Understanding the Differences for Businesses

A decade ago, Large Language Models (LLMs) were limited to understanding text classification, keyword extraction, & basic NLP tasks. Now, they’ve become an essential part of your everyday workflow. An example is Apple using ChatGPT to implement their Apple Intelligence. 

Every business doesn’t want to just save time, they want to direct their efforts towards innovation. The demand for efficiency and multitasking has driven the rapid advancement of generative AI models like ChatGPT.  

With several versions now available, including the recent ChatGPT 4, it’s crucial to understand how each model differs and which one might suit your needs best.  

In this article, we’ll break down the key differences between ChatGPT 3.5 vs 4 to help you decide.

What is ChatGPT?

When ChatGPT launched, everyone wanted to try it! Was this the future? Back then, it felt more like a novelty, fueling the rise of LinkedIn influencers selling ‘must-have’ prompt courses. 

Now, ChatGPT can perform a considerable amount of tasks, save time, and make our workflow convenient–right from simple queries to complex tasks such as mimicking human behavior. 

Here’s how this happened:

1. Model Architecture: Early versions of the LLM used smaller Transformer models, limited in depth. GPT-3 scaled to 175 billion parameters, enhancing response quality.

   ChatGPT 3.5 introduced Reinforcement Learning from Human Feedback (RLHF) — this meant that it was learning from your prompts, hence making prompt engineering a sought after skill.

   By GPT-4, multi-modal capabilities and advanced problem-solving made it more adaptable and intelligent.

2. Training Data: Initial models used broad text corpora. GPT-3 used diverse datasets, improving versatility.

   GPT-4 fine-tuned data for specialized tasks, excelling in areas like coding, legal analysis, and reasoning.

   By now, it had enough data and training to be able to accurately mimic human behaviour.

ChatGPT is no longer just a cool tool—it is shaping how we work, create, and solve problems.

ChatGPT generated the above response in the following three stages:

1. Tokenization: Your input text is broken down into ‘tokens’—smaller chunks like words or sub-words—so the model can process the information more efficiently.
2. Contextual Understanding: The model is pretrained to determine the context of the conversation, using attention mechanisms to focus on the most relevant parts of the input text.
3. Prediction: Based on its trained data, ChatGPT predicts the most likely sequence of words to follow, iterating token-by-token to generate a coherent response.
4. Output Generation: The model combines these predictions into a final output, which is returned to you as a response.

The process is highly prediction based, meaning ChatGPT doesn’t have fixed answers—it ‘guesses’ the best response based on pretrained data from vast amounts of resources.

ChatGPT 3.5: The Foundation

ChatGPT 3.5 is a large language model (LLM) developed by OpenAI. It leverages advanced deep learning techniques, specifically Transformer-based architectures, to understand and generate human-like text. 

It’s designed to process vast amounts of data and interact with users conversationally. This model is an evolution of GPT-3, with improvements in performance and efficiency. 

Key Capabilities of ChatGPT 3.5

• Natural Language Understanding: Interprets complex queries and provides detailed, context-aware responses
• Text Generation: Creates coherent, grammatically correct, and engaging content for various purposes
• Multi-turn Conversations: Maintains context across dialogue turns for fluid and consistent interactions
• Language Translation: Converts text between multiple languages with reasonable accuracy
• Summarization: Produces concise summaries of lengthy texts
• Programming Assistance: Provides coding help, debugging, and code generation in multiple programming languages
• General Knowledge and Research: Answers factual questions using its pre-trained dataset knowledge
• Adaptability: Customizes responses based on user tone, intent, or style preferences

While highly capable, ChatGPT 3.5 operates within the constraints of its training data (up to 2021) and cannot access real-time information (which is where GPT-4 fills the void!)

McKinsey had stated that executives should be using ChatGPT for the following use cases:

1. Create or improve customer chatbots to resolve questions about products and services, including cross-selling.
2. Write code and documentation to accelerate and scale developments.
3. Identify clauses of interest, such as penalties owed, through comparative document analysis.
4. Provide self-serve HR functions and automate first-line interactions such as employee onboarding.

Cost-Benefit Analysis of ChatGPT 3.5

Cost: ChatGPT 3.5 offers a free tier and a Plus plan at $20/month, providing faster responses and priority access.

Benefits:

• Efficiency: Saves hours on tasks like drafting, summarizing, and coding.
• Accuracy: Delivers context-aware outputs, reducing follow-ups.
• Scalability: Supports customer service, content creation, and more.

ROI: A $20 subscription can save professionals hundreds of dollars in time weekly.

Trade-Offs: Occasional inaccuracies require human review, especially for niche or critical tasks.

Verdict: For $20/month, ChatGPT 3.5 offers significant time and cost savings. Start with the free tier and upgrade if it fits your workflow!

ChatGPT 4: Innovative Upgrade

ChatGPT-4 is built using the transformer architecture and trained on a large corpus of text data to understand and generate human-like responses in natural language. 

It leverages advanced machine learning techniques, including deep learning and unsupervised learning, to predict the next token (word or part of a word) based on context from the input provided.

ChatGPT-4 brings a lot of breakthrough features, such as:

1. Multimodal abilities: One of the most significant upgrades in GPT-4 is its ability to handle both text and image inputs. With the vision-language model integration, it can process and understand images and text.
2. Enhanced model size and architecture: GPT-4 has ~1.8 trillion parameters across 120 layers, which is over 10 times larger than GPT-3. This increased scale enables it to perform better on tasks requiring sophisticated reasoning.
3. Advanced Reasoning Capabilities: When asked to derive a conclusion from contradictory premises, GPT-4 can demonstrate improved capacity for higher-order reasoning. This is due to its enhanced attention mechanisms, allowing it to prioritize relevant information within long or complex inputs.
4. Contextual Continuity and Memory: GPT-4 has better contextual memory, enabling it to maintain coherent conversations across extended interactions. It can remember information across turns, resulting in a more natural and fluid dialogue where responses remain contextually aligned with the input.
5. Scalability and Efficiency: GPT-4 has been optimized for better performance efficiency despite its increased scale. It leverages techniques like model pruning and layer fusion, which enable it to provide faster responses while maintaining high accuracy and low latency, making it more suitable for real-time applications such as virtual assistants, chatbots, and live technical support.

How are people using ChatGPT-4?

Skanska, a global construction company, has successfully implemented AI in quality control using a system trained on thousands of annotated images for site monitoring. The AI can quickly identify quality issues, such as improper installations and safety hazards, improving the accuracy and efficiency of inspections. 

They have also built Sidekick, an AI chatbot using Microsoft Azure and GPT-4, which helps employees quickly find information, create content, summarize documents, and work together securely.

Have people seen ROI by using ChatGPT in their business? Yes! Using ChatGPT can boost your issue resolution rate by 14% and cut ticket handling time by 9%.

ChatGPT 3.5 vs 4: Deep dive

While we’ve discussed both models in-depth till now, we now need to get to the burning question: ChatGPT 3.5 vs 4: which is better?

GPT-4 is 82% less likely to generate disallowed content and 40% more likely to provide factual responses compared to GPT-3.5. 

This improvement stems from refined training using user feedback, expert consultations, and real-world use cases, addressing previous concerns of misinformation and bias.

Let’s Do a Deeper Dive:

Feature	ChatGPT 3.5	ChatGPT 4
Model Architecture	Transformer-based with limited context	Enhanced transformer with extended context window
Multimodal Support	Text-only	Text, image, and audio inputs
Contextual Memory	8,000 words	64,000 words (Turbo: 128,000 words)
Accuracy	60-70% factual accuracy	90% factual accuracy, 82% less disallowed content
Reasoning & Logic	Basic reasoning	Advanced, multi-step logical reasoning
Safety	Moderate safeguards	Improved safeguards, reduced bias
Performance on Exams	10th percentile on Bar Exam	90th percentile on Bar Exam

Performance Benchmarks

Metric	ChatGPT 3.5	ChatGPT 4
Accuracy	85%	93%
Task Completion Speed	~0.5 seconds per query	~1 second per query (due to more complex calculations)
Error Rate	Around 10%	Significantly lower at around 5%, especially in complex queries

Cost Comparison Calculator

Plan Option	ChatGPT 3.5	ChatGPT 4
Free Plan	50 queries/month	No free plan available for ChatGPT 4
Subscription (Monthly)	$10 for unlimited access	$20 for unlimited access
Pay-as-you-go (API)	$0.002 per 1k tokens	$0.03 per 1k tokens

Industry-Specific Use Cases

Industry	ChatGPT 3.5 Use Cases	ChatGPT 4 Use Cases
Customer Support	Handles basic queries, FAQs, simple troubleshooting	Provides personalized customer interactions, complex issue resolution, and proactive support
Healthcare	Assists with general medical questions	Offers in-depth medical research, provides diagnostic support, and assists in personalized treatment suggestions
Education	Provides basic tutoring, helps with homework	Creates adaptive learning environments, offers personalized curriculum, and provides instant feedback on complex topics
E-commerce	Recommends products based on simple inputs	Generates highly personalized product recommendations, predicts trends, and offers dynamic pricing insights
Finance & Accounting	Basic financial data analysis and reporting	Complex financial forecasting, budget management, and investment analysis
Marketing & Advertising	Generates simple ad copy and marketing ideas	Develops advanced marketing strategies, creates high-conversion ad copy, and predicts consumer behavior trends

Common Myths Debunked

Myths	Reality (ChatGPT-4)
GPT-4 is only a bigger version of GPT-3.5	GPT-4 is a fundamentally enhanced model with multimodal capabilities and advanced reasoning.
GPT-4 is always faster than GPT-3.5	GPT-4 is slower in processing complex tasks due to its advanced capabilities, but it handles more sophisticated problems.
GPT-4’s improvements are marginal	GPT-4 shows substantial improvements in reasoning, memory, and factual accuracy, offering a 40% better factual response rate.
GPT-4 is free to use	GPT-4 incurs higher API costs due to its computational complexity compared to GPT-3.5.

How to Choose a Model?

We’ve understood each model and also compared them with each other. Now, we’ll discuss your company’s needs and help you make a decision with a framework. 

Scalability Factors

Factor	ChatGPT-3.5	ChatGPT-4
Response Time	Faster for simple queries	Slower for complex queries due to advanced reasoning
Resource Requirements	Moderate, lower compute cost	Higher, requires powerful infrastructure for multimodal tasks
Support for Multi-user Load	Handles moderate traffic well	Optimized for high traffic, enterprise-level applications

Integration Capabilities

Capability	ChatGPT-3.5	ChatGPT-4
API Access	Available via OpenAI API	Available via OpenAI API
Multimodal Input	Not supported	Supports text, images, and audio inputs
Custom Model Tuning	Limited customization options	Enhanced customization, fine-tuning options available
Third-party Integrations	Basic integration support	Seamless integration with enterprise-level platforms and APIs

Step-by-Step Evaluation Process

1. Define Use Case: Identify the complexity and nature of the task (e.g., simple queries vs. advanced reasoning, multimodal needs).

   Consider: Task complexity, context window size, need for multimodal inputs.

2. Assess Budget and Resources: Evaluate whether the additional cost of GPT-4 aligns with your budget, infrastructure, and scalability needs.

   Consider: API cost per request, compute power requirements, long-term scalability.

3. Review Integration and Deployment: Assess how well each model integrates with your existing systems or products and their ability to handle user load.

   Consider: Third-party integration ease, deployment infrastructure, multimodal support.

Mastering ChatGPT Integration for the Future

While both ChatGPT-3.5 and ChatGPT-4 represent significant milestones in AI development, GPT-4 stands out with its superior capabilities, enhanced accuracy, multimodal input handling, and increased memory. 

User describes how ChatGPT 4 is better than 3

These advancements make GPT-4 more versatile and suitable for complex, real-time applications across industries such as healthcare, law, and creative fields. 

For businesses and developers, choosing the right version depends on task complexity, budget, and scalability needs. 

As AI continues to evolve, understanding these differences and strategically implementing each version will be key to unlocking their full potential in driving innovation and efficiency.

Conclusion

When it comes to ChatGPT 3.5 vs. 4, both models have their own strengths. If you’re looking for a budget-friendly option that handles everyday tasks with ease, 3.5 is a solid pick. But if you need more accuracy, better context understanding, and the ability to work with images, ChatGPT 4 is the way to go. At the end of the day, the right choice depends on what you need—quick and simple, or powerful and precise.

The best way to find out which one suits you? Try them out yourself with Weam AI. you can explore both ChatGPT 3.5 and 4 to see which fits your workflow best. You can Start for FREE!—so why not take them for a spin and see what works for you?

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