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LLM token counting: exact methods vs. heuristics and cost management

By PulseAugur Editorial · [2 sources] ·

Two articles discuss methods for counting tokens in large language models (LLMs), essential for managing context windows, costs, and prompt lengths. The first article contrasts the exact token counts provided by OpenAI's `tiktoken` library with a dependency-free Python heuristic, highlighting `tiktoken`'s accuracy for billing and enforcement versus the heuristic's utility for relative size analysis. The second article offers practical advice on token math, explaining what tokens are, providing rules of thumb for quick estimates, and detailing how to count tokens exactly using `js-tiktoken` for JavaScript or `tiktoken` for Python, as well as API endpoints for models like Claude and Gemini. Both articles emphasize that non-English text, code, and special characters consume more tokens than standard English prose, and offer strategies for reducing token usage to manage costs and performance. AI

IMPACT Developers can better manage LLM costs and context window limits by understanding and implementing precise token counting methods.

RANK_REASON The articles provide practical guides and code examples for using tokenization libraries and techniques, which are tools for developers working with LLMs.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

LLM token counting: exact methods vs. heuristics and cost management

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Tool
The articles provide practical guides and code examples for using tokenization libraries and techniques, which are tools for developers working with LLMs.
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2 independent sources
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product, infra
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High
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21 days old
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COVERAGE [2]

  1. dev.to — LLM tag TIER_1 Nederlands(NL) · Royal Simpson Pinto ·

    Counting LLM Tokens in Python: tiktoken vs a Dependency-Free Heuristic

    <p>Every LLM feature I build eventually needs to answer one question: how many tokens is this? Context windows are measured in tokens, cost is measured in tokens, and truncation happens in tokens. Characters and words are close enough to lie to you and not close enough to trust.<…

  2. dev.to — LLM tag TIER_1 English(EN) · ThatToolSite ·

    Count Your Tokens Before You Paste: Practical LLM Token Math

    <p>You paste a long doc into ChatGPT, Claude or Gemini and one of three things happens: the answer ignores the end of it, you hit a context limit, or the API bill is bigger than you expected. All three come down to the same number: <strong>tokens</strong>.</p> <p>Here's the pract…

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