Define Where “Slow” Occurs
Break an interaction into stages you can observe: submission to request dispatch, waiting for the first content, ongoing delivery, and completion. Choose only the stages relevant to your application. State exactly where each timer starts and stops, and connect the measurement to a user-visible effect, such as a blank waiting screen or a pause after content begins to appear. Client-side elapsed time can include local work, network transit, and response delivery. A single total duration cannot identify which stage caused a delay, and timing boundaries that differ between runs make comparisons unreliable.
Prepare Repeatable Checks
Build cases from tasks your application actually handles. Include short and longer inputs, different requested output lengths, and streaming or non-streaming interactions only if your application supports those modes. Keep prompt wording, conversation state, output instructions, and client environment consistent; vary one condition at a time. For each run, note the time period, network conditions, concurrent activity, session or cache state, and any retry. A hypothetical case to investigate, not a reported result: if a short input appears to finish sooner than a longer input, check generation length and delivery stages before considering possible explanations. That pattern alone does not establish a cause or predict what another run will show.
Record What You Observe
For each run, record a case label, input category, configuration, start and stop times for the stages you defined, any error or retry, and whether the response completed. Keep the actual observations rather than replacing them with labels such as “fast” or “slow”; do not retain only the most favorable run. When using model API access through NexoToken, consult the current main platform documentation for the available recording options. The account platform includes usage history, but do not assume it provides per-request timing, client-side network details, or a direct match to application logs. Where records can be matched using information your setup actually exposes, compare them carefully and note any gaps. Avoid adding undocumented endpoints or assuming that a history view captures measurements it does not show.
Investigate Conditionally, Then Bound Conclusions
If repeated runs of the same case vary, check whether network conditions, concurrent requests, retries, or session state also changed. If variation appears only for a particular input category, check prompt length, requested output, and synchronous client-side work. If the wait before the first content changes while subsequent delivery appears steady, inspect request dispatch, first-content arrival, and rendering as separate events; this is a diagnostic lead, not proof of a specific cause. Change one condition in a comparison, repeat the case, and record the result rather than assuming the change will help. Mark incomplete or inconsistent observations as unresolved. Report conclusions only for the environment, configuration, and cases you actually checked; do not turn a local observation into a claim that one model is generally faster or slower, and do not invent benchmark outcomes.
Sources & further reading
NexoToken platform and community
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