How to Compare Multimodal AI Models Side-by-Side

The abundance of multimodal AI models available today can make finding the right one for a specific task overwhelming and time-consuming, often involving trial and error. To simplify this process, we have introduced a new side-by-side comparison feature that allows for a clear and direct comparison of different models, streamlining the decision-making process. In this blog, we will guide you through how you can take advantage of this functionality.

Why You Need to Compare Multimodal AI Models

Different models excel at different tasks and have varying strengths and weaknesses. By comparing outputs side-by-side, you can:

• Identify the best model for your use case: Not all models are created equal. Some may be better suited for certain tasks or data types than others. By comparing outputs, you can identify the model that produces the most accurate, relevant, or visually appealing results for your specific needs.
• Evaluate model performance: Comparing outputs can help you assess the performance of different models and identify any potential issues or limitations. This information can be valuable for debugging, fine-tuning, or selecting the most appropriate model for your project.
• Benchmark against state-of-the-art models: Comparing outputs can also help you benchmark your own models against state-of-the-art models. This can provide valuable feedback on the performance of your models and help you identify areas for improvement.
• Gain insights into model behavior: By observing how different models respond to the same input, you can gain insights into their underlying behavior and decision-making processes. This knowledge can help you better understand how to use and interpret the outputs of AI models.

That being said, comparing multimodal AI models that process various data types can be a cumbersome and time-consuming task, often requiring both visual and auditory inspection. To address this challenge, we've developed a real-time side-by-side comparison feature. On Playground, you can evaluate a broad range of multimodal capabilities, including image, video, and audio understanding, as well as image generation, speech recognition, and transcription. We are continually expanding our support to encompass even more multimodal capabilities. For a comprehensive list of supported models, please visit our models page. If you don't see the model you're interested in, simply submit a request here.

Real-time Side-by-Side Multimodal Output Comparison

The live comparison feature allows you to view and compare the outputs from various multimodal models simultaneously in a single, unified view, streamlining your decision-making process. This side-by-side comparison allows for a quick and efficient assessment of the strengths and weaknesses of each model, making it easier to identify the best model for your specific use case. By presenting the results in a clear and concise manner, this feature saves you valuable time and effort, allowing you to focus on making informed decisions and achieving optimal outcomes.

How to Compare Models

1. Visit Playground.
2. Select Your Models: Choose which multimodal models you’d like to compare from a variety of top-tier models available in our platform, each suited for different tasks like image generation, text analysis, and more.
3. Enter Your Prompt: Input a single prompt or task that you want to test across multiple models. For example, you might ask the models to generate an image based on the same text prompt or analyze an audio clip.
4. View the Results Side-by-Side: The outputs from each model will be displayed in a split-screen format, allowing you to easily compare them. This can include images, text, or other outputs depending on the models selected.
5. Evaluate and Choose: Once you have all the outputs in front of you, you can make a more informed decision about which model works best for your specific needs. You can even fine-tune your prompt or explore additional models to refine your results.

Key Benefits

Traditionally, comparing outputs from different models involves manually switching between tools, looking for subtle differences, and sometimes even exporting files for deeper analysis. Our new feature eliminates these hurdles by providing an intuitive side-by-side view of results, simplifying your decision-making process.

• Superior Time Efficiency & Performance: You no longer need to wait for long processing times across multiple models. With FriendliAI's live comparison feature, you can view faster results by processing models in parallel, helping you prioritize the most efficient options for your workflow. FriendliAI offers fastest-in-class Time to First Token (TTFT), as verified by third-party benchmark Artificial Analysis, and remarkable Time Per Output Token (TPOT), delivering rapid, uninterrupted responses. This means fewer iterations, less experimentation, and more time for the creative aspects of your project.
• Informed, Tailored Decision-Making: With concurrent, side-by-side comparisons, you can evaluate model outputs to understand the strengths and weaknesses of each. Whether it's detail, creativity, or accuracy, this feature helps you make more informed decisions about which model best suits your needs. You can also easily balance the trade-off between high-quality outputs and fast results, should you want to prioritize a model that produces great results or delivers quickly in time-sensitive tasks.
• Deployment from Hugging Face: As an official deployment option on Hugging Face, FriendliAI supports a wide range of models, including those you've fine-tuned. Our seamless integration allows you to quickly evaluate outputs from various models, giving you access to the full power of cutting-edge AI technologies and ensuring you can find the best fit for your unique needs.
• Cost-Efficiency: Friendli Inference, our state-of-the-art generative AI inference engine, reduces the GPU costs by over 50%, maximizing ROI all while delivering exceptional performance.

Use Cases

Now that you understand the key benefits, let’s explore how these multimodal capabilities translate into real-world applications:

• Text-to-Image Generation: Imagine you're designing visuals for an upcoming campaign and need high-quality images quickly. For example, if you're deciding between black-forest-labs/FLUX.1-dev and black-forest-labs/FLUX.1-schnell, you can easily compare which model produces the most visually appealing result.

• Image Understanding: When analyzing a large set of images, FriendliAI helps you compare different models to determine which one best meets your needs. For instance, you can compare Qwen/Qwen2.5-VL-72B-Instruct and FriendliAI/olmOCR-7B-0225-preview to identify which model offers more accurate understanding.

• Audio Understanding: For professionals looking to automate notetaking during meetings, interviews, or monologues, our playground simplifies the process of finding the best model for each scenario. For example, you can compare Qwen/Qwen2-Audio-7B-Instruct and openbmb/MiniCPM-o-2_6 to select the most effective solution.

With the ability to compare outputs from multiple multimodal models side-by-side, you can now navigate the world of AI with more confidence and precision. No longer will you have to rely on guesswork or self-proclaimed benchmark score to determine which model works best for your needs. Whether you’re in creative industries, research, or just exploring the capabilities of AI, this new feature will help you make smarter, faster, and more effective decisions in an objective way.

Getting Started

Simply pick your models, enter a prompt, and start comparing! The intuitive interface lets you test and explore with ease—whether you're new to AI or an expert. Click here to start today and find the perfect AI model for your next project!