diff --git a/autogpt_platform/backend/.env.example b/autogpt_platform/backend/.env.example
index 0ec84ca83e66..298178733453 100644
--- a/autogpt_platform/backend/.env.example
+++ b/autogpt_platform/backend/.env.example
@@ -95,6 +95,9 @@ REPLICATE_API_KEY=
 # Ideogram
 IDEOGRAM_API_KEY=
 
+# Openrouter
+OPENROUTER_API_KEY=
+
 # Logging Configuration
 LOG_LEVEL=INFO
 ENABLE_CLOUD_LOGGING=false
diff --git a/autogpt_platform/backend/backend/blocks/multimodal_ai_block.py b/autogpt_platform/backend/backend/blocks/multimodal_ai_block.py
new file mode 100644
index 000000000000..04a484c7ed39
--- /dev/null
+++ b/autogpt_platform/backend/backend/blocks/multimodal_ai_block.py
@@ -0,0 +1,104 @@
+from enum import Enum
+
+from openai import OpenAI
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import BlockSecret, SchemaField, SecretField
+
+
+# Model name enum
+class MultimodalAIModelName(str, Enum):
+    LLAMA_VISION_11B = "meta-llama/llama-3.2-11b-vision-instruct:free"
+    LLAMA_VISION_90B = "meta-llama/llama-3.2-90b-vision-instruct"
+    PIXTRAL_12B = "mistralai/pixtral-12b"
+    CHATGPT_4O_LATEST = "openai/chatgpt-4o-latest"
+
+
+class MultimodalAIBlock(Block):
+    class Input(BlockSchema):
+        api_key: BlockSecret = SecretField(
+            key="openrouter_api_key",
+            description="OpenRouter API Key",
+            advanced=False,
+        )
+        prompt: str = SchemaField(
+            description="Text prompt for multimodal AI response",
+            placeholder="e.g., 'Describe the contents of the image'",
+            title="Prompt",
+        )
+        image_url: str = SchemaField(
+            description="URL of the image to analyze",
+            placeholder="e.g., 'https://example.com/image.jpg'",
+            title="Image URL",
+        )
+        model_name: MultimodalAIModelName = SchemaField(
+            description="The name of the multimodal AI model",
+            default=MultimodalAIModelName.LLAMA_VISION_11B,
+            title="Multimodal AI Model",
+            advanced=False,
+        )
+
+    class Output(BlockSchema):
+        result: str = SchemaField(description="Generated output")
+        error: str = SchemaField(description="Error message if the model run failed")
+
+    def __init__(self):
+        super().__init__(
+            id="62f5be31-9896-40ed-bd71-2dda74459e20",
+            description="This block runs multimodal AI models on OpenRouter with advanced settings.",
+            categories={BlockCategory.AI},
+            input_schema=MultimodalAIBlock.Input,
+            output_schema=MultimodalAIBlock.Output,
+            test_input={
+                "api_key": "test_api_key",
+                "model_name": MultimodalAIModelName.LLAMA_VISION_11B,
+                "prompt": "Describe the contents of the image",
+                "image_url": "https://example.com/image.jpg",
+            },
+            test_output=[
+                (
+                    "result",
+                    "The image depicts a serene boardwalk surrounded by lush greenery.",
+                ),
+            ],
+            test_mock={
+                "run_model": lambda api_key, model_name, prompt, image_url: "The image depicts a serene boardwalk surrounded by lush greenery.",
+            },
+        )
+
+    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        try:
+            # Call the separated model execution logic
+            result = self.run_model(
+                api_key=input_data.api_key.get_secret_value(),
+                model_name=input_data.model_name,
+                prompt=input_data.prompt,
+                image_url=input_data.image_url,
+            )
+            yield "result", result
+        except Exception as e:
+            yield "error", str(e)
+
+    def run_model(self, api_key, model_name, prompt, image_url):
+        # Initialize OpenAI client with the API key
+        client = OpenAI(
+            base_url="https://openrouter.ai/api/v1",
+            api_key=api_key,
+        )
+
+        # Call the API to create a completion based on the input data
+        completion = client.chat.completions.create(
+            model=model_name,
+            messages=[
+                {
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": prompt},
+                        {"type": "image_url", "image_url": {"url": image_url}},
+                    ],
+                }
+            ],
+        )
+
+        # Extract and return the content from the API response
+        return completion.choices[0].message.content
diff --git a/autogpt_platform/backend/backend/util/settings.py b/autogpt_platform/backend/backend/util/settings.py
index f521bf104f7d..fde2e83465a3 100644
--- a/autogpt_platform/backend/backend/util/settings.py
+++ b/autogpt_platform/backend/backend/util/settings.py
@@ -250,7 +250,7 @@ class Secrets(UpdateTrackingModel["Secrets"], BaseSettings):
     replicate_api_key: str = Field(default="", description="Replicate API Key")
     unreal_speech_api_key: str = Field(default="", description="Unreal Speech API Key")
     ideogram_api_key: str = Field(default="", description="Ideogram API Key")
-
+    openrouter_api_key: str = Field(default="", description="OpenRouter API Key")
     # Add more secret fields as needed
 
     model_config = SettingsConfigDict(