GPT-4.5 vs GPT-4o: Is GPT-4.5 Really Better?

OpenAI has been at the top of the generative AI game for the last 3 years, releasing one ground breaking model after the other. Yesterday, they released GPT-4.5, a model with a higher EQ and creative sense for everyday tasks. The model competes with OpenAI’s flagship and by far the most used model – GPT-4o – which is great at text generation, logical reasoning, and even coding. While not launched as a direct replacement for this model, GPT-4.5 is hyped to be a bigger and more advanced model, owing to its higher pricing. In this GPT-4.5 vs GPT-4o comparison, we will witness the performance of both the model across various tasks, and find out which one is worth our buck!

What is GPT-4.5?

GPT-4.5 is OpenAI’s latest and most advanced text-based AI model, designed to improve accuracy, emotional intelligence, and creativity. Unlike GPT-4o, which is optimized for multimodal tasks (text, image, audio), GPT-4.5 focuses on text processing, knowledge accuracy, and agentic capabilities. It is faster, more reliable, and better at understanding human intent, making it ideal for writing, coding, automation, and professional applications.

Some of the key features of GPT-4.5 are:

1. Higher Knowledge Accuracy: The model outperforms GPT-4o in factual correctness and reliability.
2. Stronger Emotional Intelligence (EQ): This LLM is better at understanding human intent, emotions, and subtle cues.
3. Superior Writing & Creativity: The model excels in long-form writing, storytelling, and nuanced content creation.
4. Agentic AI Capabilities: GPT-4.5 model is more effective in multi-step automation and coding workflows.
5. Reduced Hallucination Rate: The model is factually reliable with fewer errors compared to GPT-4o.

Learn More: Everything You Need to Know About OpenAI’s GPT-4.5

What is GPT-4o?

GPT-4o (“Omni”) is OpenAI’s first widely used multimodal model, capable of processing text, images, and audio in real-time. It is designed to be faster, cheaper, and more efficient than previous models while maintaining high-quality responses. Unlike GPT-4.5, which is optimized for factual accuracy and emotional intelligence, GPT-4o focuses on multimodal capabilities and real-time interactions.

Some of the key features of GPT-4o are:

1. Multimodal Capabilities : This LLM can quickly process text, images, and audio in real-time.
2. Real-Time Interactions : GPT-4o is known for its faster response times, making it ideal for live chat and voice AI.
3. Balanced Reasoning & Creativity: The model uses a mix of step-by-step reasoning and direct answers.
4. Optimized for Conversational AI: The LLM is designed for engaging, human-like dialogue across various inputs, be it text, image or audio.
5. Better for API & Developers: The model supports multimodal applications, function calling, and real-time automation.

Learn More: What Can You Do With GPT-4o? | Demo

How to Access GPT-4.5 & GPT-4o

Both the models are available in ChatGPT. Hence to access the models,

1. Head to www.chatgpt.com
2. Log in to your account or sign up for one.
3. From the top, on the left side corner, in the model selection dropdown, select the model that you wish to work with.

While GPT-4o is also available to use in Free TIER of ChatGPT with limited usage; its largely available in the ChatGPT Plus Plan which comes for $20 per month.

GPT-4.5 is currently just available to the Pro users and would be available to the Plus users and teams from next week. The Pro plan comes for $200 per month.

To access the API, follow the following steps:

1. Sign Up or Log In to OpenAI’s website.
2. Once logged in, go to the API Keys section in your account settings.
3. Click on “Create API Key” and copy the generated key.
4. Store it securely, as OpenAI will not show it again after creation.
5. Some usage tiers require adding billing details. Ensure your account is set up for API access.
6. Implement the API key in your code to authenticate requests to OpenAI’s GPT-4.5 and GPT-4o.

Also Read: I Tried GPT-4.5 API at $150/1M Tokens – Here’s Why it’s Overpriced

GPT-4.5 vs GPT-4o: Benchmark Comparison

Let’s begin our comparison by looking at the performance of both these models in standard benchmark tests.

As seen above, GPT-4.5 performs significantly better than GPT-4o in all the tests, displaying its supremacy in Math, Science, Coding and Reasoning. The new model outperforms GPT-4o in multilingual and multimodal tasks as well.

So is GPT-4.5 really better than GPT-4o? While that is what these benchmark results say, let’s find out for ourselves by testing them both on some real-life tasks.

GPT-4.5 vs GPT-4o: Performance Comparison

In this part of the comparison, we’ll test out a few different prompts on both the models and compare their performance. For this, we’ll be trying GPT-4.5 and GPT-4o for the following tasks and comparing them based on the quality of their responses.

1. Drafting an Email
2. Summarizing a Report
3. Developing a Marketing Campaign
4. Solving a Puzzle
5. Analyzing an Image

Task 1: Drafting an Email

Prompt: “Draft an email to an employee who has been facing personal or professional challenges. Express understanding, offer support, and motivate them to keep going without sounding patronizing.”

Response by GPT-4.5

Response by GPT-4o

Comparative Analysis

Both emails are empathetic and supportive, but GPT-4.5’s version prioritizes well-being and reassurance over action-driven motivation, demonstrating higher EQ. GPT-4o’s email, while being equally supportive, leans toward motivation and resilience, which may feel slightly directive rather than purely comforting. GPT-4.5’s email is also more concise and emotionally attuned, while GPT-4o’s balances motivation with practical support like workload adjustments. On the whole, I would prefer GPT-4.5’s response as it encompasses the essence of the email within fewer words.

Score: GPT-4.5: 1 | GPT-4o: 0

Task 2: Summarizing a Report

Prompt: “Give me a 100-word summary of this report
Report.pdf”

Response by GPT-4.5

Response by GPT-4o

Comparative Analysis

Both models have given concise summaries, within the word count, highlighting the advantages and risks in accurate percentages. GPT-4.5 gives a more peripheral summary following the structure of the report, while GPT-4o provides more details into the numbers with clarity. Additionally, GPT-4o mentions the name of the report and sets a context by stating what the report is about. It also highlights the important parts, making it easy to read and understand, even at first glance. This makes GPT-4o’s response better.

Score: GPT-4.5: 1 | GPT-4o: 1

Task 3: Developing a Marketing Campaign

Prompt: “Craft a launch campaign for a new AI-powered productivity app. Focus on how it helps users manage their time efficiently and stand out in a crowded market.”

Response by GPT-4.5

You can find the full response here.

Response by GPT-4o

You can find the full response here.

Comparative Analysis

GPT-4.5 gave more of a marketing overview with key selling points and campaign channels, rather than a full-fledged campaign. While it mentioned creative taglines and suggested promotional offers, the action points were not very clear.

Meanwhile, GPT-4o gave a more structured and actionable campaign splitting it into various phases such as pre-launch, launch, and post-launch. It even planned out a week-wise marketing strategy, giving step-by-step instructions on how to go about it. Hence, for this marketing tasks, I feel GPT-4o is a better choice.

Score: GPT-4.5: 1 | GPT-4o: 2

Task 4: Solving a Puzzle

Prompt: “You are in a room with three light switches outside and three light bulbs inside. You can only enter the room once. How do you determine which switch controls which bulb?”

Response by GPT-4.5

Response by GPT-4o

Comparative Analysis

Both the models were able to come up with the right solution to this tricky puzzle. While GPT-4.5 explained the steps in fewer points, GPT-4o’s instructions were more structured and easier to follow. GPT-4o also mentions that the right answer can be determined using ‘heat as in indicator’ – which is some extra information. For a simpler and better-explained answer, my vote goes to 4o for this task.

Score: GPT-4.5: 1 | GPT-4o: 3

Task 5: Analyzing an Image

Prompt: “What is happening in this image? Explain the underlying issue for which this treatment is suggested. Also mention its possible causes.”

Response by GPT-4.5

Response by GPT-4o

Comparative Analysis

Both the models correctly identified the process shown in the image as hemodialysis. While GPT-4.5 explained the process as prompted, GPT-4o focused on explaining the image, listing out the different apparatus and what they do. Coming to the causes of the condition, GPT-4o gave a comprehensive and detailed list, mentioning the names of diseases. Whereas, GPT-4.5’s response felt more concise, picking out only what the model felt relevant or fitting. With a more detailed response, GPT-4o wins this round as well.

Score: GPT-4.5: 1 | GPT-4o: 4

Final Score: GPT-4.5: 1 | GPT-4o: 4

Performance Comparison Summary

GPT-4.5 vs GPT-4o: API Comparison

In the last section, we have seen the performance of GPT-4.5 vs GPT-4o for various tasks on their web interface. Now let’s discuss their APIs. GPT-4o API has been in use for the last two years, proving to be cost efficient while providing good performance.

With GPT-4.5, the input and output token cost are respectively 30 and 15 times more expensive compared to GPT 4o!

How much of an impact does this mean on our pockets? To figure that out, we’ll first prompt GPT-4o API to help me with a task. Based on the tokens consumed, we will estimate the price it will incur to use both the models, assuming they both give the same result (or similar performance).

Prompt: “A makeup company is losing its customers to its competitors due to lack of product variety. They do not have the resources yet to scale up and add more products, plan a strategy for them using which they can leverage their existing products to retain their customers.”

Input Code:

from openai import OpenAI
import time
import tiktoken
from IPython.display import display, Markdown
with open("path_to_api_key") as file:
api_key = file.read().strip()

task1_start_time = time.time()

client = OpenAI(api_key=api_key)

messages = [
{
"role": "system",
"content": """You are an expert an useful assistant"""
},
{
"role": "user",
"content": """A makeup company is losing its customers to its competitors due to lack of product variety.
They do not have the resources yet to scale up and add more products, plan a strategy for them using which they can leverage their existing products to retain their customers.
"""
}
]

# Use a compatible encoding (cl100k_base is the best option for new OpenAI models)
encoding = tiktoken.get_encoding("cl100k_base")

# Calculate token counts
input_tokens = sum(len(encoding.encode(msg["content"])) for msg in messages)

completion = client.chat.completions.create(
model="gpt-4o",
messages=messages
)

output_tokens = len(encoding.encode(completion.choices[0].message.content))

task1_end_time = time.time()


input_cost_per_1m = 2.5 # Example: $2.5 per 1M input tokens
output_cost_per_1m = 10 # Example: $10 per 1M output tokens

# Calculate cost
input_cost = (input_tokens / 1000000) * input_cost_per_1m
output_cost = (output_tokens / 1000000) * output_cost_per_1m
total_cost = input_cost + output_cost


# Print results
print(completion.choices[0].message)
print("----------------=Total Time Taken for task 1:----------------- ", task1_end_time - task1_start_time)
print(f"Input Tokens: {input_tokens}, Output Tokens: {output_tokens}")
print(f"Estimated Cost: ${total_cost:.6f}")

# Display result
from IPython.display import Markdown
display(Markdown(completion.choices[0].message.content)) 

Output:

API Price Analysis

This means, GPT-4.5 is approximately 15.4 times more expensive than GPT-4o for the same prompt! But is it worth paying the price?

Also Read: I Tried GPT-4.5 API at $150/1M Tokens – Here’s Why it’s Overpriced

Is GPT-4.5 Worth the Price?

Both GPT-4.5 and GPT-4o are for everyday tasks like content creation – which for most of us means – writing or proofreading our emails, or creating some kind of social media post. We may also use these models for summarizing long reports or pdfs or making quick flowcharts or understanding some new concepts.

For such tasks, that although make our lives simpler, it often doesn’t justify to pay 15 times more than what we are currently paying! So the conundrum rises: when to use GPT-4.5 and when to use GPT-4.0?

Thus, use GPT-4o for everyday tasks where speed and cost matter, and GPT-4.5 for high-accuracy, complex, or mission-critical tasks.

Even OpenAI acknowledges that GPT-4.5 is expensive and not a replacement for GPT 4o. This official email from OpenAI also suggests that they may disable it in API to prioritise other developments.

Conclusion

This GPT-4.5 vs GPT-4o comparison highlighted the strengths and trade-offs of both the models. While GPT-4.5 excels in knowledge accuracy and emotional intelligence, GPT-4o stands out for cost-efficiency, and multimodal capabilities. Hence GPT-4.5 seems to be a better choice for tasks where precision and reasoning are critical – such as in legal, financial, or high-stakes research. On the other hand, GPT-4o is best suited for tasks enhancing productivity and cost-efficient AI applications.

That being said, the most significant differentiating factor is pricing. GPT-4.5 is over 15 times more expensive than GPT-4o for similar tasks, which makes it less viable for casual users and businesses focused on cost-effective AI integration.

Ultimately, the choice between the two depends on your needs, budget, and the complexity of your AI-powered workflows. If affordability and versatility matter more, GPT-4o is the way to go. If you need premium accuracy and deep intelligence, GPT-4.5 probably justifies its price for highly-specialized use cases.

Frequently Asked Questions

K.C. Sabreena Basheer

Sabreena is a GenAI enthusiast and tech editor who's passionate about documenting the latest advancements that shape the world. She's currently exploring the world of AI and Data Science as the Manager of Content & Growth at Analytics Vidhya.