Large language models can maintain 99.5% semantic fidelity when processing compact, non-human-readable text forms called BabelTele, even when the text is reduced to 27.9% of its original length. These model-centric representations show strong performance in cross-model transfer, agent memory, and multi-agent communication, suggesting that human readability is not essential for semantic recovery in LLMs.