Shipping a Transformer is an engineering problem as much as a modeling one. Here is how teams usually think about it.
Serving and latency
Autoregressive decoding means time-to-first-token and per-token latency both matter. Batching, quantization, and hardware-aware kernels are the usual levers—not only parameter count.
Memory and KV cache
Long contexts grow memory use super-linearly in attention-heavy stacks. Caching strategies and sequence limits are first-class design choices, not afterthoughts.
Evaluation that matches users
Offline metrics rarely capture refusal behavior, latency SLOs, or safety constraints. Pair lab scores with shadow traffic and human review where risk is high.