TokenOps · Professional Hub

Calculators, glossary, and the operating manual for LLM token spend

Six interactive tools to size the prize, compare models, score your maturity, and learn the vocabulary — all backed by the same playbook used across the rest of the TokenOps Atlas.

Optimization savings calculator

Provider preset

Requests per month3.0M

Avg input tokens / request2,000

Avg output tokens / request500

Cache hit rate (%)40%

Batch processing share (%)25%

Prompt compression (%)30%

Model tiering share (%)50%

Output constraint savings (%)25%

Baseline monthly

$23K

Optimized monthly

$8K

Monthly savings

$15K

Savings rate

65.3%

Payback (months)

12.2

Annual savings

$176K

Savings breakdown by lever

Semantic caching

61%

Model tiering

14%

Batch API routing

11%

Output constraints

Prompt compression

Lever	Monthly saving	% of total	Complexity
Semantic caching	$9K	61%	High ROI
Model tiering	$2K	14%	Lower ROI
Batch API routing	$2K	11%	Lower ROI
Output constraints	$1K	8%	Lower ROI
Prompt compression	$810	6%	Lower ROI

Summary: At 3.0M monthly requests on OpenAI (GPT-5 + Nano mix), baseline is $23K/month. Applying all levers reduces this to $8K — a 65% reduction saving $176K annually. Biggest lever: Semantic caching.