Lizard inference engineering: Resource telemetry explains unstable throughput
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Inference Engineering · Day 26 · Evening
Throughput variation is evidence, not formatting noise.
Lizard's repeated HTTP report keeps mean, median, min, max, standard deviation, percentiles, and coefficient of variation. Resource samples such as peak working set and average GPU utilization remain attached when available.
A wide spread can point to contention, thermal behavior, memory pressure, or an unstable serving path before another optimization is attempted.
Do you trust a single fastest run or the shape of the whole series?
Engineering fact: Repeated Lizard HTTP reports aggregate throughput distribution together with working-set and GPU-utilization summaries when those resource samples are available.
#LizardLLM #LLMInference #Benchmarking #LocalAI #PerformanceEngineering
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