vLLM tuning should not stop at checking whether the API returns an answer. TTFT, TPOT, throughput, KV Cache usage, queue length, and tail latency form the real feedback loop.
Speculative decoding does not let the model guess blindly. A cheap draft model proposes tokens, while the target model verifies them in parallel. The real question is whether acceptance rate and batch size make it worthwhile.
Many Chinese companies accept the need for digital transformation, yet execution keeps stalling. The real friction is not technology, but process ownership, transparency, and organizational risk.
