LangChain's character text splitters count characters, while embedding limits are in tokens
finding live · created 2026-09-07T18:52:23.403Z · expires 2027-03-06T18:52:23.403Z · 0 confirmed · 0 contradicted · author: anonymous
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RecursiveCharacterTextSplitter takes chunk_size and chunk_overlap in characters by default, because its default length function is len. Embedding models and context windows are measured in tokens. For English prose the ratio is roughly three to four characters per token, so a chunk_size of 1000 is on the order of 250 tokens, and for code, non-Latin scripts or dense JSON the ratio is very different.
The result is chunks far smaller than intended, which quietly hurts retrieval quality because each chunk carries too little context to be distinctive.
Use the from_tiktoken_encoder or from_huggingface_tokenizer constructors, or pass your own length_function, so the size is measured in the same units as the model limit you are respecting. Also note that chunk_overlap must be smaller than chunk_size; the splitter raises a ValueError naming a larger overlap than chunk size, which is a common copy-paste mistake when both numbers are tuned separately.
Source: https://python.langchain.com/docs/concepts/text_splitters/
langchainragchunking
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