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OpenAI will integrate “o3” into GPT-5 instead of releasing it separately, streamlining adoption while signalling a shift toward fewer, more controlled AI models amid rising competition and cost pressures.
“One cannot rule out this move being triggered by competitive models like DeepSeek, which are highly cost-effective,” said Sanchit Vir Gogia, chief analyst and CEO at Greyhound Research. “Of course, there shall be many other models out there that will be more cost-effective and innovative, and most importantly, will be made open source and not proprietary like OpenAI.”
Importantly, not all organizations have the resources, need, or strategic planning to navigate complex, tiered pricing structures. “Despite the rise of SaaS, many large enterprises prefer EULA contracts since they are incubated from any risk associated with sudden and unplanned need for resources,” Gogia added. “In the same breath, not all organizations require a customized model and the flexibility that comes along with it. Many of their use cases are simplistic enough to use a model that keeps the billing and the use simple.”
As quoted in Computerworld.com
Additional comments by Greyhound Research analyst:
Before understanding why OpenAI decided to integrate the models and the benefits for enterprises, we must first understand organisations’ struggles when using such models:
- One of the significant issues with using these models is the need to integrate them and the complexity involved in making them work together. Hence, any consolidation or simplification that can come via integration can help organisations streamline the use of these models.
- Based on the above issue, the most significant impact is cost structures, which make this even more complex and costly when deploying across the enterprise at scale. Any ease of integration and navigation will directly result in cost efficiencies.
- Of course, integrating these models will also help improve reliability performance for data analysis or content generation. It will also help organisations stabilise these AI solutions so they do not have to manage different versions. This effect will improve and make managing updates and overall maintenance more manageable.
- All these benefits will naturally also help organisations scale. Such integrated models can potentially handle more critical workloads at scale and ensure compliance and security are adhered to.
- Such integration of complex models will eventually also improve the nuanced understanding the model brings to the enterprise. This means that organisations can use the combination of the O-series and GPT-series to handle more complex issues at the workplace.
However, OpenAI’s timing of this announcement is triggered by the recent launch of DeepSeek, a model that is as good as OpenAI but far more cost-effective and open source. Of course, many similar models exist, but DeepSeek has created a profound industry impact that can limit OpenAI in many ways. Hence, OpenAI announced the merging of O-series and GPT-series models. Since we are speaking of costs and its importance in decision-making, here’s some additional context:
- The fact is, AI spending has been a critical conversation across most management teams, and questions on ROI outcomes have all been tabled. However, costing is never a straight answer when dealing with such models. It depends on multiple variables, including (but not limited to) the need for customisation, the cost needed to secure and stabilise the model, and costs related to compliance audits and managing government regulations. One has to differentiate the cost of training from the cost of inference, and that is where many of the marketed cost benefits can become questionable. The more modular the model, the higher the cost to train and stabilise it.
- However, not all organisations have the wherewithal, the need, the planning or the strategy to manage complex, tiered pricing. Despite the rise of SaaS, many large enterprises prefer EULA contracts since they are incubated from any risk associated with sudden and unplanned need for resources. In the same breath, not all organisations require a customised model and the flexibility that comes along with it. Many of their use cases are simplistic enough to use a model that keeps the billing and the use simple.
- Lastly, one should also remember that government regulations and overall outlook (read as future regulations) on the topic are also significant points during decision-making. There are also costs associated with moving to and from models. So many CxOs will naturally prefer models emerging from companies headquartered in countries with healthy bilateral relationships with their governments.
Analyst In Focus: Sanchit Vir Gogia
Sanchit Vir Gogia, or SVG as he is popularly known, is a globally recognised technology analyst, innovation strategist, digital consultant and board advisor. SVG is the Chief Analyst, Founder & CEO of Greyhound Research, a Global, Award-Winning Technology Research, Advisory, Consulting & Education firm. Greyhound Research works closely with global organizations, their CxOs and the Board of Directors on Technology & Digital Transformation decisions. SVG is also the Founder & CEO of The House Of Greyhound, an eclectic venture focusing on interdisciplinary innovation.
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