GPT-4o explained: Everything you need to know (2024)

What is GPT-4o?

GPT-4o is the flagship model of the OpenAI LLM technology portfolio. The O stands for Omni and isn't just some kind of marketing hyperbole, but rather a reference to the model's multiple modalities for text, vision and audio.

The GPT-4o model marks a new evolution for the GPT-4 LLM that OpenAI first released in March 2023. This isn't the first update for GPT-4 either, as the model first got a boost in November 2023, with the debut of GPT-4 Turbo. The GPT acronym stands for Generative Pre-Trained Transformer. A transformer model is a foundational element of generative AI, providing a neural network architecture that is able to understand and generate new outputs.

GPT-4o goes beyond what GPT-4 Turbo provided in terms of both capabilities and performance. As was the case with its GPT-4 predecessors, GPT-4o can be used for text generation use cases, such as summarization and knowledge-based question and answer. The model is also capable of reasoning, solving complex math problems and coding.

The GPT-4o model introduces a new rapid audio input response that -- according to OpenAI -- is similar to a human, with an average response time of 320 milliseconds. The model can also respond with an AI-generated voice that sounds human.

Rather than having multiple separate models that understand audio, images -- which OpenAI refers to as vision -- and text, GPT-4o combines those modalities into a single model. As such, GPT-4o can understand any combination of text, image and audio input and respond with outputs in any of those forms.

The promise of GPT-4o and its high-speed audio multimodal responsiveness is that it allows the model to engage in more natural and intuitive interactions with users.

What can GPT-4o do?

At the time of its release, GPT-4o was the most capable of all OpenAI models in terms of both functionality and performance.

The many things that GPT-4o can do include the following:

• Real-time interactions. The GPT-4o model can engage in real-time verbal conversations without any real noticeable delays.
• Knowledge-based Q&A. As was the case with all prior GPT-4 models, GPT-4o has been trained with a knowledge base and is able to respond to questions.
• Text summarization and generation. As was the case with all prior GPT-4 models, GPT-4o can execute common text LLM tasks including text summarization and generation.
• Multimodal reasoning and generation. GPT-4o integrates text, voice and vision into a single model, allowing it to process and respond to a combination of data types. The model can understand audio, images and text at the same speed. It can also generate responses via audio, images and text.
• Language and audio processing. GPT-4o has advanced capabilities in handling more than 50 different languages.
• Sentiment analysis. The model understands user sentiment across different modalities of text, audio and video.
• Voice nuance. GPT-4o can generate speech with emotional nuances. This makes it effective for applications requiring sensitive and nuanced communication.
• Audio content analysis. The model can generate and understand spoken language, which can be applied in voice-activated systems, audio content analysis and interactive storytelling
• Real-time translation. The multimodal capabilities of GPT-4o can support real-time translation from one language to another.
• Image understanding and vision. The model can analyze images and videos, allowing users to upload visual content that GPT-4o will understand, be able to explain and provide analysis for.
• Data analysis. The vision and reasoning capabilities can enable users to analyze data that is contained in data charts. GPT-4o can also create data charts based on analysis or a prompt.
• File uploads. Beyond the knowledge cutoff, GPT-4o supports file uploads, letting users analyze specific data for analysis.
• Memory and contextual awareness. GPT-4o can remember previous interactions and maintain context over longer conversations.
• Large context window. With a context window supporting up to 128,000 tokens, GPT-4o can maintain coherence over longer conversations or documents, making it suitable for detailed analysis.
• Reduced hallucination and improved safety. The model is designed to minimize the generation of incorrect or misleading information. GPT-4o includes enhanced safety protocols to ensure outputs are appropriate and safe for users.

How to use GPT-4o

There are several ways users and organizations can use GPT-4o.

• ChatGPT Free. The GPT-4o model is set to be available to free users of OpenAI's ChatGPT chatbot. When available, GPT-4o will replace the current default for ChatGPT Free users. ChatGPT Free users will have restricted message access and will not get access to some advanced features including vision, file uploads and data analysis.
• ChatGPT Plus. Users of OpenAI's paid service for ChatGPT will get full access to GPT-4o, without the feature restrictions that are in place for free users.
• API access. Developers can access GPT-4o through OpenAI's API. This allows for integration into applications to make full use of GPT-4o's capabilities for tasks.
• Desktop applications. OpenAI has integrated GPT-4o into desktop applications, including a new app for Apple's macOS that was also launched on May 13.
• Custom GPTs. Organizations can create custom GPT versions of GPT-4o tailored to specific business needs or departments. The custom model can potentially be offered to users via OpenAI's GPT Store.
• Microsoft OpenAI Service. Users can explore GPT-4o's capabilities in a preview mode within the Microsoft Azure OpenAI Studio, specifically designed to handle multimodal inputs including text and vision. This initial release lets Azure OpenAI Service customers test GPT-4o's functionalities in a controlled environment, with plans to expand its capabilities in the future.

GPT-4 vs. GPT-4 Turbo vs. GPT-4o

Here's a quick look at the differences between GPT-4, GPT-4 Turbo and GPT-4o:

Sean Michael Kerner is an IT consultant, technology enthusiast and tinkerer. He has pulled Token Ring, configured NetWare and been known to compile his own Linux kernel. He consults with industry and media organizations on technology issues.