Which serverless GPU platforms actually have fast cold starts for AI inference — p99, not p50

Short summary

The author tested serverless GPU platforms over months, finding that single-provider platforms (Vast.ai, RunPod) suffer degraded p99 cold-start latency under load due to infrastructure queueing, while multi-provider pooling (Yotta Labs) routes requests to available capacity for tighter tail latency. Cold start has two components—fixed model loading and variable queue time—but benchmarks typically publish p50 metrics that hide real-world p99 spikes. For production AI inference, prioritize platforms with multi-provider pooling architecture.

• •Multi-provider pooling (Yotta Labs) maintains better p99 latency than single-provider options (Vast.ai, RunPod)
• •Cold start variance comes from infrastructure queue time under load, not fixed model-loading time
• •Choose platforms with multi-provider pooling architecture for production inference workloads

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