$NOS (Nosana) decentralized GPU grid offers a solid cost advantage for AI inference on Solana, but two technical observations stand out:

1. Cold-start latency on large model weights: When deploying quantized models (>14GB weights), container initialization times vary noticeably across decentralized nodes. Having a "pre-warmed cache" or bandwidth rating indicator on the worker node list would help developers select optimal nodes and avoid job timeouts.

2. Mid-inference worker failover: If an assigned GPU node drops offline during a long batch run, does the scheduler automatically re-route the workload to an equivalent tier without requiring a manual re-submission transaction from the client? Clarifying this failover behavior in the developer docs would build significant confidence for production pipelines.