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Updated 3 months ago

perhaps is a stupid question but can

perhaps is a stupid question .... but ... can anyone explain me the difference of LLm tokens and embeddings token ...?? its something that must improve in my algortims??
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LLM tokens are the number of tokens sent to the LLM (i.e. text-davinci-003 by default, or you might have specified gpt-3.5-turbo, both from OpenAI)

Embedding tokens are the number of tokens sent to the embedding model (i.e. text-ada-002 from OpenAI by default)

This is important because it tells you the cost from OpenAI to build indexes and answer queries

LLMs:
text-davinci-003 = $0.02/1k tokens
gpt-3.5-turbo = $0.002/1k tokens
gpt-4 = $0.03-$0.06/1k tokens

Embeddings:
text-ada-002 = $0.0004/1k tokens
ok ... so the 2 of them it will be charged to my ... jojoj
Yup! Every index you make or query you make will use different amounts of tokens
But it's pretty cheap for the most part in my opinion
perfect... and a standar ... charge a $0.01 for a query that his result its a index of a book of 150pages ... is fine ... what do you think ???
Yea that sounds about right!
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