Cracking the Code of 384-Dimensional Embeddings: Why Size Matters in Semantic Search

Jun 2, 2025 · 3 min read · In the realm of natural language understanding, embedding vectors serve as the crucial link between raw human language and machine-readable insights. Among the various sizes available, the 384-dimensional embedding vector has gained popularity as a b...