Overview
ChatGPT-4o, Claude 3 Opus and Gemini 1.5 Pro are three of the best generative AI large language models (LLMs) with multimodal capabilities that tech world has to offer. With multimodality capabilities these models are not just about understanding text; they can process images, video, and even code, opening up a world of possibilities for annotating data, creative expression, and real-world understanding.
With a new AI model being launched every now and then these three are still the top-ranked LLMs available in the market. In this blog we will do a comparative review of ChatGPT-4o, Claude 3 Opus and Gemini 1.5 Pro on the basis of each LLMs pros and cons.
What is Multimodal AI?
Unlike traditional models that concentrate on a single type of data, like text or images, multimodal AI systems have the capability to handle and combine information from various sources, such as:
- Text: Written language, including documents and social media posts.
- Images: Photographs, illustrations, medical scans, and more.
- Audio: Speech, music, and sound effects.
- Video: A mix of visual and auditory data.
For example, a multimodal AI model could analyze a video, understanding the visual content, spoken words, and background sounds to generate a comprehensive summary or answer questions about the video.
ChatGPT-4o: Open AI’s Multimodal AI
ChatGPT-4o is the multimodal AI offering of OpenAI. GPT-4o where ‘o’ stands for ‘omni’ is a groundbreaking shift towards more natural and seamless human-computer interactions. Unlike its previous versions, GPT-4o is designed to process and generate a combination of text, audio, and images for a more comprehensive understanding of user inputs.
Let’s discuss some of it’s pros and cons
Pros:
1. Faster Response Times: Optimized architecture allows GPT-4o to generate tokens up to 2x faster than GPT-4 Turbo, with audio response times as low as 232 milliseconds and an average of 320 milliseconds, enhancing real-time interactions for chatbots and virtual assistants.
2. Improved Multilingual Support: A new tokenizer enables GPT-4o to better handle non-English languages, using significantly fewer tokens for languages like Gujarati, Telugu, and Tamil.
3. Larger Context Window: With a 128K token context length (about 300 pages of text), GPT-4o can manage more complex tasks and maintain context over extended interactions. Its knowledge cut-off date is October 2023.
4. Enhanced Vision Capabilities: Improved vision capabilities allow GPT-4o to better understand and interpret visual data.
5. Video Understanding: GPT-4o processes video inputs by converting them into frames, understanding visual sequences without audio.
Cons:
1. Transparency: There is limited information about the data used to train GPT-4o, its model size, compute requirements, and creation techniques. This lack of transparency hinders a full assessment of its capabilities, biases, and impact. Greater openness from OpenAI would improve trust and accountability.
2. Audio Support: Although GPT-4o has advanced multimodal capabilities, its API currently lacks support for audio input, limiting its use in audio processing applications. OpenAI plans to introduce this feature to trusted testers soon.
Gemini 1.5 Pro: Google’s Multimodal AI
Gemini 1.5 Pro, Google’s top multimodal assistant offers advanced features for complex tasks like: text understanding, image/video understanding and large-scale applications. It’s versatile and capable of handling everything from creative content generation to intricate data analysis.
This models can process and generate content across text, images, audio, and video with minimal response latency, enabling more sophisticated and context-aware applications.
Pros
1. Natively Multimodal with Long Context: Gemini 1.5 Pro supports 1 million token context window along with that it is also capable of handling text, images, audio, and video inputs. Google AI Studio offers a waitlist for 1.5 Pro with a 2 million token context window.
2. Pricing and Context Caching: Gemini 1.5 Pro costs $3.50 per 1 million tokens. Context caching, available in June 2024, allows sending large files only once, enhancing affordability and utility.
3. Gemini Nano: Expanding beyond text only inputs to include images. Starting with Pixel phones, Gemini Nano will process text, sight, sound, and spoken language.
4. Project Astra: Project Astra, building on Gemini models, is a prototype AI agent that processes video and speech inputs into a timeline of events, continuously encoding video frames for efficient recall.
Cons
1. Cost: Access to Gemini 1.5 Pro, especially with the expanded context window, can be expensive for individual users or small organizations.
2. Access: Gemini 1.5 Pro model is currently in limited preview, granting access to select developers and organizations.
Claude 3 Opus: Anthropic’s Multimodal AI
Claude 3 Opus is the most advanced model in Anthropic’s latest AI suite, sets new benchmarks in cognitive tasks. As part of the Claude 3 family, Opus offers the highest performance and capabilities among Anthropic’s other models namely: Sonnet and Haiku.
Opus also demonstrates improved performance in several key areas:
- Enhanced reasoning and problem-solving skills, outperforming GPT-4 and Gemini Ultra in benchmarks such as graduate-level expert reasoning (GPQA) and basic mathematics (GSM8K).
- Increased context window of up to 200,000 tokens, allowing for more comprehensive and contextually rich responses
Pros
1. Enhanced reasoning and problem-solving abilities improve accuracy and efficiency in complex tasks.
2. Multimodal processing and multilingual support expand its applicability across various domains.
3. Increased context understanding and language fluency enable more natural and human-like interactions.
Cons
1. Potential biases and inaccuracies, reflecting biases in its training data and sometimes generating incorrect information.
2. Limited image processing capabilities, unable to identify individuals and struggling with low-quality visuals or spatial reasoning tasks.
GPT-4o Vs. Gemini 1.5 Pro vs. Claude 3 Opus: Model Performance
GPT-4o consistently outperforms other models in most evaluation sets, demonstrating superior capabilities in understanding and generating content across multiple modalities.
Evaluation Metrics
- MMMU (%)(val): Multimodal Matching Accuracy, which evaluates how well the model matches content across different modalities. GPT-4o leads with 69.1%, followed by GPT-4T at 63.1%, with Gemini 1.5 Pro and Claude Opus both at 58.5%. This shows GPT-4o’s strong multimodal capability and reasoning.
- MathVista (%)(testmini): Measures mathematical reasoning and visual understanding accuracy. GPT-4o tops with 63.8%, while Claude Opus scores the lowest at 50.5%.
- AI2D (%)(test): Assesses performance on the AI2D dataset involving diagram understanding. GPT-4o achieves 94.2%, leading the chart, while Claude Opus scores 88.1%.
- ChartQA (%)(test): Evaluates the model’s performance in answering questions based on charts. GPT-4o has the highest accuracy at 85.7%, followed by Gemini 1.5 Pro at 81.3%, and Claude Opus at 80.8%.
- DocVQA (%)(test): Assesses the model’s ability to answer questions based on document images. GPT-4o leads with 92.8%, and Claude Opus scores 89.3%.
- ActivityNet (%)(test): Measures performance in activity recognition tasks. GPT-4o scores 61.9%, Gemini 1.5 Pro scores 56.7%, and Claude Opus is not listed.
- EgoSchema (%)(test): Evaluates the model’s understanding of first-person perspectives or activities. GPT-4o scores 72.2%, Gemini 1.5 Pro scores 63.2%, and Claude Opus is not listed.
Overall, GPT-4o generally outperforms Gemini 1.5 Pro and Claude 3 Opus across evaluated metrics, although each model has its strengths and weaknesses in different tasks.
Conclusion
In summary, OpenAI’s ChatGPT-4o appears to be the most capable and versatile across various task, with Gemini 1.5 pro being closest to it which is offered by Google. Claude 3 Opus offers cost efficiency and a large context window, making it an attractive option for applications requiring deep context understanding. Each model has its strengths and weaknesses, so the choice should be guided by the specific needs and requirements of the task.
With every gradual updates, all the three models will become more advance and capable. Since every company is trying to leverage these models to increase there productivity we should be careful that we don’t totally depend on these powerful AI’s to take high stake decision for the company.
FAQs
1. How does the performance of these models compare across different evaluation metrices?
GPT-4o generally outperforms across metrics like multimodal matching, math reasoning, diagram understanding. Each model has it’s own strengths/weaknesses.
2. What are the pros and cons of using ChatGPT-4o?
Pros: Faster response, better multilingual, larger context window, enhanced vision/video
Cons: Limited transparency, no audio input currently
3. How does the pricing and accessibility of Gemini 1.5 Pro compare to the other models?
Gemini 1.5 Pro costs $3.50 per 1M tokens which is a can be in expensive side. Gemini 1.5 Pro is trying to reduce context caching to improve affordability.
4. What are the key strengths and weaknesses of Claude 3 Opus?
Strengths: Enhanced reasoning, large context window, language fluency
Weaknesses: Potential biases, limited image processing.
5. How do these models handle issues of bias, transparency, and accountability?
All three company OpenAI, Anthropic and Google have given limited details provided for ongoing efforts for transparency, bias mitigation, ethical AI development.
6. What are some important considerations for organizations while using these powerful AI tools?
Companies should maintain critical perspective in major decision making and they should not entirely depend on AI. At the end human oversight is crucial
