I've been thinking about why specialized inference providers keep appearing instead of everything being vertically integrated into model companies. The logic is pretty straightforward once you see it.
The best model changes constantly. GPT-4 gets replaced, Claude arrives, new versions launch, and suddenly you're rerouting everything. For a vertically integrated company, that's expensive. You're stuck with dedicated hardware and a product that degrades.
Inference providers operate differently. They spread demand across multiple models. When one surges, others might dip. The aggregate demand is actually quite smooth, which makes capacity planning much more manageable.
For founders evaluating AI startup ideas, this creates a clear strategic fork: own the full stack or specialize in the inference layer. The infrastructure play seems to favor companies that can aggregate diverse demand. A small startup might not hit that threshold.
But there's a subtler point. If the model layer eventually commoditizes, inference providers become the durable business. That's the real bet here. Whether that convergence actually happens is what I keep coming back to.
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