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Openai/691a41cd-2efc-800c-9eff-de439224a90d
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===== For a response of, say, ~4,000 output tokens: ===== * LoreToken case - Input tokens: ~25 - Output tokens: ~4,000 - Total β 4,025 tokens * Natural-language prompt case - Input tokens: ~220 - Output tokens: ~4,000 - Total β 4,220 tokens Even in this small example, the LoreToken version trims roughly: * 220 β 25 = 195 input tokens saved, or about a * ~4β5% reduction in total tokens processed for this one call On a single laptop, 4β5% might feel small. In a large-scale deployment (millions to billions of calls per day), shaving 4β5% of GPU work off every heavy generation is enormous. And this is just from compressing the instruction/control channel, not yet touching memory, logs, configs, or datasets.
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