ChatGPT 3.5 vs GPT-4 vs GPT-4o: Comprehensive Comparison & Insights
Introduction
In late 2022, ChatGPT made a quiet but powerful debut as a flexible chatbot from a little-known company named OpenAI. In just five days, it attracted 1 million users, outpacing the growth rates of major platforms like Netflix and Twitter. By February 2023, ChatGPT had become the fastest-growing consumer app ever.
As people were still getting used to ChatGPT's impressive abilities, OpenAI released ChatGPT 4.0 in March 2023. This new version, powered by the advanced GPT-4 engine, was a major upgrade over ChatGPT 3.5. It featured better natural language understanding, improved context retention, and more refined responses.
In this article, we'll highlight the key differences between the GPT-3.5 and GPT-4 models. We'll also compare the pricing of all OpenAI models, including the newly introduced ChatGPT 4o.
But first, let's understand what ChatGPT is and how it works.
ChatGPT's Evolution
As the world marveled at ChatGPT's capabilities, OpenAI introduced ChatGPT 4 in March 2023, powered by the advanced GPT-4 engine. This new version marked a significant upgrade from ChatGPT 3.5, especially in understanding natural language, retaining context, and providing more detailed responses.
Understanding ChatGPT
ChatGPT, developed by OpenAI, operates on GPT (Generative Pre-trained Transformer), an advanced language model at the heart of generative AI. These large language models (LLMs) consist of several components that work together to understand and generate language. They function as powerful engines, capable of writing stories, translating languages, and answering questions naturally.
In simple terms, ChatGPT provides a user-friendly interface to interact with GPT. It simplifies the complex process of language understanding and generation, allowing users to input questions, prompts, or requests and receive responses for various tasks, including writing, coding, and creating marketing messages.
Differences Between GPT-3.5 and GPT-4
The primary difference between GPT-3.5 and GPT-4 lies in their size and capabilities. GPT-3.5 was trained on 175 billion parameters, while GPT-4 boasts over 100 trillion parameters, making it significantly larger and more advanced. This improvement enables GPT-4 to deliver more detailed and relevant responses, pushing the boundaries of natural language processing and setting new standards for AI conversational systems.
Multi-Input Processing
One major limitation of ChatGPT 3.5 was its ability to understand and interpret only text input. ChatGPT 4, powered by the GPT-4 engine, can handle multiple types of input, including text and images. In a live demonstration by OpenAI co-founder Greg Brockman, ChatGPT 4 showcased its powerful image processing capabilities, highlighting its ability to understand and respond to both text and image prompts.
Enhanced Processing Power
ChatGPT 4 significantly outperforms ChatGPT 3.5 in solving complex scientific and mathematical problems. It can tackle various problems and equations in subjects like calculus, geometry, and algebra, while ChatGPT 3.5 could only guide users in the right direction without providing actual solutions.
Enhanced Detail and Creativity in ChatGPT 4
One of the notable weaknesses of ChatGPT 3.5 was its difficulty in fully grasping the nuances of natural human speech, often missing the subtleties of jokes or sarcasm. ChatGPT 4.0 has made significant strides in this area, now offering more detailed and refined responses.
In creative tasks, ChatGPT 4.0 excels remarkably. It can produce more polished poems and essays with improved flow and originality. This leap in creativity is largely attributed to its expanded context window, which can retain 25,000 words from conversations for context, a substantial increase from ChatGPT 3.5's 3,000-word limit. For instance, a poem about traffic lights generated by ChatGPT 4.0 displayed a higher level of creativity compared to a similar prompt given to ChatGPT 3.5, which produced a simpler, less imaginative version.
ChatGPT 4.0 is also adept at crafting short stories and essays based on given prompts. It can even tackle longer narratives, such as novels, developing well-thought-out plots and characters, areas where ChatGPT 3.5 previously struggled.
Improved Accuracy and Reduced Hallucinations
ChatGPT 4.0's advancements are not just limited to creative output. Built on the GPT-4 engine, which reportedly utilizes over a trillion parameters, ChatGPT 4.0 offers more precise responses and is less prone to "hallucinations" – generating responses based on inaccurate information.
When ChatGPT 3.5 was first launched, users could sometimes coax it into revealing ways to hack websites or exploit vulnerabilities, a significant security concern. ChatGPT 4.0 addresses these issues, avoiding engagement in:
- Political debates, maintaining a neutral stance
- Malware creation, refraining from assisting in any malicious software development
- War and violence, steering clear of commenting on conflicts like the Ukraine war
According to OpenAI founder Sam Altman, ChatGPT 4.0 "hallucinates significantly less" than its predecessor, making it a more reliable tool for a wide range of applications.
Latest GPT-4 Models and Their Features
OpenAI continues to enhance its GPT models. Following the March 2023 release of GPT-4, several updates and new features have been introduced, including GPT-4 Turbo and GPT-4o models. Here’s a quick comparison of these models:
Comparison of GPT Models
GPT-4
- Model Size: Large-scale transformer
- Token Capacity: 8,000 tokens
- Training Data: Diverse internet sources
- Performance: High accuracy and versatility
- Cost: Standard pricing
- Use Cases: General-purpose AI tasks
GPT-4 Turbo
- Model Size: Optimized large-scale model
- Token Capacity: 16,000 tokens
- Training Data: Enhanced diverse sources
- Performance: Improved speed and efficiency
- Cost: More cost-effective
- Use Cases: High-demand applications
GPT-4o
- Model Size: Task-specific optimization
- Token Capacity: Varies by task
- Training Data: Specialized datasets
- Performance: Specialized task performance
- Cost: Task-dependent pricing
- Use Cases: Niche and specialized applications
Pricing Structure
- GPT-4o:
- Input Cost per 1M tokens: $5.00
- Output Cost per 1M tokens: $15.00
- GPT-4 Turbo:
- Input Cost per 1M tokens: $10.00
- Output Cost per 1M tokens: $30.00
- GPT-4:
- Input Cost per 1M tokens: $30.00
- Output Cost per 1M tokens: $60.00
- GPT-4 (32k context):
- Input Cost per 1M tokens: $60.00
- Output Cost per 1M tokens: $120.00
- GPT-3.5 Turbo (16k context):
- Input Cost per 1M tokens: $0.50
- Output Cost per 1M tokens: $1.50
- GPT-3.5 Turbo Instruct (4k context):
- Input Cost per 1M tokens: $1.50
- Output Cost per 1M tokens: $2.00
As of July 18, 2024, OpenAI has launched GPT-4o mini, a cost-effective and energy-efficient small AI model, priced at 15 cents per million input tokens and 60 cents per million output tokens. It outperforms the GPT-4 model in chat preferences and scored 82% on the MMLU benchmark. The GPT-4o mini is over 60% cheaper than GPT-3.5 Turbo and supports text and vision, with future plans for multimedia support. It will be available to ChatGPT's Free, Plus, and Team users starting July 18, 2024 and enterprise users at the end of July 2024.
OpenAI's ChatGPT Pricing and Comparison with Competitors
OpenAI's pricing models include various options for its different versions, including the latest ChatGPT 4. For a comprehensive comparison of GPT-4 Turbo, Gemini Claude 3 Opus, and Google Gemini 1.5 Pro, you can find detailed information here.
Comparing GPT-4o and GPT-4: Key Updates and Differences
In May 2024, OpenAI introduced GPT-4o, an updated version of its language model. This new iteration, launched on May 13, 2024, was created to meet the growing needs of users and the rapidly evolving artificial intelligence market. In this article, we'll compare GPT-4o with the older GPT-4, focusing on their capabilities and differences, particularly in the context of text-based tasks.
Why GPT-4o is Considered Better Than GPT-4
In many cases, GPT-4o outperforms GPT-4. OpenAI now describes GPT-4o as its flagship model, highlighting its improved speed, lower costs, and multimodal capabilities. These enhancements make GPT-4o an attractive option for many users.
However, some users may still prefer GPT-4, especially in business settings. Since GPT-4 has been available for over a year, it is well-tested and familiar to many developers and businesses. This stability is crucial for critical and widely used applications, where reliability may take precedence over the latest features or cost savings.
Economic Considerations and Transition Costs
Although GPT-4o is generally more cost-effective for new deployments, IT teams managing existing setups might find it more economical to continue using GPT-4. Transitioning to a new model involves costs, particularly for systems tightly integrated with GPT-4, where switching models could require significant infrastructure or workflow changes.
Multimodal Capabilities and API Limitations
GPT-4o's multimodal capabilities, such as text, image, audio, and video processing, are a significant advancement. However, these capabilities might differ for API versus web users. As of a May 2024 post in the OpenAI Developer Forum, GPT-4o does not yet support image generation or audio through the API. Therefore, enterprises primarily using OpenAI's APIs might not find GPT-4o compelling enough to switch until these multimodal capabilities are fully available through the API.
Implications for ChatGPT Users
The introduction of GPT-4o as the new default version of ChatGPT brings major changes for users. One significant update is the availability of multimodal capabilities. Moving forward, all users will be able to interact with ChatGPT using text, images, audio, and video, and create custom GPTs – functionalities that were previously limited or unavailable.
These advancements might make the Plus subscription less appealing to some users, as many formerly premium features are now accessible in the free tier. However, paid plans still offer benefits such as higher usage caps and faster response times, which could be a deciding factor for heavy users or businesses needing reliable, high-volume interactions.
Here are some more examples to illustrate the differences between GPT-4 and GPT-4o:
Simple Math
Prompt: "Calculate the sum of 8 and 5."
GPT-4.0 Response: "The sum of 8 and 5 is 13."
GPT-4o Response: "To find the sum of 8 and 5, you simply add the two numbers together: 8 + 5 = 13. Therefore, the sum is 13."
Conclusion: Both responses are correct, but GPT-4o provides a more detailed explanation, which can be helpful for users who need a bit more context.
Very Basic Coding Problem
Prompt: "Write a Python function that takes a number and returns its double."
GPT-4 Response:
```python
def double(number):
return number * 2
```
GPT-4o Response:
```python
def double(number):
"""
This function takes a number as input and returns its double.
Example:
>>> double(5)
10
"""
return number * 2
```
Analysis:
GPT-4 Response:
- Provides a simple and correct solution.
- Directly returns the double of the given number.
GPT-4o Response:
- Includes the same simple and correct solution.
- Additionally provides a docstring explaining what the function does and an example usage.
- The docstring makes the function clearer, especially for those who might not immediately understand the code.
This example highlights that while both versions provide correct and functional code, GPT-4o enhances it with additional documentation to aid understanding.
Simple Ethics
Prompt: "Is it okay to tell a white lie?"
GPT-4.0 Response: "Telling a white lie can sometimes be justified if it is meant to avoid hurting someone's feelings."
GPT-4o Response: "Whether it is okay to tell a white lie depends on the context. A white lie is generally considered a minor lie told to avoid hurting someone's feelings or to avoid minor inconvenience. For example, saying you like a gift when you don't might be considered a harmless white lie. However, it's important to consider the potential consequences and to use honesty as much as possible."
Conclusion: GPT-4o provides a more nuanced answer, explaining the concept of a white lie and its potential implications.
By using these simpler examples, it's easier to see the distinctions between the two versions in terms of detail and clarity.
Looking Ahead to GPT-5
Despite the excitement around GPT-4o, the AI community is already looking forward to GPT-5, expected later this summer of 2024. Enterprise customers received demos of the new model this spring, and OpenAI has teased forthcoming capabilities such as autonomous AI agents.
Final Conclusion: Comparing ChatGPT 3.5, GPT-4, and GPT-4o
As we delve into the evolution of OpenAI's language models, it's clear that each iteration brings significant advancements in terms of capabilities, performance, and user experience. Here's an in-depth comparison and conclusion of ChatGPT 3.5, GPT-4, and GPT-4o:
ChatGPT 3.5
Strengths
1. Foundation of Capabilities: ChatGPT 3.5, based on the GPT-3.5 engine, set a solid foundation with its ability to handle a wide range of queries and generate coherent, relevant responses.
2. Parameter Size: With 175 billion parameters, it was a significant leap over previous models, offering improved language understanding and generation.
3. Wide Accessibility: Provided a robust tool for users across various applications, from casual conversation to more complex tasks like coding and creative writing.
Limitations
1. Contextual Limitations: ChatGPT 3.5 struggled with maintaining context over longer conversations, often losing track of previous interactions after a certain point.
2. Accuracy and Hallucinations: It had a tendency to generate incorrect information confidently, known as "hallucinations," and could be less reliable in providing accurate data.
3. Sensitivity to Prompts: The model's responses could be heavily influenced by slight changes in prompts, sometimes leading to inconsistencies.
GPT-4
Improvements Over 3.5
1. Increased Parameters: GPT-4 significantly increased the parameter count, reportedly to over a trillion, allowing for more nuanced and detailed responses.
2. Enhanced Contextual Understanding: It improved the ability to maintain context over longer interactions, supporting up to 25,000 words in its context window compared to 3,000 words in GPT-3.5.
3. Better Handling of Subtleties: GPT-4 demonstrated a better grasp of complex nuances like sarcasm, humor, and detailed instructions, making it more effective in generating creative content and engaging in sophisticated conversations.
New Features
1. Multimodal Capabilities: GPT-4 introduced the ability to process not just text but also images, expanding its utility in various applications.
2. Improved Precision: Reduced the frequency of hallucinations and provided more accurate and reliable information, especially in technical and scientific queries.
GPT-4o
Key Advancements Over GPT-4
1. Speed and Efficiency: GPT-4o is optimized for faster response times and greater efficiency, making it more suitable for high-demand applications.
2. Cost-Effectiveness: It offers lower operational costs, which can be a significant advantage for businesses and developers looking to manage budgets while leveraging advanced AI capabilities.
3. Further Enhanced Contextual Memory: GPT-4o continues to build on the improvements in context handling, offering even more stability and reliability over extended interactions.
Multimodal Capabilities
1. Advanced Multimodal Functions: GPT-4o expands on the multimodal capabilities of GPT-4, potentially handling more complex tasks involving both text and images, though some functionalities might still be limited to specific use cases (e.g., API vs. web).
Business and Practical Considerations
1. Mature Technology: GPT-4 has been widely adopted and tested, providing a stable and reliable option for existing applications. Transitioning to GPT-4o might require infrastructure adjustments and come with initial costs.
2. Specialized Features: GPT-4o's enhanced features make it particularly appealing for new deployments and advanced applications, though its full potential is realized when multimodal capabilities are fully integrated into APIs.
Overall Conclusion
Context Handling and Detailed Responses
- GPT-4 and GPT-4o: Both models offer superior contextual understanding and detailed responses compared to GPT-3.5, with GPT-4o providing even more refined and comprehensive explanations.
- GPT-3.5: While still robust, it falls short in maintaining long-term context and handling complex queries with the same depth.
Coding and Technical Problem-Solving
- GPT-4o: Excels in generating detailed and functional code, suitable for complex applications with comprehensive features.
- GPT-4: Also performs well in technical tasks but might require more user input and adjustments.
- GPT-3.5: Capable but less reliable for intricate coding problems, often needing more guidance and producing less detailed solutions.
Philosophical and Ethical Discussions
- GPT-4o: Provides succinct yet nuanced answers, balancing depth with clarity.
- GPT-4: Offers thorough and well-rounded discussions, suitable for in-depth analysis.
- GPT-3.5: Generates coherent arguments but lacks the same level of nuance and sophistication.
User Experience and Practical Use
- GPT-4o: Combines the best of speed, efficiency, and advanced capabilities, making it the optimal choice for cutting-edge applications.
- GPT-4: Remains a strong, reliable option with mature technology and widespread adoption.
- GPT-3.5: Serves as a foundational tool but is surpassed by its successors in almost all aspects.
In summary, GPT-4o represents the pinnacle of OpenAI's advancements in AI technology, offering unmatched performance, efficiency, and versatility. GPT-4 remains a robust and widely trusted model, while GPT-3.5, although foundational, is outclassed by the newer iterations. Businesses and developers should consider their specific needs, existing infrastructure, and budget when choosing between these models, with GPT-4o being the preferred choice for those seeking the latest and most advanced capabilities.