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OpenAI o1 is a generative pre-trained transformer released by OpenAI in September 2024.
o1 spends time “thinking” before it answers, making it more efficient in complex reasoning tasks, science and programming.
But, is OpenAI o1 really much better than other models from OpenAI? And what are the best use cases for this model?
Find out in my updated OpenAI o1 statistics, facts and trends guide for 2024.
You can use this jump link to quickly jump to the KEY STATS section.
Also, all the references and resources I used in crafting my guide are listed at the bottom of the page.
Jump here: Key OpenAI o1 Statistics, Facts and Trends for this Year| Detailed OpenAI o1 Statistics, Facts and Trends for this Year
Table of Contents
Key OpenAI o1 Statistics, Facts and Trends for this Year
Key OpenAI o1 Statistics, Facts and Trends for 2024
- OpenAI’s o1 scores 83% on International Mathematics Olympiad Qualifier. This is much over its predecessor, GPT-4o, which only achieved 13% accuracy on the same test.
- OpenAI’s o1 ranks in 89th percentile on Codeforces. This achievement highlights o1’s advanced reasoning capabilities in solving complex algorithmic problems and optimizing code efficiency.
- OpenAI’s o1 solves 74% of challenging math problems on the American Invitational Mathematics Examination (AIME). This is a substantial leap from GPT-4o’s 9% success rate on the same examination.
- OpenAI’s o1 excels in physics, biology, and chemistry, achieving PhD-level accuracy on the GPQA benchmark. This performance indicates o1’s potential as a valuable assistant in scientific research across multiple disciplines.
- OpenAI’s o1 can process up to 128,000 tokens. This large capacity allows the model to process and understand much longer pieces of text or more complex problems in a single prompt.
- OpenAI offers o1-preview and o1-mini variants for flexibility. This dual-model approach provides options for different use cases and resource constraints.
- OpenAI’s o1 uses internal “reasoning tokens” to power its “thought process“. These tokens represent the model’s internal chain of thought reasoning but are not visible in the output.
- Chain-of-thought reasoning is key to o1’s complex problem-solving abilities. This approach allows the model to break down intricate problems into a series of interconnected steps. At least that’s what OpenAI claim.
- OpenAI’s o1 shines in mathematics, coding, and scientific reasoning. This specialization makes it an invaluable tool for research institutions, tech companies, and educational organizations focused on STEM fields.
- OpenAI’s o1 excels in challenging languages like Yoruba and Swahili. This enhancement in language processing capabilities makes o1 a more versatile tool for global enterprises and research institutions.
- OpenAI’s o1 achieves a reduced hallucination rate of 0.44 on the SimpleQA test. This lower hallucination rate indicates that o1 is less likely to generate false or misleading information when answering questions and generating responses.
- OpenAI’s o1 achieves 94% correct answer selection on unambiguous questions. This statistic from the Bias Benchmark for QA evaluation highlights o1’s enhanced ability to provide fair and unbiased responses.
- OpenAI’s o1 has enhanced jailbreak resistance and content policy adherence. This improvement in safety features is crucial for enterprises deploying AI in public-facing or sensitive applications.
- OpenAI’s o1 comes with slower response times compared to previous models. This trade-off between depth of reasoning and speed of response is due to its extensive reasoning processes.
- OpenAI’s o1 has higher costs reflecting its advanced capabilities (o1-preview: $15 per million input tokens, $60 per million output tokens; o1-mini: $3 per million input tokens). These rates are significantly higher than those for earlier models, indicating the increased computational resources required for o1’s advanced reasoning processes.
Detailed OpenAI o1 Statistics, Facts and Trends for this Year
How Does OpenAI’s O1 Perform on the International Mathematics Olympiad Qualifier?
OpenAI’s o1 scores 83% on International Mathematics Olympiad Qualifier.
This performance demonstrates a significant improvement over its predecessor, GPT-4o, which only achieved 13% accuracy on the same test.
OpenAI’s o1 also ranks in 89th percentile on Codeforces. This achievement highlights o1’s advanced reasoning capabilities in solving complex algorithmic problems and optimizing code efficiency.
In recent testing OpenAI’s o1 successfully solved 74% of challenging math problems on the American Invitational Mathematics Examination (AIME). Despite not getting a perfect score (100% is perfect) the 74% problem-solve rate is a substantial leap from GPT-4o’s 9% success rate on the same examination.
OpenAI’s o1 also excels in physics, biology, and chemistry, achieving PhD-level accuracy on the GPQA benchmark. This performance indicates o1’s potential as a valuable assistant in scientific research across multiple disciplines, though I’m not aware of any notable scientist using o1 to help with their research.
What is the Token Processing Capacity of OpenAI’s O1?
OpenAI’s o1 processes 128,000 tokens. This large capacity allows the model to process and understand much longer pieces of text or more complex problems in a single prompt. However, maximum output token limit for OpenAI o1-preview is 32K and for OpenAI o1-mini is 65K. OpenAI officially recommend to allocate at least 25K tokens for reasoning and outputs.
OpenAI o1 is the first AI model that introduces new types of tokens called “reasoning tokens”
Reasoning tokens power the thought process that o1 model uses to come up with solutions to difficult problems. These tokens represent the model’s internal chain of thought reasoning but are not visible in the output.
What Variants of O1 Does OpenAI Offer?
OpenAI offers o1-Preview and o1-Mini variants for flexibility. This dual-model approach provides options for different use cases and resource constraints.
o1-Preview is designed to solve hard problems across domains of human knowledge and intelligence. o1-Mini is faster and cheaper and particularly good at coding, math, and science.
What is the Key to O1’s Complex Problem-Solving Abilities?
Chain-of-thought reasoning is key to o1’s complex problem-solving abilities. This approach allows the model to break down intricate problems into a series of interconnected steps.
How Does OpenAI’s O1 Perform with Challenging Languages?
OpenAI’s o1 excels in challenging languages like Yoruba and Swahili. This enhancement in language processing capabilities makes o1 a more versatile tool for global enterprises and research institutions.
What is OpenAI O1’s Hallucination Rate on the SimpleQA Test?
OpenAI’s o1 achieves a reduced hallucination rate of 0.44 on the SimpleQA test. This lower hallucination rate indicates that o1 is less likely to generate false or misleading information when answering questions.
How Does OpenAI’s O1 Perform in Answer Selection for Unambiguous Questions?
OpenAI’s o1 achieves 94% correct answer selection on unambiguous questions. This statistic from the Bias Benchmark for QA evaluation highlights o1’s enhanced ability to provide fair and unbiased responses.
What Improvements Does OpenAI’s O1 Have in Terms of Safety Features?
OpenAI’s o1 has enhanced jailbreak resistance and content policy adherence. This improvement in safety features is crucial for enterprises deploying AI in public-facing or sensitive applications.
How do OpenAI O1’s Response Times Compare to Previous Models?
OpenAI’s o1 comes with slower response times compared to previous models. This trade-off between depth of reasoning and speed of response is due to its extensive reasoning processes. Basically, while the model “thinks” you wait and the end result is much better than with faster, regular GPT models.
What are the Costs Associated with Using OpenAI’s O1?
OpenAI’s o1 has higher costs reflecting its advanced capabilities (o1-preview: $15 per million input tokens, $60 per million output tokens; o1-mini: $3 per million input tokens). These rates are significantly higher than those for earlier models, indicating the increased computational resources required for o1’s advanced reasoning processes.
How to use OpenAI o1 for Free?
It is not possible to use OpenAI o1 for free.
This premium AI model is only available to paying Open AI users.
OpenAI o1 Statistics, Facts and Trends for 2024 (Conclusion)
My updated guide for 2024 lists the best and latest statistics, facts and trends about OpenAI o1.
I hope you enjoyed it because the guide is now over. You can read my OpenAI statistics and ChatGPT statistics and GPT-4 statistics, GPT-3 statistics, GPT-2 statistics and GPT-1 statistics guides next.
During my research, I consulted these resources below:
References:
- Learning to Reason with LLMs- https://openai.com/index/learning-to-reason-with-llms/
- OpenAI o1 explained: Everything you need to know- https://www.techtarget.com/whatis/feature/OpenAI-o1-explained-Everything-you-need-to-know
- OpenAI o1- https://platform.openai.com/docs/guides/reasoning
- OpenAI o1- https://en.wikipedia.org/wiki/OpenAI_o1
- OpenAI expands o1 model availability – here’s who gets access and how much- https://www.zdnet.com/article/openai-expands-o1-model-availability-heres-who-gets-access-and-how-much/
- Introducing OpenAI o1- https://openai.com/o1/
- O1 is useless (for us and our use cases)- https://community.openai.com/t/o1-is-useless-for-us-and-our-use-cases/939838/1
- OpenAI O1 API Tutorial: How to Connect to OpenAI’s API- https://www.datacamp.com/tutorial/openai-o1-api
- How to Access OpenAI o1?- https://www.analyticsvidhya.com/blog/2024/09/how-to-access-openai-o1/
- OpenAI o1 and How It Works- https://medium.com/bimser-tech/openai-o1-and-how-it-works-0eb270efc341
- First impressions of OpenAI o1: An AI designed to overthink it- https://techcrunch.com/2024/09/13/first-impressions-of-openai-o1-an-ai-designed-to-overthink-it/
- What it means that new AIs can “reason”- https://www.vox.com/future-perfect/372843/openai-chagpt-o1-strawberry-dual-use-technology
- 15 Statistics & Facts to Know About OpenAI’s o1 Model- https://skimai.com/15-statistics-facts-to-know-about-openais-o1-model/
- OpenAI o1 and How It Works- https://medium.com/bimser-tech/openai-o1-and-how-it-works-0eb270efc341
Nikola Roza
Nikola Roza is a blogger behind Nikola Roza- SEO for the Poor and Determined. He writes for bloggers who don't have huge marketing budget but still want to succeed. Nikola is passionate about precious metals IRAs and how to invest in gold and silver for a safer financial future. Learn about Nikola here.