Maybe not impossible using shared/lossy storage if they were sparsely scattered over a large space ?

But anyways - minutes. Thanks.

Edit: Gemini suggested that this sort of (lossy) storage size could be achieved using "Product Quantization" (sub vectors, clustering, cluster indices), giving an example of 256 dimensional vectors being stored at an average of 6 bits per vector, with ANN being one application that might use this.