Comparing GPT-4o, Llama 3, and Gemini 1.5 Pro: What's best for you?

Comparing GPT-4o, Llama 3, and Gemini 1.5 Pro: What's best for you?

With the launch of GPT-4o last week and Llama 3 earlier in April, we saw waves of conversations, mentions and reactions across social media. But what does this mean for you? What differences can it make to the way you do business? This is a fantastic opportunity to introduce the GenAI models in detail, in jargon-free language and make a comprehensive comparison of GPT-4o, Llama 3 and Google’s Gemini 1.5 Pro, which was launched earlier this year and made an equal noise. 

GPT-4o: Natural human-computer interaction

GPT-4o by OpenAI is an advanced language model that continues to evolve from previous versions. It incorporates improvements in understanding and generating human-like text and supports a broader range of applications. GPT-4o is designed to provide more accurate, relevant, and contextually appropriate responses, making it a robust tool for conversational AI needs.

Users will be able to download a free version of GPT-4o, but the paid version will have five times the capacity limits.

The most interesting development of GPT-4o is the voice assistant, which can generate content or understand commands in voice, image or text and perform live translations in 50 languages. It can also respond in real time and observe body motion and facial expressions.

What’s new? Benefits and Capabilities of GPT-4o 

Let’s explore the capabilities of GPT-4o

  • Speed and Efficiency: Significantly faster response times compared to previous models, enhancing productivity and customer interactions.
  • Multimodal Processing: Handles text, audio, and images simultaneously, enabling diverse and seamless interactions.
  • Voice Interaction: Allows natural spoken conversations, enhancing accessibility and user experience.
  • Emotional Intelligence: Improved understanding of emotional cues, tone, and sentiment in language, allowing for empathetic responses.
  • Advanced Language Support: Better performance in non-English languages.
  • Real-Time Content Generation: Generates text, audio, and image outputs quickly, aiding in faster content creation.
  • Enhanced Customer Engagement: Personalises interactions based on customer preferences and sentiment.
  • Built-in Safety Systems: Advanced safety features across all modalities, including filtering training data and refining model behaviour.

Limitations of GPT-4o:

  • Accuracy Variability: Inconsistent accuracy in interpreting complex visuals and emotions.
  • Bias Susceptibility: Potential biases in training data can lead to misinterpretations.
  • Ethical Concerns: Privacy and consent issues, especially with audio and visual data.
  • Early Development Stages: Some features are still in alpha testing and not widely available.

GPT-4o use cases for businesses:

Here are some ways you can use tGPT-4o at your business:

  • Customer Service: Enhance customer interactions through responsive and empathetic AI agents, reducing wait times and improving satisfaction.
  • Marketing Content Creation: Automate and accelerate the creation of engaging social media posts, email campaigns, and promotional materials.
  • Data Analysis and Insights: Quickly summarise market research, analyse customer feedback, and extract actionable insights to inform business strategies.

Llama 3: The Android of the AI world

Llama 3 by Meta aspires to be something like the "Android of the AI world" due to its open-source nature and a high degree of customisability, much like the Android operating system in the mobile industry. Just as Android allows developers to modify and tailor the OS to their needs, Llama 3 offers extensive flexibility for customisation and enhancement. This enables a broad range of applications and innovations, supported by a robust community of developers contributing to its continuous improvement. 

Featuring models with up to 70 billion parameters, Llama 3 integrates advanced functionalities like improved reasoning abilities, enhanced token efficiency, and support for multiple languages. With significant improvements over its predecessors, including better performance in nuanced tasks and more efficient use of computational resources, Llama 3 stands out as a versatile tool for developers and businesses.

Source: Meta

What’s new? Benefits and Capabilities of Llama 3

  • Creative Writing and Problem Solving: Excels in generating engaging and inventive content.
  • User Interaction: Known for its friendly and positive conversational tone, enhancing customer interactions and satisfaction.
  • Simplicity Preference: Performs well with less complex prompts and is suitable for straightforward tasks.
  • State-of-the-Art Performance: Offers improved reasoning, code generation, and instruction following.
  • Improved Token Efficiency: Features a tokeniser that yields up to 15% fewer tokens than Llama 2, enhancing efficiency.
  • Broader Availability: Accessible on multiple platforms, including AWS, Google Cloud, and Microsoft Azure.
  • Open Source: Embraces the open-source ethos, allowing extensive customisation and community collaboration.
  • Built-in Safety Systems: Incorporates Llama Guard 2, Code Shield, and CyberSec Eval 2 to ensure safe and secure model interactions.
  • Data Filtering Pipelines: Utilises heuristic filters, NSFW filters, semantic deduplication, and text classifiers to maintain high-quality training data.

Limitations of Llama 3

  • Complex Task Performance: Struggles with mathematical calculations, complex coding tasks, and reasoning requiring deep technical expertise.
  • Accuracy Decline with Complexity: Accuracy tends to decline with more complex prompts.
  • Multilingual Performance: Limited performance in non-English languages compared to English.
  • Safety Concerns: Requires continuous monitoring and updates to address potential risks in code generation and cybersecurity.
  • Early Development Stages: Some capabilities, such as multilingual and multimodal support, are still in development and not yet fully realised.

Llama 3 use cases for businesses:

  • Empathetic GenAI Assistant: You can leverage Llama 3's advanced language processing capabilities to simulate engaging and empathetic dialogues with users. A Llama 3-powered assistant can actively listen, identify patterns in conversations, and provide relevant assistance or guide users to appropriate resources. 
  • AI Coding Assistant: Llama 3 can be used to create an AI coding assistant that enhances developers' productivity. By integrating Llama 3 with tools like VSCode and enabling features such as tab-autocomplete, developers can receive real-time coding suggestions and assistance. This assistant can improve coding efficiency by providing relevant code snippets, debugging tips, and best practice recommendations.
  • Superfast Research Assistant: Llama 3 can be deployed as a research assistant that quickly processes and summarises complex topics. It can handle large volumes of information, generate detailed research reports, and provide concise summaries at high speeds. This use case is particularly beneficial for academic research, market analysis, and any scenario requiring rapid information processing and summarisation.

Gemini 1.5 Pro: Next Generation Capabilities

Gemini 1.5 Pro by is the latest iteration in Google's AI offering, bringing enhanced capabilities and improvements designed to meet the needs of modern enterprises. This version focuses on robust multimodal processing, sophisticated reasoning, and advanced coding tasks, making it a versatile tool for various industries.

This promise of a world responsibly empowered by AI continues to drive our work at Google DeepMind. For a long time, we’ve wanted to build a new generation of AI models inspired by how people understand and interact with the world. AI that feels less like a smart piece of software and more like something useful and intuitive — an expert helper or assistant.

- Demis Hassabis, CEO and Co-Founder of Google DeepMind

What’s new? Benefits and Capabilities of Gemini 1.5 Pro

  • Multimodality: Understands and processes text, images, audio, video, and code, allowing seamless integration of various data types.
  • Native Audio Understanding: Enhanced audio processing capabilities that provide better understanding and generation of audio content.
  • Sophisticated Reasoning: Excels at complex reasoning tasks, making it suitable for scientific research, finance, and other data-intensive fields.
  • Advanced Coding: Generates, debugs, and explains high-quality code across popular programming languages, enhancing software development productivity.
  • Contextual Understanding: Provides accurate and relevant responses by understanding the context of queries, which is useful for complex research tasks.
  • Creative Outputs: Generates art, music, and multimodal storytelling, facilitating creative and expressive applications.
  • Personalised Search: Tailors search results based on user interactions, leading to more efficient information discovery.
  • Explainable AI: Offers clear explanations of its reasoning and decision-making processes, which builds trust and understanding in AI systems.
  • Efficient Resource Use: Designed for deployment on a wide range of devices and platforms, ensuring broad accessibility and integration possibilities.
  • Built-in Safety Classifiers: Identifies and filters out harmful content, such as violence and negative stereotypes.
  • Adversarial Testing: Utilises advanced adversarial testing techniques to identify and mitigate potential safety issues.

Limitations of Gemini 1.5 Pro

  • Technical Knowledge Required: Requires expertise in coding and AI concepts, making it less accessible for non-technical users.
  • Bias and Fairness: Inherits biases from training data, which needs continuous addressing to ensure ethical use.
  • Explainability and Transparency: While it offers explanations, they might not always be easily interpretable by all users.
  • High Computational Cost: Running advanced models like Gemini requires significant computational resources, limiting scalability for smaller users.
  • Ethical Considerations: Powerful capabilities raise concerns about potential misuse, necessitating strong guidelines and safeguards.

Gemini 1.5 Pro use cases for businesses

  • Healthcare Enhancement: Google Gemini AI can revolutionise healthcare by improving diagnostic accuracy and personalised treatment plans. It excels in medical imaging analysis, offering unparalleled precision in detecting diseases from scans, which can lead to earlier interventions and better patient outcomes. Additionally, Gemini can assist in creating tailored care plans by analysing extensive patient data and genetic information, optimising treatment efficacy and reducing healthcare costs. It also supports drug discovery by accelerating research and development, potentially bringing life-saving treatments to market faster.
  • Creative and Expressive Capabilities: Gemini’s multimodal abilities enable it to generate innovative content across various formats, including text, images, audio, and video. This makes it an invaluable tool for artistic and creative industries. For example, it can compose music, generate visual art, and create interactive narratives combining multiple media types. Such capabilities can be used in entertainment, marketing, and educational content creation, providing a versatile tool for storytellers and artists.
  • Advanced Coding and Software Development: Gemini is proficient in understanding, generating, and debugging code across multiple programming languages such as Python, Java, and C++. It can be used to automate coding tasks, suggest improvements, and fix bugs, significantly enhancing developer productivity. This capability extends to creating more advanced coding systems like AlphaCode 2, which excels in competitive programming by solving complex problems that require both coding skills and theoretical knowledge.

Comparison between GPT-4o, Llama 3 and Gemini 1.5 Pro models

Getting Started with End-to-End AI Transformation

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