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Up to 110x differences in cold-start latency reveal that execution infrastructure can dramatically impact the efficiency of coding-agent reinforcement learning.
Traditional benchmarks miss 82% of LLM performance, revealing a vast underestimation of their true capabilities in diverse tasks.