For developers designing a retrieval pipeline who want to see what chunk size and overlap do to chunk count and cost. You get the number of chunks, the effective step, embedded tokens and the embedding cost.
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You enter
50,000 tokens, chunk size 512, overlap 64, $0.02 per 1M
The tool shows
112 chunks, effective step 448 tokens, about 57,344 embedded tokens, embed cost $0.001147
Many pipelines start with 256 to 1,024 tokens and about 10 to 20 percent overlap, then tune by checking retrieval quality on real questions. Smaller chunks are more precise; larger ones carry more context.
Overlap repeats the end of one chunk at the start of the next, so a sentence or idea split at a boundary still appears whole in at least one chunk.
The step is chunk size minus overlap, and chunks equal the total tokens minus overlap divided by the step, rounded up. Each chunk is embedded at full chunk size, so overlap adds to the bill.
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