Open AI O3 vs GPT-4: Top Differences That You Should Know in 2025

OpenAI has introduced O3 as part of its Project Strawberry initiative. An advanced AI model built to enhance reasoning capabilities, making it more effective in tasks like coding, math, and complex problem-solving.

For developers, business owners, or anyone working with AI, understanding how O3 differs from GPT-4 is important in choosing the right tool.

In 2025, AI is integrated into various applications, so choosing the right technology is important.

In this post we’ll compare O3 and GPT-4 and look at the key differences and how O3’s features can benefit your business

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OpenAI O3

In December 2024, OpenAI unveiled its latest AI model, o3, marking a significant advancement in artificial intelligence with a focus on enhanced reasoning capabilities. Designed to tackle complex tasks across various domains, o3 demonstrates superior performance in areas such as coding, mathematics, and science. Notably, it achieved a score of 87.7% on the GPQA Diamond benchmark, which includes expert-level science questions not publicly available online. Additionally, on the SWE-bench Verified coding tests, o3 scored 71.7%, surpassing the previous o1 model’s 48.9%.

To cater to diverse computational needs, OpenAI also introduced o3-mini, a distilled version of the o3 model optimized for coding tasks. Scheduled for release by the end of January 2025, o3-mini offers three compute levels—low, medium, and high—allowing users to balance performance and resource consumption according to their specific requirements. This flexibility makes advanced AI capabilities more accessible to a broader range of users and applications.

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OpenAI GPT 4

GPT-4, released on March 14, 2023, represents a significant leap in artificial intelligence as a multimodal system capable of processing text, image, and audio inputs. Designed for seamless interaction, it features a intialy to 32,000k to 128K token context window, allowing it to handle vast amounts of information in a single instance. With the earlier ability to generate up to 4,096 tokens per request, GPT-4 excels at managing complex tasks, from content generation to analyzing intricate datasets, while maintaining a high degree of accuracy and coherence.

Renowned for its advanced reasoning abilities, GPT-4 has achieved remarkable results on industry benchmarks, scoring 85.4% on the MMLU test, which evaluates general knowledge and reasoning across a wide range of disciplines, and 86.6% on the Human Eval coding benchmark, a measure of its coding proficiency. These accomplishments highlight its versatility and reliability, making it a powerful tool for applications in fields like software development, research, education, and creative problem-solving.

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What is the Difference Between OpenAI O3 and GPT-4?

OpenAI O3 is a tool for developers to integrate AI models, while GPT-4 is the language model used for text generation. These two have different functions but work together to enable AI solutions. So, what’s the difference between OpenAI O3 and GPT-4?

To compare their features more clearly, see the table below:

Feature	GPT-4	O3
Context Window	Up to 128K tokens	Up to 200K tokens
Output Capacity	Up to 4,096 tokens per request	Up to 100K tokens per request
Multimodal Capabilities	Yes (text, image, audio)	Primarily text-focused
Reasoning Capabilities	Advanced	Exceptional (math-focused)
Mathematical Performance	64.5% on MATH benchmarks	96.7% on AIME 2024
Coding Performance	86.6% on Human Eval coding	71.7% on SWE-bench coding
Safety Protocols	RLHF and fine-tuning	Deliberative alignment
Compute Efficiency	Moderate	High-compute adaptability
Primary Strength	Multimodal processing	Advanced reasoning
Release Date	Initial Release (March 2023)	December 2024

Context Window

• GPT-4: Offers a context window of up to 128K tokens, making it suitable for handling moderately long conversations or documents. This size enables it to process large inputs or maintain context over extended interactions.
  
• O3: Expands this significantly to 200K tokens, allowing for processing much larger datasets or maintaining context over even longer interactions, making it ideal for complex workflows and projects involving vast amounts of data.
  
  For businesses that want to combine such AI reasoning power with customer relationship management, solutions such as AI CRM software can provide a direct way to integrate advanced models like O3 into sales, support, and marketing pipelines.

Output Capacity

• GPT-4: Can generate up to 4,096 tokens per request, which is sufficient for most text generation tasks like articles, summaries, or creative writing.
  
• O3: Increases output capacity to 100K tokens per request, making it capable of producing comprehensive reports, large-scale content, or detailed analyses in one go.

Multimodal Capabilities

• GPT-4: Fully multimodal, capable of processing text, images, and audio as inputs. It is particularly versatile in tasks like image captioning, audio transcription, and multimodal content understanding.
  
• O3: Focuses primarily on text-based tasks, with less emphasis on multimodal capabilities, reflecting its specialized design for text-intensive reasoning and problem-solving tasks.

Reasoning Capabilities

• GPT-4: Offers advanced reasoning abilities, performing well on a variety of general benchmarks. It is adept at handling diverse use cases, such as logical reasoning and text comprehension.
  
• O3: Excels in exceptional reasoning, particularly in mathematical and logical problem-solving. It sets a higher standard for tasks requiring deep analytical thinking.

Mathematical Performance

• GPT-4: Achieves 64.5% on MATH benchmarks, demonstrating solid mathematical reasoning but leaving room for improvement in highly complex calculations.
  
• O3: Significantly surpasses GPT-4 with 96.7% accuracy on AIME 2024, highlighting its specialized focus on mathematical and computational reasoning tasks.

Coding Performance

• GPT-4: Scores 86.6% on the Human Eval benchmark, excelling in tasks like code generation and debugging for various programming languages.
  
• O3: Achieves 71.7% on the SWE-bench coding benchmark, showing proficiency in coding tasks but with a stronger emphasis on reasoning than pure programming skills.

Safety Protocols

• GPT-4: Implements Reinforcement Learning from Human Feedback (RLHF) and fine-tuning to improve safety and alignment with user needs.
  
• O3: Uses deliberative alignment, a more robust approach to ensure ethical, safe, and context-sensitive interactions, particularly for high-stakes or sensitive applications.

Compute Efficiency

• GPT-4: Has moderate compute efficiency, balancing performance with resource usage, making it suitable for general-purpose tasks.
  
• O3: Optimized for high-compute adaptability, allowing it to handle resource-intensive tasks while maintaining performance, particularly for complex tasks.

Primary Strength

• GPT-4: Specializes in multimodal processing, offering flexibility across text, image, and audio inputs, making it ideal for creative, diverse applications.
  
• O3: Focused on advanced reasoning, making it a go-to choice for tasks that demand deep analytical thinking, like research, technical writing, or mathematical problem-solving.

These differences show that GPT-4 vs O3 both are the best of there time and is optimized for tasks requiring extended context, advanced reasoning, and improved performance.

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Conclusion:

GPT-4 and OpenAI O3 are both advanced AI models, designed for different applications. GPT-4 is a multimodal system that processes text, images, and audio, making it a suitable tool for tasks such as content creation, customer support, and multimedia analysis. Its wide-ranging functionality enables it to address diverse use cases with strong performance across various benchmarks.

On the other hand, OpenAI O3, introduced in December 2024, is optimized for tasks requiring sophisticated reasoning and large-scale data processing. With its expanded context window and strong performance in mathematical and logical problem-solving, O3 is better suited for high-performance applications such as research, technical writing, and data-heavy analysis.

Understanding the distinct strengths of each model allows businesses to use GPT-4 for creative and interactive tasks, while utilizing O3 for more specialized, performance-focused solutions.