Groq's Vertical Stack vs Gimlet's Orchestration

This split is really a fight over where the control point in AI inference lives. Gimlet is building the traffic cop that can route each request to the best available chip and kernel, while Groq is betting that if one vendor owns the silicon, runtime, and cloud endpoint together, it can deliver faster and more predictable output without that extra orchestration layer. Groq makes the strongest case in latency sensitive serving, while Gimlet matters most when customers run mixed hardware fleets.

• Groq is vertically integrated by design. It sells custom LPU based inference through GroqCloud, and its product layer has expanded into Compound, which pushes Groq beyond raw token generation into agent style workflows. That bundling makes Groq look less like a chip vendor and more like a full inference stack.
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• Gimlet sits at the opposite layer. Its core pitch is serverless inference plus autonomous kernel generation, compiler, and scheduling technology for heterogeneous hardware. In plain terms, it helps operators use many chip types at once, instead of forcing them to pick one vendor and live inside that vendor stack.
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• The biggest pressure on both models comes from incumbents collapsing the stack from above. NVIDIA now positions Dynamo as a distributed inference framework for high throughput and low latency serving, while AWS and Google package serving on their own accelerators like Trainium2 and TPU v6e inside existing cloud buying relationships.
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The market is heading toward two durable lanes. One lane is vertically integrated inference clouds that win on speed, consistency, and simple procurement. The other is orchestration software that wins wherever enterprises want bargaining power across chips, clouds, and model backends. As AI spending broadens, both lanes can grow, but the independent control layer becomes more valuable as hardware diversity increases.