🧩 RAG Architecture • Vector DB Sizing • OpenAI, Cohere, BGE Embeddings
RAG Chunking & Vector Embeddings Calculator
Bad chunking destroys RAG retrieval accuracy. Calculate token chunk boundaries, sliding window overlap, vector dimensional storage, and Pinecone / Qdrant RAM sizing in seconds.
Corpus Size & Chunking Parameters
Document Corpus Size: 50,000 words (~65,000 tokens)
1k words (1 blog) 100k words (1 book) 1M words (Enterprise Docs)
Total Chunks
145
Vector embeddings generated Index RAM Size
0.89 MB
Float32 uncompressed memory
PYTHON RECURSIVE CHUNKER CODE