This is a concrete self-improvement loop with production economics attached: the model is being used to lower the marginal cost of running the model.
“Our primary objective is to serve more tokens with the same hardware, while preserving the intelligence, latency, availability, and reliability users expect.”
“If a task requires 30 model requests, an extra second per request adds up.”
“Tool output is capped at 10,000 tokens by default unless the model requests a different limit.”
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