": {\n            \"format\": \"${parameters.audioFormat}\",\n\"source\": {\n                \"bytes\": \"${parameters.inputAudio}\"\n            }\n        }\n    }\n}",
+            "pre_process_function": "connector.pre_process.bedrock.nova.audio_embedding",
+            "post_process_function": "connector.post_process.bedrock.nova.embedding"
+        }
+    ]
+}
+```
+
+## 2. Register remote model:
+
+Register a separate model for each connector created in step 2. Use the corresponding connector_id for each modality:
+
+```json
+POST /_plugins/_ml/models/_register
+{
+  "name": "Amazon Bedrock Nova Multi-Modal Embedding model",
+  "function_name": "remote",
+  "description": "Test model for Amazon Bedrock Nova embedding model",
+  "connector_id": "<connector_id>"
+}
+```
+
+## 3. Test model inference:
+
+### Text Embedding
+
+```json
+POST /_plugins/_ml/models/<model_id>/_predict
+{
+  "parameters": {
+    "inputText": "hello world"
+  }
+}
+```
+
+Sample response:
+
+```json
+{
+  "inference_results": [
+    {
+      "output": [
+        {
+          "name": "sentence_embedding",
+          "data_type": "FLOAT32",
+          "shape": [
+            1024
+          ],
+          "data": [
+            -0.014445321,
+            0.029572023,
+            -0.024120959,
+            ...
+          ]
+        }
+      ]
+    }
+  ]
+}
+```
+
+### Image Embedding
+
+Replace `{{image_base64}}` with your base64-encoded image string:
+
+```json
+POST /_plugins/_ml/models/<model_id>/_predict
+{
+  "parameters": {
+    "inputImage": "{{image_base64}}"
+  }
+}
+```
+
+Sample response:
+
+```json
+{
+  "inference_results": [
+    {
+      "output": [
+        {
+          "name": "sentence_embedding",
+          "data_type": "FLOAT32",
+          "shape": [
+            1024
+          ],
+          "data": [
+            0.0012908162,
+            -2.3238199E-5,
+            -0.04998639,
+            ...
+          ]
+        }
+      ]
+    }
+  ]
+}
+```
+
+### Video Embedding
+
+Replace `{{video_base64}}` with your base64-encoded video string:
+
+
+```json
+POST /_plugins/_ml/models/<model_id>/_predict
+{
+  "parameters": {
+    "inputVideo": "{{video_base64}}"
+  }
+}
+```
+
+Sample response:
+
+```json
+{
+  "inference_results": [
+    {
+      "output": [
+        {
+          "name": "sentence_embedding",
+          "data_type": "FLOAT32",
+          "shape": [
+            1024
+          ],
+          "data": [
+            0.014660299,
+            -0.023394907,
+            0.022433588,
+            ...
+          ]
+        }
+      ]
+    }
+  ]
+}
+```
+
+### Audio Embedding
+
+Replace `{{audio_base64}}` with your base64-encoded audio string:
+
+
+```json
+POST /_plugins/_ml/models/<model_id>/_predict
+{
+  "parameters": {
+    "inputAudio": "{{audio_base64}}"
+  }
+}
+```
+
+Sample response:
+
+```json
+{
+  "inference_results": [
+    {
+      "output": [
+        {
+          "name": "sentence_embedding",
+          "data_type": "FLOAT32",
+          "shape": [
+            1024
+          ],
+          "data": [
+            -0.019146109,
+            -0.02901372,
+            -0.041826885,
+            ...
+          ]
+        }
+      ]
+    }
+  ]
+}
+```
\ No newline at end of file
diff --git a/docs/remote_inference_blueprints/standard_blueprints/README.md b/docs/remote_inference_blueprints/standard_blueprints/README.md
index d8a91af00a..de255061eb 100644
--- a/docs/remote_inference_blueprints/standard_blueprints/README.md
+++ b/docs/remote_inference_blueprints/standard_blueprints/README.md
@@ -37,6 +37,7 @@ These blueprints include pre- and post-processing functions, suitable when you n
 - Bedrock:
   - [amazon.titan-embed-text-v1](https://github.com/opensearch-project/ml-commons/blob/main/docs/remote_inference_blueprints/bedrock_connector_titan_embedding_blueprint.md)
   - [amazon.titan-embed-image-v1](https://github.com/opensearch-project/ml-commons/blob/main/docs/remote_inference_blueprints/bedrock_connector_titan_multimodal_embedding_blueprint.md)
+  - [amazon.nova-2-multimodal-embeddings-v1:0](https://github.com/opensearch-project/ml-commons/blob/main/docs/remote_inference_blueprints/bedrock_connector_nova_multimodal_model_blueprint.md)
   - [cohere.embed-english-v3](https://github.com/opensearch-project/ml-commons/blob/main/docs/remote_inference_blueprints/bedrock_connector_cohere_cohere.embed-english-v3_blueprint.md)
   - [cohere.embed-multilingual-v3](https://github.com/opensearch-project/ml-commons/blob/main/docs/remote_inference_blueprints/bedrock_connector_cohere_cohere.embed-multilingual-v3_blueprint.md)
 - Cohere