Moderate Tokens Question 73 of 223

How do you count tokens before calling an API?

GenAI / LLM · Speak this in 60–90 seconds · Faridabad & Delhi NCR

The model does not read letters like humans. It reads these pieces, then predicts the next one.

Use the same tokenizer the model uses, such as tiktoken for many OpenAI models.

LLMs use tokens (not full words) because it helps them:

This is a process

question about Tokens.

Panels listen for order,

trade-offs, and what you would actually do on a GenAI / LLM project - not buzzwords.

Stable token IDs

Each piece maps to a number the network can learn.

Fits the model

Fixed pieces are what transformers expect as input.

Before the model can read a sentence, it goes through these steps:

1
Use the same tokenizer
the model uses, such as tiktoken for many OpenAI models.
2
Character heuristics like four
characters per token are only rough.
3
Count messages after chat-template
formatting, including tools and retrieved context.
4
Context mix
Attention looks at nearby tokens together.
5
Next token
The model scores what should come next.
6
Decode
IDs turn back into readable text.

Let's see how a real sentence is tokenized (tokens may vary by model):

Input text

“Character heuristics like four characters per token are only rough.”

Tokenized output

Characterheuristicslikefourcharactersper

Token IDs (example)

2987408337471632900

Note: Actual tokens and IDs depend on the tokenizer (e.g., GPT, Llama, etc.).

Use the same tokenizer the model uses, such as tiktoken for many OpenAI models. Character heuristics like four characters per token are only rough.