An engineer modifies a large language model by doubling the number of attention heads per layer while simultaneously halving the dimensionality of each head's key/value vectors. Assuming all other parameters (like the number of layers and sequence length) remain constant, how does this architectural change affect the multi-dimensional structure of the model's key-value (KV) cache?

KV Cache Structure Trade-offs

Calculating KV Cache Size per Token