Most LLM cost isn't compute – it's identity drift (110-cycle GPT-4o benchmark) (github.com) 1 points by teugent 9mo ago ↗ HN
[–] teugent 9mo ago ↗ We ran a controlled 110-cycle benchmark on GPT-4o under identical context limits and temperature.Baseline used a static system prompt. SIGMA runtime reasserts identity and consolidates context each cycle.Results: - 60.7% fewer tokens (1322 → 520) - 20.9% lower latency (3.22s → 2.55s) - baseline drifted at cycle 23 and collapsed by cycle 73No fine-tuning, no RAG, no larger context window. Just runtime-level control.Happy to answer questions.
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[ 3.9 ms ] story [ 14.7 ms ] threadBaseline used a static system prompt. SIGMA runtime reasserts identity and consolidates context each cycle.
Results: - 60.7% fewer tokens (1322 → 520) - 20.9% lower latency (3.22s → 2.55s) - baseline drifted at cycle 23 and collapsed by cycle 73
No fine-tuning, no RAG, no larger context window. Just runtime-level control.
Happy to answer questions.