Load Testing Systems That Call a Model
Your load test was built for HTTP. The model answers in tokens. Speed, capacity, and correctness all change once a model is in the request path. The pilot passed because nobody was on it.
Four numbers classic load tests miss
A request that returns 200 in half a second and then streams for thirty passes a classic load test and fails the user. Time to first token, inter-token latency, output token throughput, and the saturation point are the four numbers a model-backed endpoint needs that requests per second does not provide.
Under concurrency, the time-to-first-token distribution spreads far beyond what a single tester sees. NVIDIA guidance states that total tokens per second rises as requests increase until GPU compute saturates, then can decrease. The tools you already own (LoadRunner, NeoLoad, JMeter, k6) can capture all four. The gap is that nobody wrote the test, not that the tool could not run it.
Three data points from the research
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What's inside: The four numbers classic load tests miss. Why capacity has a cliff. Six failure modes that pass a latency test. The two-layer method (application + inference). Sizing before you buy. Written for engineering leaders, four-walls environments, and performance teams.
No sales call required. Research-backed metrics from Gartner, NVIDIA, and academic studies.
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