openrouter/router/vision

Run any Vision Language Model with fal. Analyze and understand images using Claude (Anthropic), GPT-5 / GPT-4o (OpenAI), Gemini (Google), Grok (xAI), Llama (Meta), Qwen, Pixtral (Mistral), and more. Send one or multiple images for captioning, analysis, OCR, or visual Q&A. Powered by OpenRouter.

Inference

Commercial use

Streaming

Partner

Schema

LLMs

Playground API Examples

Input

Image Urls*

Hint: Drag and drop files from your computer, images from web pages, paste from clipboard (Ctrl/Cmd+V), or provide a URL.

1 image added

Prompt*

Type # to reference inputs.

System Prompt

Model*

Reasoning

Additional Settings

Customize your input with more control.

Streaming

Result

Idle

Close-up, detailed shot of an Inuit man, 30s-40s, with warm brown eyes, a trimmed black beard and mustache, frosted with snow and ice, looking thoughtfully upwards, against a blurred background of a snowstorm and cold, pale blue sky, wearing a thick, faux fur-lined parka with light brown and white fur, covered in snow, with flakes of snow falling on his hair, beard, and parka, his skin has slight blemishes and small scars.

What would you like to do next?

{
  "output": "Close-up, detailed shot of an Inuit man, 30s-40s, with warm brown eyes, a trimmed black beard and mustache, frosted with snow and ice, looking thoughtfully upwards, against a blurred background of a snowstorm and cold, pale blue sky, wearing a thick, faux fur-lined parka with light brown and white fur, covered in snow, with flakes of snow falling on his hair, beard, and parka, his skin has slight blemishes and small scars.",
  "usage": {
    "prompt_tokens": 1856,
    "completion_tokens": 100,
    "total_tokens": 1956,
    "cost": 0.0008068,
    "prompt_tokens_details": {
      "cached_tokens": 0,
      "cache_write_tokens": 0
    }
  }
}

You will be charged based on the number of input and output tokens.

Logs

🚀 Usage with OpenAI Client

python
from openai import OpenAI
import os

client = OpenAI(
    base_url="https://fal.run/openrouter/router/openai/v1",
    api_key="not-needed",
    default_headers={
        "Authorization": f"Key {os.environ['FAL_KEY']}",
    },
)

response = client.chat.completions.create(
    model="google/gemini-2.5-flash",
    messages=[
        {
            "role": "system",
            "content": "Only answer the question, do not provide any additional information or add any prefix/suffix other than the answer of the original question. Don't use markdown.",
        },
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "Caption this image for a text-to-image model with as much detail as possible."},
                {
                    "type": "image_url",
                    "image_url": "https://fal.media/files/tiger/4Ew1xYW6oZCs6STQVC7V8_86440216d0fe42e4b826d03a2121468e.jpg",
                },
            ],
        },
    ],
    temperature=1,
)

print(response.choices[0].message.content)

🚿 Streaming Example

python
from openai import OpenAI
import os

client = OpenAI(
    base_url="https://fal.run/openrouter/router/openai/v1",
    api_key="not-needed",
    default_headers={
        "Authorization": f"Key {os.environ['FAL_KEY']}",
    },
)

stream = client.chat.completions.create(
    model="google/gemini-2.5-flash",
    messages=[
        {
            "role": "system",
            "content": "Only answer the question, do not provide any additional information or add any prefix/suffix other than the answer of the original question. Don't use markdown.",
        },
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "Caption this image for a text-to-image model with as much detail as possible."},
                {
                    "type": "image_url",
                    "image_url": "https://fal.media/files/tiger/4Ew1xYW6oZCs6STQVC7V8_86440216d0fe42e4b826d03a2121468e.jpg",
                },
            ],
        },
    ],
    temperature=1,
    stream=True,
)

for chunk in stream:
    if chunk.choices and chunk.choices[0].delta:
        print(chunk.choices[0].delta.content, end="", flush=True)

📚 Documentation

For more details, visit the official docs:

🔗 OpenRouter API Docs
⚡ fal.ai API Docs