Add openrouter support for image/generation endpoints

docs/my-website/docs/image_generation.md

@@ -15,7 +15,7 @@ import TabItem from '@theme/TabItem';
 | Fallbacks | ✅ | Works between supported models |
 | Loadbalancing | ✅ | Works between supported models |
 | Guardrails | ✅ | Applies to input prompts (non-streaming only) |
-| Supported Providers | OpenAI, Azure, Google AI Studio, Vertex AI, AWS Bedrock, Recraft, Xinference, Nscale | |
+| Supported Providers | OpenAI, Azure, Google AI Studio, Vertex AI, AWS Bedrock, Recraft, OpenRouter, Xinference, Nscale | |
 
 ## Quick Start
 
@@ -238,6 +238,27 @@ print(response)
 
 See Recraft usage with LiteLLM [here](./providers/recraft.md#image-generation)
 
+## OpenRouter Image Generation Models
+
+Use this for image generation models available through OpenRouter (e.g., Google Gemini image generation models)
+
+#### Usage
+
+```python showLineNumbers
+from litellm import image_generation
+import os
+
+os.environ['OPENROUTER_API_KEY'] = "your-api-key"
+
+response = image_generation(
+    model="openrouter/google/gemini-2.5-flash-image",
+    prompt="A beautiful sunset over a calm ocean",
+    size="1024x1024",
+    quality="high",
+)
+print(response)
+```
+
 ## OpenAI Compatible Image Generation Models
 Use this for calling `/image_generation` endpoints on OpenAI Compatible Servers, example https://github.com/xorbitsai/inference
 
@@ -301,5 +322,6 @@ print(f"response: {response}")
 | Vertex AI | [Vertex AI Image Generation →](./providers/vertex_image) |
 | AWS Bedrock | [Bedrock Image Generation →](./providers/bedrock) |
 | Recraft | [Recraft Image Generation →](./providers/recraft#image-generation) |
+| OpenRouter | [OpenRouter Image Generation →](./providers/openrouter#image-generation) |
 | Xinference | [Xinference Image Generation →](./providers/xinference#image-generation) |
 | Nscale | [Nscale Image Generation →](./providers/nscale#image-generation) | 

docs/my-website/docs/providers/openrouter.md

@@ -93,3 +93,120 @@ response = embedding(
 )
 print(response)
 ```
+
+## Image Generation
+
+OpenRouter supports image generation through select models like Google Gemini image generation models. LiteLLM transforms standard image generation requests to OpenRouter's chat completion format.
+
+### Supported Parameters
+
+- `size`: Maps to OpenRouter's `aspect_ratio` format
+  - `1024x1024` → `1:1` (square)
+  - `1536x1024` → `3:2` (landscape)
+  - `1024x1536` → `2:3` (portrait)
+  - `1792x1024` → `16:9` (wide landscape)
+  - `1024x1792` → `9:16` (tall portrait)
+
+- `quality`: Maps to OpenRouter's `image_size` format (Gemini models)
+  - `low` or `standard` → `1K`
+  - `medium` → `2K`
+  - `high` or `hd` → `4K`
+
+- `n`: Number of images to generate
+
+### Usage
+
+```python
+from litellm import image_generation
+import os
+
+os.environ["OPENROUTER_API_KEY"] = "your-api-key"
+
+# Basic image generation
+response = image_generation(
+    model="openrouter/google/gemini-2.5-flash-image",
+    prompt="A beautiful sunset over a calm ocean",
+)
+print(response)
+```
+
+### Advanced Usage with Parameters
+
+```python
+from litellm import image_generation
+import os
+
+os.environ["OPENROUTER_API_KEY"] = "your-api-key"
+
+# Generate high-quality landscape image
+response = image_generation(
+    model="openrouter/google/gemini-2.5-flash-image",
+    prompt="A serene mountain landscape with a lake",
+    size="1536x1024",  # Landscape format
+    quality="high",     # High quality (4K)
+)
+
+# Access the generated image
+image_data = response.data[0]
+if image_data.b64_json:
+    # Base64 encoded image
+    print(f"Generated base64 image: {image_data.b64_json[:50]}...")
+elif image_data.url:
+    # Image URL
+    print(f"Generated image URL: {image_data.url}")
+```
+
+### Using OpenRouter-Specific Parameters
+
+You can also pass OpenRouter-specific parameters directly using `image_config`:
+
+```python
+from litellm import image_generation
+import os
+
+os.environ["OPENROUTER_API_KEY"] = "your-api-key"
+
+response = image_generation(
+    model="openrouter/google/gemini-2.5-flash-image",
+    prompt="A futuristic cityscape at night",
+    image_config={
+        "aspect_ratio": "16:9",  # OpenRouter native format
+        "image_size": "4K"       # OpenRouter native format
+    }
+)
+print(response)
+```
+
+### Response Format
+
+The response follows the standard LiteLLM ImageResponse format:
+
+```python
+{
+    "created": 1703658209,
+    "data": [{
+        "b64_json": "iVBORw0KGgoAAAANSUhEUgAA...",  # Base64 encoded image
+        "url": None,
+        "revised_prompt": None
+    }],
+    "usage": {
+        "input_tokens": 10,
+        "output_tokens": 1290,
+        "total_tokens": 1300
+    }
+}
+```
+
+### Cost Tracking
+
+OpenRouter provides cost information in the response, which LiteLLM automatically tracks:
+
+```python
+response = image_generation(
+    model="openrouter/google/gemini-2.5-flash-image",
+    prompt="A cute baby sea otter",
+)
+
+# Cost is available in the response metadata
+print(f"Request cost: ${response._hidden_params['additional_headers']['llm_provider-x-litellm-response-cost']}")
+```

litellm/images/main.py

@@ -404,6 +404,7 @@ def image_generation(  # noqa: PLR0915
             litellm.LlmProviders.STABILITY,
             litellm.LlmProviders.RUNWAYML,
             litellm.LlmProviders.VERTEX_AI,
+            litellm.LlmProviders.OPENROUTER
         ):
             if image_generation_config is None:
                 raise ValueError(

litellm/llms/openrouter/image_generation/__init__.py

@@ -0,0 +1,13 @@
+from litellm.llms.base_llm.image_generation.transformation import (
+    BaseImageGenerationConfig,
+)
+
+from .transformation import OpenRouterImageGenerationConfig
+
+__all__ = [
+    "OpenRouterImageGenerationConfig",
+]
+
+
+def get_openrouter_image_generation_config(model: str) -> BaseImageGenerationConfig:
+    return OpenRouterImageGenerationConfig()