Example content: this dummy article exists to exercise the publishing pipeline and should be replaced or unpublished before launch.

Local inference benchmarks are easy to produce and surprisingly easy to misread. A useful result starts by naming the exact model artifact, runtime, hardware, prompt shape, generation length, and sampling settings.

Separate the measurements

Time to first token and steady-state generation speed answer different questions. Report them separately, include warm and cold runs when startup costs matter, and avoid reducing the whole experience to one throughput number.

Preserve the context

A number without its conditions is not portable evidence. Record the software versions, quantization, context length, and memory pressure alongside the result. When another system cannot reproduce the environment, it should still be able to understand the comparison's limits.

This example intentionally makes no benchmark claims and cites no sources. A real article must link important claims to primary evidence in its body.