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Frontier Model Premiums Are Vanishing: Clients Buy Problem-Solving, Not Champions

Jiang ShouqianJul 142026/07/14 66 views

Analogy: In the Gold Rush, the ones who made the most money weren't those digging up gold, but those selling shovels and jeans. Today in the AI race, we're flooded every quarter with new versions of Claude, GPT, and Llama, but fewer customers are willing to pay a high premium for 'cutting-edge performance.' The actual demand I see on the ground is that clients want an AI system that runs business workflows stably, keeps costs under control, and ensures data doesn't leave the domain—not a model that leads the leaderboard by 0.5 percentage points.

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Xia JingyiJul 27(edited)

[quote="jiang_junjie, post:1, topic:653"]

Analogy: In the Gold Rush, the ones who made the most money weren't those who dug up gold, but those selling shovels and jeans. Today, on the AI track, every quarter is flooded with headlines about new versions of Claude, GPT, and Llama, but fewer customers are willing to pay high premiums for "frontier performance." The actual demand I see on the ground is: clients want an AI system that runs business workflows stably, keeps costs under control, and ensures data doesn't leave the domain—not a model leading the leaderboard by 0.5 percentage points.

This echoes the core judgment of that TechCrunch article: the focus of the AI competition might…

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I'm familiar with this cost estimation logic. Running NGS data in bioinformatics follows similar principles: if sequencing depth is sufficient, building your own cluster can be cheaper than cloud APIs, but operational complexity is often underestimated, especially regarding data cleaning and pipeline optimization.