What is throughput? Work completed per unit time differs from latency
Explain request and token throughput and compare capacity using concurrency, lengths and failures.
Understand the concept
Throughput is work processed or completed per unit time, such as requests or tokens per second. Units and lengths differ. High throughput guarantees neither low latency nor quality. Define windows, valid completion and load and exclude failed or duplicate output from usable production.
Volume and individual waiting describe different properties
NVIDIA distinguishes throughput and latency; PagedAttention studies serving memory and batching. Concurrency can raise total output while increasing individual queues. Specify input versus output tokens and task lengths. Long answers and short labels produce different numbers. Evaluate quality and latency constraints rather than promising peak saturation for every workload.
Check valid completions and queues under one workload
Use fixed public classification inputs and output criteria, increase authorized concurrency and count valid completions per interval. Track failures, cancellations and retries separately and avoid duplicate work counts. Record individual waits. No load test or throughput measurement occurred here. Match model and precision so smaller models or reduced quality are not mislabeled service optimization.
Sustained capacity also needs failure and resource conditions
Short peaks do not prove sustained operation; inspect memory, queues and recovery as needed. Offline batches prioritize volume while interactive tasks also constrain waits. Preserve workload settings and replay after updates. Include reserved capacity and failure handling. Report units and conditions so high numbers cannot conceal incomplete or unacceptable outputs.
Checked sources
These sources support the concepts and methods described here. Examples and test scope are labeled separately; check the version of the tools you use.