Introduction
The landscape of artificial intelligence (AI) is constantly evolving, and a significant paradigm shift is occurring: model speed is beginning to outweigh raw intelligence. Martin Alderson discusses this phenomenon in an article where he explains why he now prioritizes speed over raw intelligence for his daily tasks. But what does this mean for tech businesses?
Why Speed is Taking Over
Historically, model intelligence has been the main selection criterion. However, with models like Opus 4.6 that are "smart enough" for common tasks such as coding, conducting research, or data analysis, speed becomes a critical factor. Studies show that users prefer faster software, even if it is less sophisticated.[1]
Indeed, the interaction speed with a model can significantly enhance the user experience. When a model is fast, it allows for a smoother and more efficient workflow, which is essential in increasingly time-pressured environments.
The 100tok/s Threshold
Alderson highlights an interesting threshold: 100 tokens per second (tok/s) is the equivalent of "100ms feeling instant" for humans. This is the speed at which the average user can keep up with the model without being overwhelmed. Below 50tok/s, the model seems slow, while above 200tok/s, it becomes almost unsettling.
This notion of speed is crucial as it directly influences user productivity. Fast models like GLM5.2 or DeepSeek V4 Flash GA, capable of exceeding 100tok/s, enable the completion of complex tasks more rapidly.
Impact on Tech Businesses
For decision-makers and entrepreneurs, this paradigm shift means it's time to reconsider the criteria for selecting AI models. Speed can lead to productivity gains and better user satisfaction, which is vital to remain competitive.
For example, a company using a fast model for data analysis can obtain results more quickly, speeding up decision-making processes. In another case, a fast model for customer support can significantly improve user experience by reducing waiting times.
Conclusion
As AI models continue to improve, it is essential to adapt our selection criteria to maximize benefits. Prioritizing speed might seem counter-intuitive at first, but it's a strategy that can pay off in the long run in a world increasingly focused on efficiency.
Let's discuss your project in 15 minutes.