Introduction
December has arrived, with the world seemingly slowing down and snowfall in some regions. However, OpenAI is just ramping up its activities. In a festive mood, Sam Altman and his team have initiated a 12 – day gift – giving spree, and the first offering is significant: OpenAI o1, their most capable model to date. For months, GPT – 4o has been the default large – language model (LLM) for various tasks, but now o1 has emerged to disrupt the status quo. In this article, we will pit OpenAI’s o1 against GPT – 4o in several tasks to determine which model comes out on top.
OpenAI o1 – What’s New?
OpenAI’s latest o1 model is an enhanced version of the o1 – preview model released in September 2024. It is engineered to handle more complex tasks with higher precision and speed. Compared to its predecessor, o1 – preview, o1 shows a remarkable ability to think more concisely for simpler problems, with its thinking time proportional to the difficulty of the query. OpenAI claims that o1 significantly outperforms o1 – Preview in mathematical reasoning and coding – related tasks. Additionally, o1 has multimodal capabilities, meaning it can work with text, images, and audio, unlike the o1 – preview which was limited to text.
How to access o1?
o1 is available in the ChatGPT Plus and ChatGPT Pro plans, but not in the free plan. The ChatGPT Pro plan allows unlimited chats with o1, while the Plus plan has a limit on the number of chats. To access o1, head to ChatGPT and log in to your Pro/Plus account. Then, at the top, on the left – hand side of the screen, under the model choice, you can select o1.
o1 vs. GPT – 4o: The Showdown
Despite the o1 – preview making waves in recent months, GPT – 4o has remained the top choice for both technical and non – technical ChatGPT users. Launched in May 2024, GPT – 4o is a refined multimodal model known for its precision, speed, and versatility. It processes text, images, and audio with human – like response times and state – of – the – art accuracy, excelling in complex reasoning and nuanced understanding with an impressive 88.7% score on MMLU benchmarks. Now, o1 is vying for the spotlight with its outstanding performance in mathematics, coding, and complex problem – solving. But does o1 truly outperform GPT – 4o? To find out, we have put both models to the test with five challenging tasks:
- Understanding the problem and designing a flow chart
- Image analysis with science
- Image analysis with mathematics
- Solve a Sudoku puzzle
- Image generation
The Challenges and Results
Challenge 1: Understand the Problem and Design a Flow Chart
Prompt: “I need a simple flow diagram and a detailed explanation of the tools and technologies required to implement a sentiment analysis system. The system should fetch stock – related news using a News API, analyze the sentiment (positive, negative, or neutral), and deliver a 140 – character summary and the sentiment to customers.”
Result: GPT – 4o provided a conceptual description of the flow diagram along with a vague image with spelling mistakes and a confusing flow. o1, on the other hand, gave a simple and clean flowchart with no spelling errors, detailed text descriptions for each part of the flowchart, additional information on tools, and a concise summary. Verdict: o1 won this task.
Challenge 2: Image Analysis with Science
Prompt: “Calculate the output of this circuit diagram.”
Result: GPT – 4o correctly identified the circuit diagram and some components but failed to read the graph values. o1 analyzed the image in a few seconds, correctly identified all components and values, described the circuit operation, and calculated the key parameters. Verdict: o1 is a master at Physics – related tasks.
Challenge 3: Image Analysis with Mathematics
Prompt: “What is the win probability for each team in this game?”
Result: GPT – 4o understood the game but not the format, and did not give the win probability. o1 understood the task well, analyzed the image, identified the game, format, and other details, and calculated the win probability for each team. Verdict: o1 did a great job.
Challenge 4: Solve a Sudoku Puzzle
Prompt: “Solve the following Sudoku and give the final solution as an image.”
Result: GPT – 4o generated an incorrect Matplotlib chart instantly. o1 took time to think, made several iterations, explained its placements, but still did not provide the correct solution. Verdict: Both models failed this task.
Challenge 5: Image Generation
Prompt: “Create an image of a dog running close to the seashore”
Result: GPT – 4o quickly generated the requested image. o1 could not generate images and only provided a detailed prompt for an AI image generator. Verdict: GPT – 4o won this challenge.
Conclusion
o1 clearly outperforms GPT – 4o in most tasks, thanks to its improved reasoning and logical thinking capabilities. It is better at understanding complex queries and providing more relevant, precise responses. However, it is not perfect. Like any model, it has limitations, such as generating incorrect responses and requiring multiple iterations. Nevertheless, o1 is a valuable tool for researchers, scientists, designers, and students, with its exceptional problem – solving skills, attention to detail, and advanced features holding great potential for enhancing productivity and innovation.
