Meta AI Llama 3 vs. ChatGPT 4: A comparative analysis of AI assistant capabilities

Meta AI Llama 3 vs. ChatGPT 4: A comparative analysis of AI assistant capabilities

By Ammar Ahmed

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With the debut of Meta AI’s Llama 3, we’re witnessing a true leap in AI assistants. Being seamlessly integrated across multiple social media platforms like Facebook, Llama 3 is set to revolutionize real-time digital interactions. Mark Zuckerberg boasts that it’s the most intelligent free AI assistant out there, which directly throws the gauntlet down to OpenAI’s ChatGPT 4. 

The question everyone is asking: Will Llama 3 outperform ChatGPT 4? In this article, we’ll provide a comparative analysis of the capabilities of each technology.

What is Meta AI Llama 3 and how to access it?

Meta AI’s Llama 3 is a versatile large language model that supports multimodal inputs. This helps it process and generate outputs based on text and other data types like images and videos. Integrated into Meta’s social media apps, Llama 3 enhances user experience by facilitating more intuitive interactions with technology.

To access the Meta AI assistant, visit the website and log in using your Facebook credentials. This login process allows you to save your conversation preferences and enhances your interaction with Meta AI. 

Meta AI is also accessible across Meta’s other platforms, including social media apps. Within Facebook, Instagram, Messenger, and WhatsApp, tap the search icon to find a modified search bar labeled “Ask Meta AI anything.” As you type, the AI will suggest relevant queries, identified by a blue circle next to them. When you tap the blue circle, it opens a direct chat window with Meta AI. Also, if you notice Meta AI under a post in your feed, it will offer questions you can ask about the content viewed.

Meta AI Llama 3 vs. ChatGPT 4: A detailed comparison

This section will compare the features, capabilities, and applications of both AI assistants to determine which model might better serve user needs.

Comparison table of Meta AI Llama 3 and ChatGPT 4

Technical specifications

Llama 3 operates with 70 billion parameters, a modest number compared to ChatGPT 4’s massive 1.7 trillion parameters​​. This size discrepancy impacts the processing capabilities and influences the ability of AI assistants to manage complex tasks and data sets.

Despite its smaller parameter count, Llama 3 competes admirably in various AI benchmarks. It challenges the larger AI models such as ChatGPT 4 in tasks that demand quick processing. However, the extensive parameter base of ChatGPT 4 allows it to excel in more complex scenarios that require high-level reasoning.

Performance and scores

Llama 3 performs well in undergraduate-level benchmarks, scoring 82% on the MMLU 5-shot test, just behind GPT 4’s 86.4%. This suggests that while ChatGPT 4 leads in raw processing power, Llama 3 remains competitive in basic language tasks.

On more complex tasks requiring advanced reasoning, Llama 3 surprisingly edges out with a 35.7% score in graduate-level benchmarks, against GPT 4’s 39.5%. In coding-related evaluations, GPT 4’s superiority is evident again, scoring 85.9% in the HumanEval benchmark, surpassing Llama 3’s 81.7%. This reveals ChatGPT 4 as the preferable choice for programming and coding applications.

Multimodal capabilities 

ChatGPT 4 is a powerful multimodal AI platform that accepts visual, textual, and audio inputs. It also supports document attachments in multiple formats. This capability allows users to engage in diverse conversations and perform tasks that require multimedia inputs.

Meta AI’s Llama 3 currently supports only textual inputs. While it can generate images from text commands, its capabilities are limited to text-based interactions. Meta AI plans to expand its multimodal functions to match the capabilities of platforms like ChatGPT 4.

Real-world applications

Llama 3, being open-source, is particularly favored for customized AI tasks. It allows developers to modify and integrate the model into unique use cases like language translation tools and efficient chatbots​. ChatGPT 4’s sophisticated language capabilities make it ideal for generating high-quality content for creative writing, scriptwriting, and automated stories.

The difference in accessibility also affects their application in real-world scenarios. ChatGPT 4’s extensive training data enable its use in more complex tasks requiring nuanced language, such as educational tools​. Meanwhile, Llama 3 is free, which makes this AI language model a go-to option for startups and academic researchers who require reliable AI performance without any expenditure.

Open source and proprietary status

Llama 3 is an open source large language model that allows developers and researchers worldwide to access and modify its code. This transparency promotes innovation and broad experimentation within the tech community. The open-source nature of Llama 3 promotes a collaborative approach to AI development and reduces costs for users and developers.

OpenAI’s ChatGPT 4 operates on a proprietary basis, which limits its modification by external parties to ensure consistent quality and control. This approach provides high standards but may restrict wider creative exploration and customization that open-source models support.

Text-to-visual capabilities

Meta AI Imagine offers a simple approach to AI image generation, ideal for those new to the technology. It’s a free tool, limited to generating four image variations from a single prompt, without options for history tracking or fine-tuning outputs. This simplicity makes Meta AI a good starting point for casual users interested in exploring AI-driven text-to-visual capabilities.

DALL-E 3 by OpenAI, integrated with ChatGPT 4, provides a more refined experience. It transforms user prompts into better-suited queries for generating images. Although it may produce images that sometimes appear too polished, DALL-E 3 excels in handling complex and high-context prompts. 

Testing problem-solving capabilities:

To assess the intelligence and logic of AI assistants, it is crucial to understand their problem-solving competence. This section will evaluate how ChatGPT 4 and Meta AI Llama 3 perform in various challenges and apply their cognitive dexterity.

Task 1: Solving a complex math problem


ai93 +bi35 +ai24 – bi86 = 40 + 20i

ChatGPT 4:

A math task solved by ChatGPT 4

Meta AI Llama 3:

A math task solved by Meta AI Llama 3Final results:
ChatGPT 4’s answer is accurate, while the response of Meta AI Llama 3 is incorrect.

Task 2: Generating an image from a prompt


Imagine a futuristic cityscape at dusk, where the sky is a gradient of orange to deep blue. In the foreground, there’s a smart transportation hub with autonomous electric vehicles and hovering drones. Above, a network of skywalks connects the buildings crowded with people. 

ChatGPT 4:

An image generated by ChatGPT 4

Meta AI Llama 3:

An image generated by Meta AI Llama 3

Final results:
Although Meta AI processed the image much faster, ChatGPT 4’s rendition closely aligns with the provided prompt.

Task 3: Analyzing a bug in the code


def printsample_matrix(matrix):

for a in range(matrix.getLength(0)):

for b in range(matrix.getLength(0)):


Please find a bug in the above code and provide the fixed version.

ChatGPT 4:

ChatGPT 4 analyzes a bug in the code

Meta AI:

Meta AI Llama 3 analyzed a bug in the code

Final results:
Both AI assistants accurately analyzed the code to identify the bug and provided the correct version of the code.

Ethical considerations of AI assistants:

The open-source nature of Meta AI’s Llama 3 allows for wider scrutiny and adaptation by developers. This approach enables organizations to modify these models to suit their specific requirements. However, the model’s accessibility poses risks, as it could be misused for creating misleading content.

ChatGPT 4 faces scrutiny for the lack of transparency regarding its training data and development. The model’s outputs may unintentionally perpetuate harmful stereotypes or disseminate unreliable information. Moreover, using collected data for training raises concerns about user privacy, urging the need for strict data management policies.

Llama 3 and ChatGPT 4 face ensuring their outputs do not contain or propagate toxic content. Ensuring the ethical use of AI requires robust regulations and active monitoring to prevent the spread of harmful material. These measures are crucial to mitigate risks and guide the responsible deployment of advanced AI technologies.

Future prospects and developments:

The future of ChatGPT 4 looks promising as OpenAI is continuously improving how businesses and individuals interact with AI. By refining its response accuracy and aligning more closely with ethical guidelines, ChatGPT 4 will likely become integral to industries requiring reliable technology. 

Meta AI’s Llama 3’s ongoing development, particularly with its upcoming model with 400B parameters, might close the performance gap compared to ChatGPT 4. The future models will have improved multimodal functions and the ability to understand different languages. As more developers engage with the open-source platform, Llama 3 is expected to evolve rapidly and integrate unique AI-driven innovations.

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