EasyExperience level: 0-2 years · 3-5 years1 min read

What are tokens and embeddings in an LLM?

Reviewed by Gurusankar M.

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Concept Made Simple

Coffee Chat Question

“What are tokens and embeddings in an LLM?”

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Mind Map Answer

A token is a chunk of text (roughly ¾ of a word). An embedding is that token turned into a list of numbers capturing its meaning.

Token
"interview" → maybe 1–2 tokens
Embedding
[0.12, -0.4, 0.9, ...] vector
Why
Similar meanings → nearby vectors

Think Beyond the Expected

What If?

Why do longer prompts cost more?

Models bill per token for both input and output. More words means more tokens to process, which means more compute and higher cost — plus you can hit the context window limit.

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Plain-language foundations

I'm preparing for a software engineering interview and want to understand this from scratch, as a beginner.

Topic: Tokens (AI Basics)
Interview question: "What are tokens and embeddings in an LLM?"

Please:
1. Explain the core idea in simple, plain language, using an everyday analogy.
2. Define any technical terms you use.
3. Walk through one small, concrete example.
4. Finish with a single sentence I can easily remember.

Keep the tone friendly and assume I'm new to this topic.
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