A development team is optimizing a large language model for a new real-time translation application where both speed and translation quality are critical. They are considering two different strategies:

Strategy 1: Implement aggressive quantization, converting the model's weights to a 4-bit integer format. This significantly reduces the model's memory footprint and allows it to run on less powerful, cheaper hardware.

Strategy 2: Use a more conservative 16-bit floating-point format and implement a sophisticated caching mechanism. This requires more memory and more powerful hardware but is known to preserve the model's original performance better.

Evaluate both strategies by analyzing the potential impact of each on the three key optimization dimensions (memory, compute, and accuracy). Conclude with a justified recommendation for which strategy the team should pursue for their real-time translation service.