The Ultimate Comparison: ChatGPT o1, GPT-4o, and Claude 3.5 Sonnet

In the rapidly evolving world of artificial intelligence, new models are continuously emerging, each claiming to outperform their predecessors. In this article, we will explore the capabilities of three prominent AI models: ChatGPT o1, GPT-4o, and Claude 3.5 Sonnet. We will review their performance across various prompts, including logic puzzles, math problems, and coding challenges, to determine which model stands out in different scenarios.

Understanding the Models

Before diving into the comparisons, it’s essential to understand what each model brings to the table.

• ChatGPT o1: This is the latest model from OpenAI, showcasing advancements in natural language understanding and generation.
• GPT-4o: The previous generation from OpenAI, known for its robust capabilities but facing challenges with certain tasks.
• Claude 3.5 Sonnet: Developed by Anthropic, this model emphasizes safety and ethical AI, with performance that rivals the best in the industry.

Testing Methodology

To ensure a comprehensive assessment, I designed a series of ten prompts that would test the models in various scenarios. This includes straightforward questions, complex reasoning tasks, and coding challenges. The goal was to see not just which model could provide the correct answer, but also how well they articulated their reasoning.

Prompt 1: Counting Letters

The first test was a simple one: “How many R’s are in the word ‘strawberry’?”

All models correctly identified that there are three R’s in “strawberry.” However, the depth of their responses varied significantly.

• ChatGPT o1: “There are three R’s in strawberry.”
• GPT-4o: “There are three R’s in the word strawberry.”
• Claude 3.5 Sonnet: “There are three R’s in the word ‘strawberry’.” However, the response lacked the reasoning seen in custom prompts.

Prompt 2: The Chicken or the Egg?

Next, I posed the age-old question: “Which came first, the chicken or the egg?”

All models provided the scientifically accurate response that the egg came first, but the explanations varied.

• ChatGPT o1: Explained that the egg came first due to evolutionary processes.
• GPT-4o: Gave a similar response, emphasizing the role of mutations.
• Claude 3.5 Sonnet: Also stated that the egg came first, noting it was laid by a close ancestor of the chicken.

Prompt 3: Comparing Numbers

The next prompt was a simple comparative question: “Which number is bigger, 9.11 or 9.9?”

All models managed to answer correctly, identifying that 9.9 is greater than 9.11. However, the time taken to respond varied.

• ChatGPT o1: Quick response, identifying 9.9 as the larger number.
• GPT-4o: Gave the correct answer slightly slower than o1.
• Claude 3.5 Sonnet: Correctly identified the larger number but took longer.

Prompt 4: The Marble in the Glass

This prompt involved a bit of logical reasoning: “A marble is put in a glass cup. The glass is turned upside down and put on a table. Then the glass is picked up and put in a microwave. Where’s the marble?”

The correct answer is that the marble is left behind on the table.

• ChatGPT o1: Identified that the marble was left behind on the table.
• GPT-4o: Incorrectly stated that the marble was in the microwave.
• Claude 3.5 Sonnet: Correctly identified that the marble was on the table.

Prompt 5: Counting Words

The next challenge was to ask the models, “How many words are in your response to this prompt?”

This task often proves tricky for AI models.

• ChatGPT o1: Counted correctly, but there was some confusion regarding punctuation.
• GPT-4o: Struggled with the counting and provided an inaccurate number.
• Claude 3.5 Sonnet: Also struggled with counting, providing an answer that did not align with the actual word count.

Prompt 6: Hallucination Test

In this test, I asked the models to describe certain mango cultivars.

ChatGPT o1 accurately stated it did not have information about one cultivar, while GPT-4o fabricated details about it.

• ChatGPT o1: “I don’t have information about this variety.”
• GPT-4o: Created a fictional description.
• Claude 3.5 Sonnet: Acknowledged uncertainty but still fabricated some details.

Prompt 7: Logic Puzzle

The next prompt was a logic puzzle: “There are three killers in the room. Someone enters the room and kills one of them. How many killers are left in the room?”

All models correctly concluded that there were three killers left, as the new arrival counts as a killer too.

• ChatGPT o1: Correctly stated there are three killers.
• GPT-4o: Also arrived at the correct conclusion.
• Claude 3.5 Sonnet: Agreed with the others, stating there are three killers.

Prompt 8: Coding Challenge

For the coding challenge, I asked the models to write a simple game of chess in Python.

The responses varied greatly in terms of functionality and usability.

• ChatGPT o1: Provided a comprehensive code with instructions for required assets.
• GPT-4o: Delivered a basic code that lacked critical features.
• Claude 3.5 Sonnet: Provided code but crashed when executed.

Overall Performance

In summary, ChatGPT o1 emerged as the clear winner in this testing session, outperforming both GPT-4o and Claude 3.5 Sonnet in several key areas. It demonstrated superior reasoning abilities, better accuracy in counting tasks, and provided more reliable coding outputs.

GPT-4o, while still a strong contender, showed weaknesses in certain logical tasks and struggled with hallucination issues. Claude 3.5 Sonnet performed admirably in some areas but fell short in coding challenges and faced challenges with word counting.

Conclusion

The advancements in AI language models are evident, but the competition remains fierce. As users, it’s essential to choose the right model based on specific needs and tasks. Whether you require detailed reasoning, coding capabilities, or reliable factual responses, understanding the strengths and weaknesses of each model will help you make informed decisions.