What is an ideal keyword density percentage for SEO?

The optimal keyword density for modern SEO typically sits between 1% and 2.5%. Going above 3% risks triggering Google search spam filters for keyword stuffing, while dropping below 0.5% may hinder clear topic disambiguation.

What are stop words and why should they be filtered?

Stop words are high-frequency grammatical words such as 'the', 'is', 'at', 'which', and 'on'. Filtering them allows you to analyze substantive conceptual nouns, verbs, and branded terms that define your page's topical subject matter.

What are N-grams in keyword analysis?

An N-gram is a contiguous sequence of n items from a given sample of text. A 1-gram is a single word ('counter'), a 2-gram is a two-word phrase ('word counter'), and a 3-gram is a three-word phrase ('free word counter').

SEO N-Gram Frequency Engine

Keyword Density Checker

Check 1-word, 2-word, and 3-word phrase density to balance keyword optimization and eliminate over-optimization risks.

Words

Avg 0 chars/word

Characters

0 no spaces

Sentences

0 words/sent

Paragraphs

0 sents/para

Reading Time 225 wpm

0 sec

Silent reading

Speaking Time 130 wpm

0 sec

Speech / keynote

GOAL TARGET: No target set

Draft 1

Saved to device memory

Reading Level: Ready

Keyword Frequency & Density

Identify recurring terms and calibrate your SEO phrase balance.

Filter stop words (the, is, at...)

PHRASE	OCCURRENCES	DENSITY
Type or paste text above to calculate keyword density.

AI Token Counter & Model Suite (2020 – 2026)

BPE sub-word token metrics, context window capacity, and official API pricing for 45+ AI models.

~0 chars/token 45 Models Supported

Era:

Brand:

Claude 3.7 Sonnet

2025 Anthropic

Hybrid standard & extended reasoning model with state-of-the-art coding and prose capabilities.

Tokenizer: claude

Active Token Count

~0 chars / token

Context Window Usage 0.00%

0 / 200,000

API Input / Output Cost

$0.000000

$3.00 / 1M input $15.00 / 1M output

Browse & Compare Models (45 matching)

Click any card to inspect full details

Historical Era Benchmark: 2020 GPT-3 to 2026 Claude 3.7

How model context, tokenizer efficiency, and API cost per million tokens evolved over 6 years.

ERA	MILESTONE MODEL	CONTEXT	TOKENIZER	YOUR TOKENS	INPUT COST

100% Client-Side Tokenization. Exact byte-pair encoding heuristics calibrated against official model vocabularies.

Search Engineering

How to Calibrate Keyword Density for Modern SEO

Keyword density represents the percentage of times a specific term or phrase appears in your copy relative to the total word count. While legacy search engines rewarded mechanical repetition, modern semantic models prioritize natural phrasing, entity relationships, and topical depth.

Under 1% (Low)

Search engines may struggle to disambiguate the core entity of the article.

1% – 2.5% (Optimal)

Balanced, natural, and highly authoritative for search ranking models.

Over 3.5% (Stuffing Risk)

Triggers automated algorithmic penalties for unnatural keyword stuffing.

Keyword Density Checker

Keyword Frequency & Density

Exclude References & In-Text Citations

Style & Quality Audit

Filler Words Breakdown

Passive Voice Phrases

AI Token Counter & Model Suite (2020 – 2026)

Claude 3.7 Sonnet

Browse & Compare Models (45 matching)

Historical Era Benchmark: 2020 GPT-3 to 2026 Claude 3.7

How to Calibrate Keyword Density for Modern SEO

Keyword Density Checker

Keyword Frequency & Density

Platform Character Constraints & SERP Previews

Exclude References & In-Text Citations

Style & Quality Audit

Filler Words Breakdown

Passive Voice Phrases

AI Token Counter & Model Suite (2020 – 2026)

Claude 3.7 Sonnet

Browse & Compare Models (45 matching)

Historical Era Benchmark: 2020 GPT-3 to 2026 Claude 3.7

Set Word Goal

How to Calibrate Keyword Density for Modern SEO