Can OpenAI’s New o1 Models Transform STEM with Superior Reasoning?

OpenAI has recently unveiled a new family of large language models (LLMs), dubbed “o1,” which aims to deliver superior performance and accuracy in science, technology, engineering, and math (STEM) fields. This launch came as a surprise, as many anticipated the release of either “Strawberry” or GPT-5 instead. The new models, o1-preview and o1-mini, are initially available to ChatGPT Plus users and developers through OpenAI’s paid API, enabling developers to integrate these models into existing third-party applications or create new ones on top of them.

Enhanced Reasoning Capabilities

A key feature of the o1 models is their enhanced “reasoning” capabilities. According to Michelle Pokrass, OpenAI’s API Tech Lead, these models employ a sophisticated reasoning process that involves trying different strategies, recognizing mistakes, and engaging in comprehensive thinking. In tests, o1 models have demonstrated performance on par with PhD students on some of the most challenging benchmarks, particularly excelling in reasoning-related problems.

Current Limitations

The o1 models are currently text-based, meaning they handle text inputs and outputs exclusively and lack the multimodal capabilities of GPT-4o, which can process images and files. They also do not yet support web browsing, restricting their knowledge to data available up to their training cutoff date of October 2023. Additionally, the o1 models are slower than their predecessors, with response times sometimes exceeding a minute.

Early Feedback and Practical Applications

Despite these limitations, early feedback from developers who participated in the alpha testing phase revealed that the o1 models excel in tasks such as coding and drafting legal documents, making them promising candidates for applications that require deep reasoning. However, for applications demanding image inputs, function calling, or faster response times, GPT-4o remains the preferred choice.

Pricing and Access

Pricing for the o1 models varies significantly. The main o1-preview model is the most expensive to date, costing $15 per 1 million input tokens and $60 per 1 million output tokens. Conversely, the o1-mini model is more affordable at $3 per 1 million input tokens and $12 per 1 million output tokens. The new models, capped at 20 requests per minute, are currently accessible to “Tier 5” users—those who have spent at least $1,000 through the API and made payments within the last 30 days. This pricing strategy and rate limit suggest a trial phase where OpenAI will likely adjust pricing based on usage feedback.

Notable Uses During Testing

Among the notable uses of the o1 models during testing include generating comprehensive action plans, white papers, and optimizing organizational workflows. These models have also shown promise in infrastructure design, risk assessment, coding simple programs, filling out requests-for-proposal (RFP) documents, and strategic engagement planning. For instance, some users have employed o1-preview to generate detailed white papers with citations from just a few prompts, balance a city’s power grid, and optimize staff schedules.

Future Opportunities and Challenges

While the o1 models present new opportunities, there are still areas where improvements are necessary. The slower response time and text-only capabilities are significant drawbacks for certain applications. However, the high performance in reasoning tasks makes them valuable for specific use cases, particularly in STEM-related fields.

How to Access the Models

Developers keen on experimenting with OpenAI’s latest offerings can access the o1-preview and o1-mini models through the public API, Microsoft Azure OpenAI Service, Azure AI Studio, and GitHub Models. OpenAI’s continuous development of both the o1 and GPT series ensures that there are numerous options for developers looking to build innovative applications.

In summary, OpenAI’s introduction of the o1 family marks a significant step in the evolution of reasoning-focused LLMs, particularly for STEM applications. While the models have some limitations in speed and input modalities, their advanced reasoning capabilities offer promising avenues for complex problem-solving tasks. As OpenAI continues to refine these models, developers can expect incremental improvements and adjustments in pricing and performance, heralding a new era of AI development.

Explore more

Why Should Leaders Invest in Employee Career Growth?

In today’s fast-paced business landscape, a staggering statistic reveals the stakes of neglecting employee development: turnover costs the median S&P 500 company $480 million annually due to talent loss, underscoring a critical challenge for leaders. This immense financial burden highlights the urgent need to retain skilled individuals and maintain a competitive edge through strategic initiatives. Employee career growth, often overlooked

Making Time for Questions to Boost Workplace Curiosity

Introduction to Fostering Inquiry at Work Imagine a bustling office where deadlines loom large, meetings are packed with agendas, and every minute counts—yet no one dares to ask a clarifying question for fear of derailing the schedule. This scenario is all too common in modern workplaces, where the pressure to perform often overshadows the need for curiosity. Fostering an environment

Embedded Finance: From SaaS Promise to SME Practice

Imagine a small business owner managing daily operations through a single software platform, seamlessly handling not just inventory or customer relations but also payments, loans, and business accounts without ever stepping into a bank. This is the transformative vision of embedded finance, a trend that integrates financial services directly into vertical Software-as-a-Service (SaaS) platforms, turning them into indispensable tools for

DevOps Tools: Gateways to Major Cyberattacks Exposed

In the rapidly evolving digital ecosystem, DevOps tools have emerged as indispensable assets for organizations aiming to streamline software development and IT operations with unmatched efficiency, making them critical to modern business success. Platforms like GitHub, Jira, and Confluence enable seamless collaboration, allowing teams to manage code, track projects, and document workflows at an accelerated pace. However, this very integration

Trend Analysis: Agentic DevOps in Digital Transformation

In an era where digital transformation remains a critical yet elusive goal for countless enterprises, the frustration of stalled progress is palpable— over 70% of initiatives fail to meet expectations, costing billions annually in wasted resources and missed opportunities. This staggering reality underscores a persistent struggle to modernize IT infrastructure amid soaring costs and sluggish timelines. As companies grapple with