@rayofhk: The cheapest AI may not be the cheapest AI. For a long time, much of the AI competition has been measured in price per token. But as AI moves from answering questions to actually completing work, I think that metric becomes increasingly incomplete. Imagine one model costs $1 but completes your task successfully only 60% of the time. Another costs $10 but succeeds 95% of the time. Which one is really cheaper? The cheapest token is not necessarily the cheapest completed task. This becomes even more important with AI agents. An agent may spend minutes reasoning, calling tools, searching databases, writing code, correcting mistakes and coordinating multiple steps before finally delivering an outcome. At that point, businesses may care much less about the cost of each individual token — and much more about whether the job actually gets done. That’s why the evolution of models such as DeepSeek V4 Pro is interesting to me. The important story isn’t simply that another chatbot is getting better. It is the broader transition from: AI that talks → AI that works. And if AI can reliably perform economically useful work, intelligence itself begins to acquire much clearer economic value. Perhaps the next phase of AI competition will therefore be measured less by: Price per token and increasingly by: Value per completed task. That could fundamentally change not only how AI models compete — but how they are priced. #AI #artificialintelligence #aiagents #DeepSeek #AgenticAI

🐉Ray🦅Sep20-200DayAnniversary

Open In TikTok:

Region: SG

Sunday 16 August 2026 10:51:49 GMT