---
title: "OpenRouter"
description: "<a target=\"_blank\" href=\"https://colab.research.google.com/github/BerriAI/litellm/blob/main/cookbook/LiteLLM_OpenRouter.ipynb\"> <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/> </a>"
type: skill
canonical_url: https://claudary.paisolsolutions.com/skills/openrouter-1
source: "Claudary"
difficulty: intermediate
author: "Claude Code Knowledge Pack"
date: 2026-07-10T11:31:31.999Z
license: CC-BY-4.0
attribution: "OpenRouter — Claudary (https://claudary.paisolsolutions.com/skills/openrouter-1)"
---

# OpenRouter
<a target="_blank" href="https://colab.research.google.com/github/BerriAI/litellm/blob/main/cookbook/LiteLLM_OpenRouter.ipynb"> <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/> </a>

## Overview

# OpenRouter
LiteLLM supports all the text / chat / vision / embedding models from [OpenRouter](https://openrouter.ai/docs)

<a target="_blank" href="https://colab.research.google.com/github/BerriAI/litellm/blob/main/cookbook/LiteLLM_OpenRouter.ipynb">
  <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>

## Usage
```python
import os
from litellm import completion

os.environ["OPENROUTER_API_KEY"] = ""
os.environ["OPENROUTER_API_BASE"] = "" # [OPTIONAL] defaults to https://openrouter.ai/api/v1
os.environ["OR_SITE_URL"] = "" # [OPTIONAL]
os.environ["OR_APP_NAME"] = "" # [OPTIONAL]

response = completion(
            model="openrouter/google/palm-2-chat-bison",
            messages=messages,
        )
```

## Configuration with Environment Variables

For production environments, you can dynamically configure the base_url using environment variables:

```python
import os
from litellm import completion

# Configure with environment variables
OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY")
OPENROUTER_BASE_URL = os.getenv("OPENROUTER_API_BASE", "https://openrouter.ai/api/v1")

# Set environment for LiteLLM
os.environ["OPENROUTER_API_KEY"] = OPENROUTER_API_KEY
os.environ["OPENROUTER_API_BASE"] = OPENROUTER_BASE_URL

response = completion(
    model="openrouter/google/palm-2-chat-bison",
    messages=messages,
    base_url=OPENROUTER_BASE_URL  # Explicitly pass base_url for clarity
)
```

This approach provides better flexibility for managing configurations across different environments (dev, staging, production) and makes it easier to switch between self-hosted and cloud endpoints.

## OpenRouter Completion Models
🚨 LiteLLM supports ALL OpenRouter models, send `model=openrouter/<your-openrouter-model>` to send it to open router. See all openrouter models [here](https://openrouter.ai/models)

| Model Name                | Function Call                                       |
|---------------------------|-----------------------------------------------------|
| openrouter/openai/gpt-3.5-turbo | `completion('openrouter/openai/gpt-3.5-turbo', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OPENROUTER_API_KEY']` |
| openrouter/openai/gpt-3.5-turbo-16k | `completion('openrouter/openai/gpt-3.5-turbo-16k', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OPENROUTER_API_KEY']` |
| openrouter/openai/gpt-4    | `completion('openrouter/openai/gpt-4', messages)`       | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OPENROUTER_API_KEY']` |
| openrouter/openai/gpt-4-32k | `completion('openrouter/openai/gpt-4-32k', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OPENROUTER_API_KEY']` |
| openrouter/anthropic/claude-2 | `completion('openrouter/anthropic/claude-2', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OPENROUTER_API_KEY']` |
| openrouter/anthropic/claude-instant-v1 | `completion('openrouter/anthropic/claude-instant-v1', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OPENROUTER_API_KEY']` |
| openrouter/google/palm-2-chat-bison | `completion('openrouter/google/palm-2-chat-bison', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OPENROUTER_API_KEY']` |
| openrouter/google/palm-2-codechat-bison | `completion('openrouter/google/palm-2-codechat-bison', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OPENROUTER_API_KEY']` |
| openrouter/meta-llama/llama-2-13b-chat | `completion('openrouter/meta-llama/llama-2-13b-chat', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OPENROUTER_API_KEY']` |
| openrouter/meta-llama/llama-2-70b-chat | `completion('openrouter/meta-llama/llama-2-70b-chat', messages)` | `os.environ['OR_SITE_URL']`,`os.environ['OR_APP_NAME']`,`os.environ['OPENROUTER_API_KEY']` |

## Passing OpenRouter Params - transforms, models, route
Pass `transforms`, `models`, `route`as arguments to `litellm.completion()`

```python
import os
from litellm import completion

os.environ["OPENROUTER_API_KEY"] = ""

response = completion(
            model="openrouter/google/palm-2-chat-bison",
            messages=messages,
            transforms = [""],
            route= ""
        )
```

## Embedding

```python
from litellm import embedding
import os

os.environ["OPENROUTER_API_KEY"] = "your-api-key"

response = embedding(
    model="openrouter/openai/text-embedding-3-small",
    input=["good morning from litellm", "this is another item"],
)
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']}")
```

## Image Edit

OpenRouter supports image editing through select models like Google Gemini image models. LiteLLM routes image edit requests to OpenRouter's chat completions endpoint with the source image sent as a base64 data URL and `modalities: ["image", "text"]`.

### Supported Models

| Model | Description |
|-------|-------------|
| `openrouter/google/gemini-2.5-flash-image` | Gemini 2.5 Flash with image editing |

See all available image models on [OpenRouter's model list](https://openrouter.ai/models?modality=image).

### Supported Parameters

| Parameter | OpenRouter Mapping | Notes |
|-----------|--------------------|-------|
| `size` | `image_config.aspect_ratio` | `1024x1024` → `1:1`, `1536x1024` → `3:2`, `1024x1536` → `2:3`, `1792x1024` → `16:9`, `1024x1792` → `9:16` |
| `quality` | `image_config.image_size` | `low`/`standard` → `1K`, `medium` → `2K`, `high`/`hd` → `4K` |
| `n` | `n` | Number of images |

:::note
`quality=high` (4K) is only supported by `google/gemini-3-pro-image-preview` and `google/gemini-3.1-flash-image-preview`. The `google/gemini-2.5-flash-image` model supports up to `medium` (2K).
:::

### Usage

```python
from litellm import image_edit
import os

os.environ["OPENROUTER_API_KEY"] = "your-api-key"

# Basic image edit
response = image_edit(
    model="openrouter/google/gemini-2.5-flash-image",
    image=open("original_image.png", "rb"),
    prompt="Make the sky a vibrant purple sunset",
)

print(response)
```

### Advanced Usage with Parameters

```python
from litellm import image_edit
import os

os.environ["OPENROUTER_API_KEY"] = "your-api-key"

# Edit with size and quality parameters
response = image_edit(
    model="openrouter/google/gemini-2.5-flash-image",
    image=open("photo.png", "rb"),
    prompt="Add northern lights to the sky",
    size="1536x1024",   # Maps to aspect_ratio 3:2
    quality="high",      # Maps to image_size 4K
)

# Access the edited image
image_data = response.data[0]
if image_data.b64_json:
    import base64
    with open("edited.png", "wb") as f:
        f.write(base64.b64decode(image_data.b64_json))
```

### Multiple Images Edit

```python
from litellm import image_edit
import os

os.environ["OPENROUTER_API_KEY"] = "your-api-key"

response = image_edit(
    model="openrouter/google/gemini-2.5-flash-image",
    image=[
        open("scene.png", "rb"),
        open("style_reference.png", "rb"),
    ],
    prompt="Blend the reference style into the scene",
)

print(response)
```

---

Source: [Claudary](https://claudary.paisolsolutions.com/skills/openrouter-1) · https://claudary.paisolsolutions.com