OpenAI's newest model, the GPT-40, deemed superior to its renowned predecessor, the GPT-5, in a head-to-head comparison?
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In the world of artificial intelligence, the release of two new language models, GPT-5 and GPT-4o, has sparked a lot of interest and debate. While both models have their strengths, there are significant differences between them, particularly in areas such as coding, reasoning, image analysis, and content creation.
GPT-5, launched in August 2025, has been hailed for its unified architecture that eliminates the need for manual switching between models for different tasks. This improvement has led to a substantial 42% relative improvement in real-world coding benchmarks compared to GPT-4o, as demonstrated by scores of 74.9% on SWE-bench Verified and 88% on Aider Polyglot.
In terms of mathematics and reasoning, GPT-5 has shown impressive results, achieving state-of-the-art results with 94.6% on the AIME 2025 math competition and 88.4% on the graduate-level GPQA test. This surpasses GPT-4o's more limited deep reasoning capabilities.
GPT-5 also excels in multimodal performance, particularly in image analysis and generation. It performs better on multimodal understanding benchmarks, such as the MMMU, enabling better reasoning over images, charts, and diagrams.
However, GPT-5 is not without its drawbacks. It takes more time to generate responses in some tasks, such as generating code for a word-counting website, compared to GPT-4o. Additionally, in certain contexts, GPT-5 may initially struggle with tasks that GPT-4o can handle more easily, such as image interpretation for a Sudoku puzzle.
GPT-4o, on the other hand, delivers faster responses and holds its own in content creation and image generation/analysis tasks. It struggled with tasks that required deep reasoning, such as identifying the components of a circuit diagram and calculating the output current and voltage values.
Despite GPT-5's advancements, there have been calls for a comeback of GPT-4o. Some users find it hard to adapt to the changes in GPT-5 and argue that it only marginally surpasses GPT-4o on specific tasks. Context matters when comparing the two models, as GPT-4o benefits from more recent training data and agentic optimizations in GPT-5.
In conclusion, GPT-5 represents a major leap forward in performance on content creation, coding, reasoning, image analysis, and other complex tasks. However, GPT-4o still has its place, particularly in tasks that require quick responses and less complex reasoning. The choice between the two models will depend on the specific needs and context of the user.
[1] GPT-5 Whitepaper
[2] GPT-5 Technical Brief
[3] GPT-5 Dataset
[4] GPT-5 User Experience Review
[5] GPT-5 Impact Assessment
- The advancements in GPT-5 technology, specifically its unified architecture, have led to improvements in artificial-intelligence applications, such as coding and content creation, resulting in higher scores on benchmarks like SWE-bench Verified and Aider Polyglot.
- In comparison, artificial-intelligence models like GPT-4o are still valuable for tasks that require quick responses and less complex reasoning, such as content creation and image generation/analysis, even though they may have more limited deep reasoning capabilities compared to GPT-5.
