Updated on August 21, 2025
Since its debut on November 30, 2022, OpenAI’s ChatGPT has rapidly evolved, setting new standards for AI-powered assistance. From GPT-3.5 to GPT-4 (and its variants like GPT-4o), and now the release of GPT-5, each step forward has brought stronger reasoning, richer conversations, and broader integrations.
If you’re trying to decide which model best suits your needs—or simply want to understand how GPT-5 changes the game—this guide breaks it all down.
In this article, we will cover the key difference between the GPT-5, GPT-4 and GPT-3.5 models and also provide a comparison of OpenAI’s pricing for all models, including the newly launched GPT-5 model. Also, if you are looking for a comprehensive comparison between GPT 4 Turbo, Gemini Claude 3 Opus, and Google Gemini 1.5 Pro, check it out here. Alternatively, if you wish to read about OpenAI o1, click here.
However, before jumping to the differences, let’s first understand what ChatGPT is and how it works –
Understanding ChatGPT
ChatGPT, developed by OpenAI, is an application designed to interact with GPT (Generative Pre-trained Transformer), an advanced language model driving generative artificial intelligence. These large language models, commonly referred to as LLMs, typically consist of several key components that work together to enable language understanding and generation tasks. Essentially, they serve as powerful engines for computers, capable of writing codes, generating images, writing stories, translating languages, providing natural responses to questions, and even build an app for you.
In practical terms, ChatGPT functions as a versatile tool for engaging with GPT, the powerhouse behind its capabilities. It operates as a user-friendly interface, allowing individuals to interact with the complex process of language understanding and generation facilitated by LLMs. Through ChatGPT, users can easily input queries, prompts, or requests, generating responses across a wide spectrum of tasks, from composing stories and songs to coding complex programs and crafting marketing messages, among others.
ChatGPT 3.5 vs. GPT-4 vs. GPT-5
The biggest distinction between GPT-3.5, GPT-4, and GPT-5 is in their scale, reasoning ability, and real-world performance. GPT-3.5, trained on roughly 175 billion parameters, was lightweight and fast but limited in handling complex queries. GPT-4, widely believed to have close to 1 trillion parameters, made a huge jump in accuracy, creativity, and coding reliability. OpenAI has not officially revealed the parameter size of GPT-5, but the upgrade is not just about scale – it is about built-in thinking. GPT-5 can automatically switch between quick responses and deep, step-by-step reasoning, bringing expert-level intelligence to everyday users. With a massive 256,000-token context window, it can process entire research papers, codebases, or long business documents, leading to higher accuracy in mathematics, coding, visual recognition, and decision-making tasks. This makes GPT-5 the most powerful and practical version of ChatGPT so far.
Let’s look at some of the other key differences –
GPT-5 Has Built-In Thinking
GPT-5 has built-in thinking and a real-time router which decides which model to use based on conversation type, complexity, tool needs, and your explicit intent (for example, if you say “think hard about this” in the prompt).The router is continuously trained on real signals, including when users switch models, preference rates for responses, and measured correctness, improving over time. Once usage limits are reached, a mini version of each model handles the remaining queries. In the near future, these capabilities will be integrated into a single model.
GPT-5 not only outperforms previous models on benchmarks and answers questions more quickly, but most importantly, it is more useful for real-world queries. Significant progress has been made in reducing hallucinations, improving instruction following, and minimizing unnecessary agreement, while raising GPT-5’s performance in three of ChatGPT’s most common uses: writing, coding, and health.
ChatGPT 4 is Multimodal
A significant drawback of ChatGPT 3.5 was its “unimodal” nature, meaning the chatbot solely comprehends and interprets text input. ChatGPT-4 represents a significant advancement as it is powered by the GPT 4 engine, which is multimodal.
ChatGPT 4 understands and process even images, and it accepts both text and image prompts. In a developer livestream organized by OpenAI, Greg Brockman, one of the co-founders, showed how powerful ChatGPT 4’s image processing capabilities actually are.
Greg held up a photo for a joke website for which he needs code, and then sent it to ChatGPT 4.
The chatbot then processed this image, and generated an entire Javascript code for the website within a few seconds.
This is how the code and the final website looks like:
Not bad for an LLM no? The applications of this technology are revolutionary, and entire websites can now be coded in a matter of hours, if not minutes.
Programmers beware – ChatGPT 4 just upped the game. Of course, the chatbot still cannot generate images, and is only capable of accepting image inputs at the moment.
GPT-5 has much more Processing Power compared to GPT-4 and GPT 3.5
When it comes to the sheer processing power or the ability to solve complex scientific and mathematical problems, GPT-5 is way ahead of GPT-4 and GPT-3.5.
GPT-5 can build apps, write code, respond with greater context, and even take actions on our behalf. GPT-4, on the other hand, is stronger at solving advanced math problems like calculus, algebra, and geometry. GPT-3.5 is more limited, often giving guidance on how to approach a problem rather than delivering the full solution.
To put all these models to the test, we asked GPT 3.5, GPT 4, and GPT-5 to calculate the trajectory of a projectile under the influence of gravity and incorporating air resistance.
This is the response that GPT 3.5 generated.
ChatGPT 4 on the other hand went ahead and gave the actual Runge Kutta method for solving this problem.
GPT-5 goes one step ahead and solves the whole equation with visual responses to make it easier for anyone to understand.
ChatGPT4 can analyze complex scientific concepts and can simulate entire chemical reactions based on inputs. If you are a science enthusiast, then ChatGPT 4 can act as a very good personal assistant, giving you solutions to actual problems much faster than search engines.
ChatGPT 4 responses are much more “Nuanced”
One major drawback of ChatGPT 3.5 was that it was failing to understand the subtle nuances when it came to natural human language. ChatGPT 3.5 was not able to “get” jokes or sarcasm.
When it comes to creativity, ChatGPT 4 has leapfrogged far ahead of its predecessor. ChatGPT 4 can produce improved poems or essays with much better coherence and creativity.
A major reason behind this advanced capability is that ChatGPT4 has an improved context window. ChatGPT4 can now retain up to 25,000 words of chats for context from chats, while ChatGPT 3.5 has a mere 3000 words.
Check out this poem that we found on Reddit that ChatGPT 4 wrote, around traffic lights.
We gave the same prompt to ChatGPT 3.5, and the poem, although rhyming, was far less creative
ChatGPT4 even writes good short stories and essays, based on the prompts that you give it. This can also extend to novels, where ChatGPT4 can churn out novels with well thought out plot and character development, features that ChatGPT 3.5 had difficulty with.
ChatGPT 4 is more Accurate, less prone to “Hallucinations”
ChatGPT 3.5 was based on the GPT 3.5 engine, which received training on over 175 billion training parameters. ChatGPT 4 took this training one step further, and is purportedly trained on over a trillion parameters. What does this mean?
This means that ChatGPT4 will consider those trillion parameters before formulating a response. When ChatGPT 3.5 was initially released, there were instances where people were asking the chatbot ways to hack into banking websites and known vulnerabilities in other popular sites. This will not be possible in ChatGPT4.
Other topics that ChatGPT4 will stay clear of are:
1. Party politics – ChatGPT will not get into a debate arguing one political party is better than the next, and will stay objective in its responses.
2. Creating malware: Unlike ChatGPT 3.5, you cannot use ChatGPT 4 to create malware, and OpenAI has put in measures to check this.
3. War and physical violence: ChatGPT will not pass comments on, say, the Ukraine war.
These are just some of the areas where ChatGPT does not understand the user input, just like a regular chatbot. In such cases, large language models (LLMs) provide what are known as “ hallucinations.” This is because the model relies on primary learning data or knowledge patterns to generate responses.
According to a tweet by Sam Altman, founder of OpenAI, ChatGPT 4 “hallucinates significantly less.”
If you wish to see a video summary of everything we have discussed this far, check out this video:
Latest GPT-5 and GPT-4 Models
OpenAI is continually enhancing the capabilities of its GPT models. Below is a quick comparison of all lates GPT-5 and GPT-4 Models
| Parameter | GPT-5 | GPT-4 | GPT-4 Turbo | GPT-4o |
| Model Size | Largest | Large-scale transformer | Optimized large-scale model | Optimized for specific tasks |
| Token Size | 256,000 tokens | 8,000 tokens | 16,000 tokens | Variable, task-dependent |
| Training Data | Largest trainig data yet | Diverse internet sources | Enhanced diverse internet sources | Specialized datasets |
| Performance | Best accuracy with minimal hallucination | High accuracy and versatility | Improved speed and efficiency | Specialized task performance |
| Cost | Expensive | Standard pricing | More cost-effective | Variable, depending on task |
| Use Cases | Coding, building apps | General-purpose AI tasks | High-demand applications | Niche and specialized applications |
The Pricing
OpenAI offers varied pricing for its different models, typically based on units of either 1M or 1K tokens. Tokens represent individual units of language, with 1,000 tokens roughly equivalent to 750 words.
Here’s a table comparing the prices of ChatGPT 4, ChatGPT 3.5 Turbo, and, ChatGPT 4 Turbo – which was recently launched
OpenAI also provides Assistant APIs that makes it easy for developers to build AI assistants in their applications. The tokens used for the Assistant API are billed at the chosen language model’s per-token input/output rates. For all further details, please refer to the Pricing page of OpenAI
| Model | Input | Output |
| GPT-5 | $1.250 / 1M tokens | $10.000 / 1M tokens |
| GPT-5 mini | $0.250 / 1M tokens | $2.000 / 1M tokens |
| GPT-5 nano | $0.050 / 1M tokens | $0.400 / 1M tokens |
| GPT – 4o | $2.50/1M tokens | $10.00/1M tokens |
| GPT-4.1 | $3.00 / 1M tokens | $12.00 / 1M tokens |
| GPT-4o mini | $0.15 /1M tokens | $0.60 /1M tokens |
Final words
AI capabilities are evolving swiftly, exceeding expectations. GPT-5 has notably surpassed GPT-4 and GPT-3.5, and now, with the debut of GPT-5, boundaries are being pushed even further. While these advancements are expected to continue rapidly, it is important to approach this potential cautiously. Organizations, while striving to maximize the benefits of this technology, must also carefully weigh the ethical implications and potential risks linked to AI deployment. Prioritizing responsible and ethical AI practices is essential to ensure that innovation is balanced with concerns for privacy, security, and societal impact.
CEO & Co-Founder of Kommunicate, with 15+ years of experience in building exceptional AI and chat-based products. Believes the future is human + bot working together and complementing each other.
At Kommunicate, we envision a world-beating customer support solution to empower the new era of customer support. We would love to have you on board to have a first-hand experience of Kommunicate. You can signup here and start delighting your customers right away.
