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GPT 5 vs GPT 4o Comparison - Ultimate OpenAI Models Coding Test

#AI Tools
2025-12-02 20:558 min read

Content Introduction
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This video introduces the launch of GPT-5 by OpenAI, comparing its capabilities with the previous model, GPT-4. The presenter discusses various coding prompts and math problems, showcasing how both models respond to these challenges. Throughout the comparison, the advancements in GPT-5's performance are highlighted, including improvements in generating complex HTML codes and solving intricate math problems. The differences in output, response time, and memory efficiency between the two models are evaluated, with GPT-5 consistently outperforming GPT-4 in various scenarios. The audience is encouraged to follow the presenter for more insights into programming and AI tools.

Key Information

  • GPT-5 has been officially launched by OpenAI, and the video compares it with the existing GPT-4 model.
  • The presenter has not received the update to use GPT-5 in chat and is still using GPT-4 responses.
  • Multiple models of GPT-5 are available, including GP5 nano and GP5 mini.
  • The video showcases coding prompts and math problems to compare the performance of GPT-4 and GPT-5.
  • The first test involves a simple HTML code for a bouncing ball inside a spinning rectangle, showing that GPT-4 performs decently but GPT-5 handles complex visual effects better.
  • In math problem-solving, GPT-5 outperforms GPT-4, correctly addressing complex queries.
  • The video discusses differences in model performance, including coding capabilities and execution efficiency, demonstrating how GPT-5 excels overall.
  • GPT-5 shows significant improvements in handling complex prompts and creating detailed outputs compared to previous models.

Timeline Analysis

Content Keywords

GPT 5

GPT 5 has been officially launched by OpenAI, and this video compares it with the existing chat model, GPT 4.

GPT 4 vs GPT 5

The comparison includes usage of the API playground, assessing the performance and outputs of both models across various coding prompts and math problems.

HTML coding example

An HTML code example showcases a ball bouncing inside a spinning rectangle, demonstrating the models' abilities to handle physics aspects like friction and gravity.

GPT 5 outputs

GPT 5 produces visually improved outputs and correct responses in various coding tasks compared to GPT 4.

Math problem solving

Both models are tested on math problems, with GPT 5 showing superior performance by providing accurate solutions whereas GPT 4 gives incorrect answers.

Performance metrics

The performance metrics of GPT 5 include a high success rate in test cases, outperforming GPT 4 particularly in runtime and memory usage.

Programming use cases

The video discusses various programming use cases where GPT 5 excels, including creating complex web apps from scratch, demonstrating its versatility and efficacy.

General conclusion

The conclusion emphasizes the enhanced capabilities of GPT 5 over GPT 4, particularly in coding and math problem-solving contexts, encouraging viewers to subscribe for further programming content.

Related questions&answers

What key features distinguish GPT 5 from GPT 4?

GPT 5 has improved response accuracy, better handling of complex prompts, and more advanced features that make it closer to AGI.

How does GPT 5 perform in coding tasks compared to GPT 4?

GPT 5 has demonstrated a higher output of accurate code and can handle more complex programming tasks effectively.

What are the benefits of using the open AI API playground with GPT 5?

The open AI API playground allows users to easily switch between models and experiment with various functionalities of GPT 5.

Is GPT 5 capable of solving math problems effectively?

Yes, GPT 5 can solve math problems accurately and has shown a strong capability in handling difficult mathematical challenges.

What types of prompts can be used to test GPT 5's versatility?

Users can test GPT 5 with coding challenges, mathematical problems, and creative prompts like generating HTML for visual effects.

How does GPT 5 compare in performance when dealing with complex or abstract requests?

GPT 5 outperforms GPT 4 with more precise outputs and an understanding of nuanced requests, making it feel more intuitive.

Are there any areas where GPT 5 still struggles compared to previous models?

While GPT 5 has made significant improvements, it still faces challenges with certain types of creative tasks and very specific domain knowledge.

What is the significance of having multiple models like GPT 5 nano and mini?

Different model sizes allow users to choose the best fit for their specific needs, balancing performance and resource consumption.

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