AEO & AI Search
GPT-4o Token Counter & Web Scraping Cost Calculator
Scraping and digestion costs for OpenAI GPT-4o ($2.50 / 1M input tokens).
LLM Context Window & Token Cost Estimator
Active Model:
Estimated TokensCalibrated BPE
109
~3.5 chars / token
Signal-to-NoiseClean DOM
40%
44 text vs 65 markup
Cost / 1,000 Scrapes$2.5/1M
$0.270
On GPT-4o
Context WindowOpenAI
0.09%
Of 128,000 limit
GPT-4o Context Utilization109 / 128,000 tokens (0.09%)
Ingestion Cost Comparison (Per 10,000 Scrapes):
Click any card to switch active modelClaude 3.7 Sonnet
$3.27
$3/1M • 200k ctx
Claude 3.5 Sonnet
$3.27
$3/1M • 200k ctx
Claude 3.5 Haiku
$0.87
$0.8/1M • 200k ctx
GPT-4o
$2.73
$2.5/1M • 128k ctx
GPT-4o mini
$0.16
$0.15/1M • 128k ctx
o3-mini (Reasoning)
$1.20
$1.1/1M • 200k ctx
Gemini 2.0 Flash
$0.11
$0.1/1M • 1000k ctx
Gemini 1.5 Pro
$1.36
$1.25/1M • 2000k ctx
DeepSeek-R1 (Reasoning)
$0.60
$0.55/1M • 64k ctx
DeepSeek-V3
$0.15
$0.14/1M • 64k ctx
Llama 3.3 70B
$0.44
$0.4/1M • 128k ctx
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Methodology & Grounded Benchmarks
What is the Signal-to-Noise Ratio (SNR) in web scraping?
Signal-to-Noise Ratio measures the proportion of readable content tokens versus raw HTML boilerplate, div wrappers, and script tags. Standard web pages often exhibit an SNR below 25%, meaning 75% of your token budget is wasted on markup overhead.
Why does token count matter for Agent Engine Optimization (AEO)?
Autonomous AI agents (such as Claude Computer Use, OpenAI Operator, and Perplexity) prioritize sites that provide clean, semantic HTML or JSON-LD. Pages with high token bloat take longer to parse and risk truncation in restricted agent sub-contexts.