Artificial intelligence inference speed includes response startup latency, token generation rate, and the time needed to complete a useful model output. Hardware, model size, quantization, batching, caching, serving software, load, and network placement all affect observed speed.
Fast model generation can keep a user engaged during interactive prototyping, but end-to-end workflow speed also includes tool calls, compilation, tests, network requests, and retries. A headline token rate does not measure the full task experience.
