Embedding models made a quiet quality leap (RAG got better).
RAG quality improved quietly—test new embeddings on your content.
What changed
• New embedding models show 15-30% improvement on retrieval benchmarks
• Better multilingual and domain-specific understanding
• Some newer models are both better and cheaper than predecessors
Who it affects
• RAG builders
• Semantic search applications
• Anyone doing vector similarity matching
What to do now
• Benchmark new embeddings on your actual retrieval tasks
• Test migration on a subset before full re-embedding
• Monitor retrieval quality metrics after switching
• Consider domain-specific embeddings for specialized content