8 hours (up to 24 hours with charging case)
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Many popular vision-language models (VLMs) have trended towards growing in parameter count and, in particular, the number of tokens they consume and generate. This leads to increase in training and inference-time cost and latency, and impedes their usability for downstream deployment, especially in resource‑constrained or interactive settings.
除了行业内部的问题，外部政策的不确定性也被从业者视为潜在风险。