Are AI models worse when new models in beta?

Have you noticed this with AI model rollouts?

Over the past couple of years, I’ve noticed a pattern with major AI providers like OpenAI, Anthropic, and Google. When a model is publicly available, it seems like compute resources are prioritized to support that stable version. But once a new version enters beta (e.g., trusted testers), the compute allocation feels more balanced—or even tilted toward the newer model.

The result? The stable version starts to feel slightly less precise than it did before the beta rollout. Still usable, still solid—but not quite as sharp. Just my impression, of course.

It reminds me of how phone manufacturers eventually stop supporting older hardware to focus on newer devices. So I’m wondering: will AI companies start deprecating or even open-sourcing older models to free up compute for current and experimental ones?

Curious if anyone else has noticed this or has thoughts on where this trend might lead.

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