GPT-4 Omni (GPT-4o)
by Stephen M. Walker II, Co-Founder / CEO
Top tip
GPT-4o fine-tuning is now available, enabling GPT-4o customization for your specific use cases.
What is OpenAI GPT-4 Omni?
GPT-4 Omni (GPT-4o) is OpenAI's latest flagship model, launched on May 13, 2024. The "o" in GPT-4o stands for "omni," reflecting its advanced multimodal capabilities that allow it to process and generate text, audio, image, and video inputs and outputs. This model represents a significant leap forward in natural human-computer interaction, offering more seamless and intuitive user experiences across various applications.
Performance Benchmarks
GPT-4o exhibits remarkable performance across multiple domains, matching GPT-4 Turbo's capabilities in text processing, reasoning, and coding while simultaneously setting new benchmarks in multilingual understanding, audio processing, and visual perception. These advancements represent a significant leap forward in AI's ability to handle diverse modalities and complex tasks, pushing the boundaries of machine learning in both breadth and depth of understanding.
Long Context Utilization
GPT-4o outperforms GPT-4 Turbo in utilizing long context across various lengths and depths. The comparison results are summarized in the following table:
Model | Wins |
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GPT-4 Omni 0513 | 42 |
GPT-4 Turbo 1106 | 29 |
Tie | 62 |
GPT-4o's advantage is most evident at lower context lengths and higher depths. While both models perform identically at the 2000 context length, GPT-4o excels at the 7900 context length, consistently outperforming from 5% to 90% depth. Performance varies at intermediate and higher context lengths, with GPT-4o maintaining a slight edge. At the maximum tested context length of 37400, GPT-4o demonstrates markedly better performance, especially at higher depths.
The substantial number of ties suggests that both models often perform comparably. This nuanced performance profile highlights the importance of considering specific context lengths and depths when choosing between GPT-4o and GPT-4t for particular applications.
Needle in a Haystack Eval
To further assess GPT-4o's capabilities in handling long contexts, a "needle in a haystack" evaluation was conducted. This test involves inserting a small, crucial piece of information (the "needle") within a large amount of irrelevant text (the "haystack") and evaluating the model's ability to locate and utilize this information accurately.
GPT-4o exhibits strong long context accuracy across a wide range of lengths and depths, particularly excelling between 60,000 and 128,000 tokens. While it consistently achieves high scores in these ranges, performance fluctuates at extreme context lengths, such as 20,500 and 73,000 tokens. Despite occasional inconsistencies, the model generally maintains robust accuracy across multiple depths, showcasing its versatility in handling extended contexts.
Text Evaluation
GPT-4o outperformed leading AI models like GPT-4T, Claude3 Opus, and Gemini Pro 1.5 in recent benchmark evaluations, demonstrating its superior capabilities across various tasks.
GPT-4o demonstrated exceptional performance across various benchmarks. In the MMLU test for massive multitask language understanding, it achieved 88.7% accuracy. The model excelled in coding tasks with a 90.2% pass rate on HumanEval, and showed remarkable proficiency in multilingual grade school math problems, scoring 90.5% on MGSM. For more advanced mathematics, GPT-4o scored 76.6% on the MATH benchmark. It also performed well in discrete reasoning over paragraphs, with an 83.4% accuracy on DROP. However, the model showed room for improvement on complex, nuanced questions, scoring 53.6% on the GPoQA benchmark. These results position GPT-4o as a leading model in text evaluation performance across diverse domains.
Translation Evaluation
The recent performance evaluation of various models in audio translation using the CoVoST-2 benchmark shows that GPT-4o achieved the highest BLEU score of approximately 42, surpassing other models significantly.
While Meta's SeamlessM4T-v2 and Google's AudioPaLM-2 demonstrated strong capabilities with scores around 35, they fell short of GPT-4o's performance. OpenAI's Whisper-v3 and Meta's XLS-R achieved lower scores of approximately 28 and 25, respectively. These results underscore GPT-4o's exceptional performance in real-time speech translation, solidifying its position as the leading model for audio translation tasks and demonstrating its superior efficiency and accuracy across multiple languages.
Audio Evaluation
The audio ASR performance evaluation reveals that GPT-4o, using a 16-shot method, significantly outperforms Whisper-v3 across various regions based on the Word Error Rate (WER).
GPT-4o consistently outperformed Whisper-v3 in audio transcription tasks across various linguistic regions, as evidenced by lower Word Error Rates (WER). In Western European languages, GPT-4o achieved a 5% WER compared to Whisper-v3's 7%. The performance gap widened in other regions: Eastern Europe (10% vs 15%), Central Asia/Middle East/North Africa (15% vs 20%), Sub-Saharan Africa (17% vs 30%), South Asia (20% vs 35%), South East Asia (10% vs 15%), and the CJK region (7% vs 10%). These results underscore GPT-4o's superior accuracy in transcribing diverse languages and accents, demonstrating its advanced capabilities in audio processing across global linguistic landscapes.
Exam Evaluation
The M3Exam zero-shot results highlight GPT-4o's superior accuracy compared to GPT-4 across various languages and question types.
In Afrikaans, Chinese, and English, GPT-4o achieved impressive accuracy rates of 85%, 80%, and 78% respectively. It also excelled in other languages such as Italian, Javanese, and Portuguese, with accuracy rates ranging from 75% to 80%. Notably, GPT-4o's proficiency extended to vision questions, where it maintained its lead with 75% accuracy in Afrikaans and 70% in both Chinese and English. These results highlight GPT-4o's enhanced capabilities in processing both textual and visual inputs across diverse linguistic contexts, marking a significant improvement over GPT-4's performance.
Vision Evaluation
Eval Sets | GPT-4o | GPT-4T 04-09 | Gemini 1.0 Ultra | Gemini 1.5 Pro | Claude Opus |
---|---|---|---|---|---|
MMMU | 69.1 | 63.1 | 59.4 | 58.5 | 59.4 |
MathVista | 63.8 | 58.1 | 53.0 | 52.1 | 50.5 |
AI2D | 94.2 | 89.4 | 79.5 | 80.3 | 88.1 |
ChartQA | 85.7 | 78.1 | 80.8 | 81.3 | 80.8 |
DocVQA | 92.8 | 87.2 | 90.9 | 86.5 | 89.3 |
ActivityNet | 61.9 | 59.5 | 52.2 | 56.7 | 52.2 |
EgoSchema | 72.2 | 63.9 | 61.5 | 63.2 | 61.5 |
GPT-4o sets new benchmarks in visual understanding tasks. The model achieves state-of-the-art performance across various visual perception evaluations. All vision-related assessments were conducted in a zero-shot setting, with MMMU, MathVista, and ChartQA specifically utilizing zero-shot chain-of-thought (CoT) reasoning. This demonstrates GPT-4o's advanced capabilities in interpreting and reasoning about visual information without prior task-specific training.
Key Features
GPT-4o builds upon its predecessors, such as GPT-4 and GPT-4 Turbo, but offers enhanced performance, efficiency, and versatility. It is designed to handle complex tasks with greater accuracy and speed, making it a powerful tool for developers and businesses looking to leverage cutting-edge AI capabilities.
Some of the key features and improvements of GPT-4o include:
- Multimodal capabilities — GPT-4o can accept any combination of text, audio, image, and video inputs, and generate text, audio, and image outputs.
- Real-time processing — It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is comparable to human response time in a conversation.
- Enhanced performance — GPT-4o matches GPT-4 Turbo performance on text in English and code, with significant improvements in non-English languages.
- Improved efficiency — The model is 50% cheaper in the API compared to previous versions.
- Larger context window — GPT-4o maintains the 128k token context window, allowing it to process more information in a single prompt.
- Updated knowledge base — GPT-4o has knowledge of events up to April 2023.
Features
OpenAI GPT-4o distinguishes itself with several key improvements and capabilities:
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End-to-end multimodal processing — Unlike previous models that used separate models for different modalities, GPT-4o is trained end-to-end across text, vision, and audio, allowing for more integrated and nuanced understanding and generation.
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Real-time audio processing — GPT-4o can respond to audio inputs with human-like speed, significantly reducing latency compared to previous voice interaction models.
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Enhanced multilingual capabilities — The model shows significant improvement in processing and generating non-English languages.
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Advanced vision understanding — GPT-4o sets new high watermarks on vision-related benchmarks and tasks.
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Improved efficiency — The model is faster and more cost-effective to run compared to its predecessors.
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Versatile output generation — GPT-4o can generate not just text, but also audio and images, expanding its creative and interactive capabilities.
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Safety measures — OpenAI has implemented safety measures across all modalities, including filtering training data and refining the model's behavior through post-training.
GPT-4o represents OpenAI's continued effort to advance AI technology, providing a powerful tool that can handle more nuanced, multimodal interactions and perform a wider range of tasks with improved efficiency and accuracy.
What are the differences between GPT-4 and GPT-4o?
GPT-4o is a significant advancement over GPT-4, with several key differences:
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Multimodal capabilities — While GPT-4 primarily focused on text and image inputs with text outputs, GPT-4o can process and generate text, audio, image, and video inputs and outputs.
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Real-time processing — GPT-4o can respond to audio inputs in milliseconds, comparable to human response times, which is a major improvement over GPT-4's processing speed.
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Integrated model — Unlike GPT-4, which often relied on separate models for different tasks, GPT-4o is trained end-to-end across multiple modalities, allowing for more coherent and context-aware responses.
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Enhanced multilingual performance — GPT-4o shows significant improvements in processing and generating non-English languages compared to GPT-4.
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Cost efficiency — GPT-4o is 50% cheaper to use in the API compared to previous versions, making it more accessible for developers and businesses.
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Advanced vision capabilities — While GPT-4 had some image understanding abilities, GPT-4o sets new benchmarks in vision-related tasks.
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Broader creative outputs — GPT-4o can generate not just text, but also audio and images, expanding its creative and interactive potential beyond GPT-4's capabilities.
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Updated knowledge — GPT-4o's knowledge base is more current, with information up to April 2023, compared to GPT-4's earlier cutoff date.
In essence, GPT-4o represents a more versatile, efficient, and capable evolution of the GPT series, designed to handle a wider range of inputs and outputs while maintaining high performance across various tasks.
How can developers access GPT-4o?
Developers can access GPT-4o through the OpenAI API. As of the announcement, the following details are available:
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API Access — GPT-4o is available in the API as a text and vision model.
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Performance and Cost — Compared to GPT-4 Turbo, GPT-4o is 2x faster, half the price, and has 5x higher rate limits.
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Rollout Plan — The text and image capabilities of GPT-4o are being rolled out immediately.
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Future Capabilities — OpenAI plans to launch support for GPT-4o's new audio and video capabilities to a small group of trusted partners in the API in the coming weeks.
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ChatGPT Integration — GPT-4o's capabilities are also being rolled out in ChatGPT, including in the free tier and for Plus users with higher message limits.
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Voice Mode — A new version of Voice Mode with GPT-4o will be available in alpha within ChatGPT Plus in the coming weeks.
To use GPT-4o, developers will need to have an OpenAI API account. The exact model name to be used in API calls has not been specified in the provided information, but it's likely to follow a similar naming convention to previous models (e.g., "gpt-4o-date").
As with previous model releases, developers should refer to OpenAI's official documentation for the most up-to-date information on how to access and use GPT-4o in their applications.