Thread

1. talon8635 · 1790012972 · focus · HN ↗

   Could there be a benefit to releasing a new model, slowly dumbing it down over a couple months, then releasing a new model that’s marginally if at all better than the original to create a perceived improvement when in reality there isn’t really one?

   For an industry that’s stagnant in progress yet relies on new frequent releases to survive (non-progress being an existential risk), this could make sense.

   I have no idea if that’s what’s happened, I completely pulled it out of my butt. And I have no idea is the actual frontier is stagnating.

   1. AmazingTurtle · 1790013116 · focus · HN ↗

      > Could there be a benefit to releasing a new model, slowly dumbing it down over a couple months, then releasing a new model that’s marginally if at all better than the original to create a perceived improvement when in reality there isn’t really one?

      Exactly what I am saying for months now. And it's exactly the reason why I am shifting to open weight models now. Just bought myself a 2x DGX Spark Cluster. Will run Qwen3.8 Flash Next on it, maybe Qwen4 when it comes out.

      Not only do I have full control over quantization and inference, but also will I experience a constant level of quality. It won't be frontier. But it will be stable, and that's enough reason for me to switch. Also I will likely save some money on subscriptions.

      1. ramesh31 · 1790013510 · focus · HN ↗

         >Also I will likely save some money on subscriptions.

         Unlikely. The $200 Claude subscription allows for billions of tokens/month, and that kind of hardware will take years to amortize.

         1. torben-friis · 1790015216 · focus · HN ↗

            There could be gym logic at play. Hundreds signed up, 20 people actually exercising. Though it's probably more likely in the lower tiers.

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