Analyze images and answer visual questions with OpenRouter Vision — a multimodal LLM endpoint that processes both text and image inputs. Ideal for image understanding, OCR, and visual reasoning tasks. Try free — pay per generation, no subscription.
About this model
Introducing openrouter-vision, a versatile large language model engineered to excel in a broad spectrum of natural language processing tasks. Designed for seamless text generation, chat, summarization, and comprehensive text-to-text transformation, openrouter-vision leverages best-in-class REST inference APIs to deliver exceptional performance without coldstarts. This model is built with user-centric efficiency in mind, enabling developers and enterprises to deploy robust NLP capabilities swiftly and cost-effectively.
Powered by cutting-edge technology and optimized for ultra-low latency, openrouter-vision stands out for its balance of speed, accuracy, and affordability. Its flexible API structure simplifies integration, while its competitive pricing of $0.025 per generation ensures that businesses can scale their operations without compromising on performance. Whether you need dynamic content creation, detailed summarizations, or interactive chat functionalities, openrouter-vision provides a reliable and scalable solution that meets modern digital demands.
Cost analysis
| Provider | Cost | Notes |
|---|---|---|
| muapiapp | $0.025 | muapiapp is 20-50% more affordable than its competitors while delivering comparable or superior quality. |
| Fal.ai | $0.04 | Pricing is nearly identical to Replicate, but muapiapp offers a 20-50% lower cost, making it a more cost-effective choice. |
| Replicate | $0.04 | With pricing similar to Fal.ai, muapiapp stands out by providing significant cost savings while maintaining high performance. |
muapiapp is 20-50% more affordable than its competitors while delivering comparable or superior quality.
Pricing is nearly identical to Replicate, but muapiapp offers a 20-50% lower cost, making it a more cost-effective choice.
With pricing similar to Fal.ai, muapiapp stands out by providing significant cost savings while maintaining high performance.
* Competitor pricing is estimated based on similar model architectures and usage tiers.
Configuration schema
| Parameter | Type | Description | Default |
|---|---|---|---|
| Prompt | string | The prompt to generate the response | Caption this image for a text-to-image model with as much detail as possible. |
| Image URLs | array | Upload or provide image urls. Used for image-to-video generation. | https://d3adwkbyhxyrtq.cloudfront.net/webassets/videomodels/openrouter-vision.jpg |
| System Prompt | string | System prompt to provide context or instructions to the model. | 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. |
| Model | Enum (5 options) | Name of the model to use. Premium models are charged at 10x the rate of standard models, they include: deepseek/deepseek-r1, google/gemini-pro-1.5, openai/gpt-4.1, anthropic/claude-3-5-haiku, openai/gpt-4o, anthropic/claude-3.5-sonnet, openai/o3, meta-llama/llama-3.2-90b-vision-instruct, anthropic/claude-3.7-sonnet, openai/gpt-5-chat. | google/gemini-2.5-flash |
| Reasoning | boolean | Should reasoning be the part of the final answer. | false |
| Temperature | int | This setting influences the variety in the model's responses. Lower values lead to more predictable and typical responses, while higher values encourage more diverse and less common responses. At 0, the model always gives the same response for a given input. | 1 |
| Max Tokens | int | This sets the upper limit for the number of tokens the model can generate in response. It won’t produce more than this limit. The maximum value is the context length minus the prompt length. | null |
The prompt to generate the response
Caption this image for a text-to-image model with as much detail as possible.Upload or provide image urls. Used for image-to-video generation.
https://d3adwkbyhxyrtq.cloudfront.net/webassets/videomodels/openrouter-vision.jpgSystem prompt to provide context or instructions to the model.
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.Name of the model to use. Premium models are charged at 10x the rate of standard models, they include: deepseek/deepseek-r1, google/gemini-pro-1.5, openai/gpt-4.1, anthropic/claude-3-5-haiku, openai/gpt-4o, anthropic/claude-3.5-sonnet, openai/o3, meta-llama/llama-3.2-90b-vision-instruct, anthropic/claude-3.7-sonnet, openai/gpt-5-chat.
google/gemini-2.5-flashShould reasoning be the part of the final answer.
falseThis setting influences the variety in the model's responses. Lower values lead to more predictable and typical responses, while higher values encourage more diverse and less common responses. At 0, the model always gives the same response for a given input.
1This sets the upper limit for the number of tokens the model can generate in response. It won’t produce more than this limit. The maximum value is the context length minus the prompt length.
nullDeveloper documentation
Step 1: Prepare Your Input
prompt and images_list.system_prompt, model, reasoning, temperature, and max_tokens to fine-tune the response.Step 2: Send the Request
Step 3: Interpret the Results
Step 4: Iterate and Optimize
Frequently asked
openrouter-vision is optimized for a variety of NLP tasks with a focus on speed and cost-efficiency. Its ready-to-use REST inference API and no coldstart performance make it an attractive option for developers needing reliable and scalable solutions.
Inputs should be structured in a JSON format as specified by the technical input schema. Key fields include 'prompt' and 'images_list', while you can also provide optional parameters like 'system_prompt', 'model', 'reasoning', 'temperature', and 'max_tokens' to tailor the response.
The model is competitively priced at $0.025 per generation, making it a cost-effective solution compared to similar offerings in the market.
Absolutely. Its architecture is designed to provide swift responses with minimal latency, making it suitable for real-time applications such as chatbots and interactive assistants.