Findapeach.com - Original Research
What the high-earners actually take home: average annual earnings per creator in the top-1,000, top-50, and top-10 brackets for every US state and the country's 100 biggest cities - alongside the same creator counts, gender mix, prices, followers, and minimum-wage comparisons as our 2026 USA location report.
At Findapeach.com, we operate at the intersection of data science and adult content. As one of the leading metasearch engines for OnlyFans and their over 400 million monthly visitors, we focus on the platform's most active creators - a number closer to 699,000 who are regularly publishing and monetizing their work. This unique position gives us a front-row view of both the creator and consumer sides of the industry.
The United States is home to the largest concentration of OnlyFans creators anywhere in the world - an estimated 345,892 active models generating over $3 billion in annual creator revenue, accounting for 52.3% of the global platform total. But that national figure hides enormous variation. This page breaks the US down by all 50 states and the top 100 creator cities to answer: Where exactly are America's creators, and which places punch above their weight?
The dataset combines our proprietary scraper (which continuously crawls OnlyFans for creator data) with a third-party export of verified profiles. We applied strict inclusion criteria for active accounts: login activity within the last 6 months, at least 5 posts or media items, and no inactive or closed status. This means the dataset represents creators who are actively trying to generate revenue on the platform - not every account ever registered. Free-text locations were cleaned and standardized (e.g., "Chicago" becomes Chicago; whimsical entries like "Hogwarts" or "North Pole" are marked Unknown).
City-level entries are validated against a master reference database to ensure only genuine cities appear in the rankings - state names, territories, and regional descriptors are excluded. Comparisons use metro-area populations (sourced from Macrotrends) rather than strict city limits, as creators typically self-identify with the nearest major hub (e.g., Evanston creators list "Chicago"; Fort Lauderdale creators often say "Miami"). Boroughs and satellite areas are aggregated into parent metros (e.g., Brooklyn merges into New York City; the DMV area rolls into Washington, D.C.). Dallas Fort Worth is retained as a single ranking entry despite spanning two cities - the bulk of creators in that metro self-list their location as "Dallas Fort Worth" with no consistent split between Dallas proper and Fort Worth, so any disaggregation would be arbitrary; the metro is treated as one entity for ranking purposes. State populations use US Census Bureau estimates.
The results provide the most detailed publicly available breakdown of where America's OnlyFans creators are concentrated - both in absolute numbers and on a per-adult-population basis.
The Total Models figures in the tables below are extrapolated estimates that account for creators who don't list a location. The profile counts shown on individual Findapeach pages are observed (raw) counts. Both are valid - they answer different questions. For definitions, formulas, and caveats, see the Methodology section at the bottom of the page.
Focus on USA - regional density & economic context
Where USA OnlyFans creators are based. Findapeach scraping data on 180,056 active profiles in the United States.
States with population data, sorted by creator density per 100,000 adults.
Cities in the United States with at least one observed creator and population data, sorted by density.
Average creator earnings against local benchmarks (full year, USD).
The average United States OnlyFans creator earns 55% of full-time min wage (6.6 months equivalent) and 11% of median household income. Local cost of living index is 100 (NYC=100), so those dollars buy +0% what they would in NYC.
United States OnlyFans creators generated about $3,014M in 2024. Compared to similarly-sized United States industries:
The United States creator economy is comparable in size to the US sex toy & adult novelty industry ($3.01B vs $3.00B). It runs across 345,874 individual creators, with no studio, label, or distributor in between.
These are upper-end, full-time "expert in the field" salaries - not entry-level pay and not part-time wages. A "Cardiologist" benchmark means a senior cardiologist at the top of their career, not a first-year resident; a "Retail Cashier" benchmark means a senior full-time worker in a high-cost market, including benefits and shift premiums, not someone on a few part-time shifts. Each Top-1,000 / Top-50 / Top-10 USD value in the state and city tables is matched to the highest rung whose salary is below it. Top-N averages below the floor (a full-time minimum-wage job) are labelled "Below Full-Time Wage".
| Expert annual salary (USD) | Comparable Profession |
|---|---|
| $35K/yr | Retail Cashier |
| $45K/yr | Retail Salesperson |
| $60K/yr | Bartender |
| $85K/yr | Plumber |
| $110K/yr | Registered Nurse |
| $150K/yr | Police Captain |
| $190K/yr | High School Principal |
| $250K/yr | Big Tech Engineering Manager |
| $350K/yr | Family Dentist |
| $525K/yr | Cardiologist |
| $800K/yr | Non-Equity Big Law Partner |
| $1.3M/yr | Wall Street Managing Director |
| $2.2M/yr | NFL Veteran |
| $3.5M/yr | Top Neurosurgeon |
| $5.5M/yr | NBA Bench Player |
| $10M/yr | Hollywood Lead Actor |
| $20M/yr | Fortune 100 CEO |
| $40M/yr | Top Tier Pop Star |
| $70M/yr | A List Movie Star |
Average OnlyFans creator earnings against US wage anchors. The mean is dragged down by the long tail; the bracket tables above show the gap between rank-and-file and the top earners.
US OnlyFans creators generated approximately $3.0B in 2024 (estimated, gross consumer spend; ~80% reaches creators after the platform cut). Compared to other US consumer / media categories:
Highest likes-share publish-status creators in United States, with followers, modelled annual income, and the comparable expert-tier profession from the global salary ladder. Income is likes-share attribution against OnlyFans' disclosed creator pool: (likes ÷ Σlikes) × $5.776B. Comparable Profession picks the highest rung from the expert-tier global salary ladder at or below that modelled figure. Names link to each creator's OnlyFans profile.
These yearly-income figures are an extrapolation, not a measured value. They divide each creator's likes by the location's total likes and multiply by the location's yearly creator-economy pool — so they are indicative of relative scale, not actual earnings. Real monetisation varies considerably with subscription pricing (free vs paid), promo offers, custom-content sales, tip jar volume, content type and engagement quality; some creators earn far more than likes-share suggests, others far less.
| # | Creator | Likes | Followers | Yearly income | Comparative income |
|---|---|---|---|---|---|
| 1 | Bryce Adams 💪🍑 | 13,019,968 | 4,647 | $23.82M | Fortune 100 CEO |
| 2 | PeachJars | 9,531,506 | 818 | $17.44M | Hollywood Lead Actor |
| 3 | Jessica Nigri | 6,627,233 | 1,027 | $12.12M | Hollywood Lead Actor |
| 4 | Mrs. Poindexter | 6,050,353 | 11,757 | $11.07M | Hollywood Lead Actor |
| 5 | 𝐿𝒶𝒸𝒾𝑒 𝑀𝒶𝓎 💋 Average Mom Next door 🚪 | 5,914,010 | 1,622 | $10.82M | Hollywood Lead Actor |
| 6 | 💋Marleny1 | 5,872,151 | 1,144 | $10.74M | Hollywood Lead Actor |
| 7 | Riley Reid | 4,338,818 | 260 | $7.94M | NBA Bench Player |
| 8 | Valorie 🥰 | 4,215,830 | 441 | $7.71M | NBA Bench Player |
| 9 | Mia Malkova🤍🤍 | 3,746,830 | 1,365 | $6.85M | NBA Bench Player |
| 10 | Txkitty69 💕 BIRTHDAY MONTH 🎂🎉 | 3,720,295 | 11,346 | $6.81M | NBA Bench Player |
| 11 | Brynn Woods | 3,691,499 | 1,994 | $6.75M | NBA Bench Player |
| 12 | Taylor’s diary | 3,498,745 | 271 | $6.4M | NBA Bench Player |
| 13 | Alyssa 💞✨ | 3,427,245 | 23,038 | $6.27M | NBA Bench Player |
| 14 | Emily Lynne 🍑 | 3,421,041 | 729 | $6.26M | NBA Bench Player |
| 15 | ANGELA WHITE | 3,160,793 | 19 | $5.78M | NBA Bench Player |
| 16 | Tati Evans ✨ | 3,125,345 | 510 | $5.72M | NBA Bench Player |
| 17 | Corinna Kopf | 2,731,143 | 12 | $5M | Top Neurosurgeon |
| 18 | Ava Addams | 2,664,155 | 4 | $4.87M | Top Neurosurgeon |
| 19 | Violet Brandani | 2,659,488 | 162 | $4.87M | Top Neurosurgeon |
| 20 | alvajay 🎀 | 2,631,790 | 3,824 | $4.81M | Top Neurosurgeon |
| 21 | NakedGamer | 2,596,079 | 39,725 | $4.75M | Top Neurosurgeon |
| 22 | Nakedbakers | 2,595,102 | 4,692 | $4.75M | Top Neurosurgeon |
| 23 | Sweet Vickie FREE 💋 Top 1% | 2,593,327 | 4,249 | $4.74M | Top Neurosurgeon |
| 24 | 🌺 Brooke is 𝗖𝗥𝗘𝗔𝗠𝗬 🥛 | 2,532,601 | 1,447 | $4.63M | Top Neurosurgeon |
| 25 | 💋 Sara Underwood | 2,520,062 | 458 | $4.61M | Top Neurosurgeon |
| Top 25 total / average | $60.8M ($2.43M avg) | ||||
A complete, plain-language explanation of every column in the US States and Top 100 US Cities tables - where each number originates, how it is calculated, and what it represents.
The US States and Top 100 US Cities analyses are subsets of the same underlying dataset used for the Country Analysis and Top 100 Global Cities tables. The same raw profiles, the same extrapolation approach, and the same revenue modelling apply. Two important adjustments are made for US-specific analysis.
This dataset does not include every account registered on OnlyFans. Only profiles that meet an activity threshold are included: a minimum of 5 posts, images, or videos published, and the account must have been active within the last 6 months. This filters out dormant, abandoned, or placeholder accounts and ensures the data reflects creators who are actively trying to generate revenue. There are significantly more accounts registered on OnlyFans than appear in this analysis, but those that do not pass this activity test are excluded.
Rather than using the global $5.776B revenue pool, the US analyses use a US-specific revenue pool derived from the Country Analysis: the United States accounts for 49.6% of the global platform revenue estimate - $3,063M of the $6,178M global total. All state and city revenue figures are distributed from this US pool.
Using a US-specific pool keeps the state-level revenue figures internally consistent with the Country Analysis. All 50 states' revenues sum to approximately $3,063M - the same figure shown for the United States in the Country Analysis.
Not every profile contains a usable location field. Observed counts are scaled up using a coverage rate computed at runtime from the actual dataset - not a hardcoded constant. This is the same approach used in the Country Analysis.
The Total Models figures in these tables are extrapolated estimates designed to represent the full creator population, including those who don't list a location. The profile counts visible on the site are observed counts - the actual number of profiles that list a given location. Both numbers are valid; they answer different questions.
For example, California shows approximately 31,000 profiles that explicitly list California as their location, but only ~55% of all profiles include a usable location at all. The extrapolated California total in the table is therefore approximately 31,000 ÷ 0.55 ≈ 57,970. The site profile pages show the observed count; the state analysis here shows the extrapolated estimate. Neither is wrong - they answer different questions.
The headline US total (346K extrapolated) is taken directly from the country-level US count in the Country Analysis - not by summing the 50 individual state totals. This is intentional: a meaningful share of profiles resolve to "United States" with no specific state attached (e.g. just "USA", "America", or a US ZIP without a state), so summing the 50 state counts will always be lower than the true country total.
For the current dataset the 50 state totals sum to approximately 285K, while the US country-level total is 346K. The ~61K gap represents profiles attributed to the United States as a country but without a more specific state-level location. This gap is expected and does not indicate missing data - the country-level number is the authoritative US figure.
For the Top 100 US Cities table, city counts use the same coverage-rate scaling as states. Many profiles resolve to a US state but not a specific city, so as with states, the sum of all listed cities is lower than the US country total.
Both stages of extrapolation assume that creators who omit detail are distributed in the same proportions as those who provide it. If creators in specific states or cities are systematically more or less likely to list detailed locations, the corresponding estimates will be affected.
Revenue is distributed using the same engagement-weighted approach as the global analysis - each location receives a share of the US revenue pool proportional to its combined subscriber and follower engagement score.
Like the global figures, these are arithmetic means pulled upward by a small number of top earners. The typical creator in any state or city earns substantially less than the stated average.
States or cities ranked #1 downward by estimated total creator count. California, Florida, and Texas typically dominate by raw count due to their large populations.
Ranked by creators per 100,000 adult residents. States with smaller populations but high engagement often rank higher here than by raw count.
For the Top 100 US Cities table, city population figures are sourced from Macrotrends and use metropolitan area populations rather than city-centre-only figures. This is because creators tend to list the nearest major city as their location rather than the specific outer-suburban municipality they live in. A creator in Arlington, Texas, for example, will typically list "Dallas Fort Worth" rather than a smaller local area name. Using metro populations ensures that density calculations reflect the realistic catchment area that each city name represents in the data.
Gender classification uses automated image recognition applied to each model's profile photo, combined with any gender-affirming statement present in the profile. Where both signals are available, stated gender takes precedence as the authoritative source. Image recognition provides coverage where no gender is explicitly stated.
Profiles identified as Trans - either through stated gender or image recognition - are classified first and excluded from subsequent steps.
Remaining profiles identified as Male via stated gender or image recognition are classified as Male.
All remaining profiles are classified as Female based on stated gender or image recognition output.
All gender percentages in the US States and Top 100 US Cities sheets are
stored as direct percentage
values (e.g. 82.89 = 82.89% female).
The following three columns appear in the Top 100 US Cities table only (they are not included in the US States sheet).
The applicable city or state minimum wage for that location in USD, annualised (hourly rate × 2,080 hours). States without their own minimum wage above the federal floor use the federal figure.
The last three sortable columns answer the question journalists ask most: what does a typical high-earner in this location actually take home? For each location we estimate annual revenue per active creator, rank descending, and report the average per creator across the top 1,000, top 50, and top 10 brackets.
Average annual earnings of the 1,000 highest-earning active located creators in that state or city. This is the most "broad-shouldered" view - it picks up small-town breadwinners as well as superstars and is the closest thing to a typical high-earner number.
Average annual earnings of the 50 highest-earning active located creators. The mid-bracket lens - established performers but not just the household names.
Average annual earnings of the 10 highest-earning active located creators. Use this column when you want a sense of what the elite at the top of the local creator economy actually pull in.
To make the dollar figures easier to feel, each top-N average is paired with a US occupation whose median annual salary sits closest to that figure on a hand-curated 21-tier ladder running from fast-food worker (~$15K) up through registered nurse, dentist, federal judge, MLB rookie, and NFL starter to A-list movie star. The ladder uses public US Bureau of Labor Statistics medians for the trades and licensed professions, and well-reported public-record figures for the high tiers. The match is approximate - it answers "the average top-N creator in this state earns about as much as a [profession]."
The same publish & recently active & non-empty profile filter used for the per-location creator counts (post_status=publish, last_seen within 180 days, ≥5 posts or media). Free-tier creators with non-zero followers contribute via the engagement fallback; pure ghost profiles drop out.
These are upper-bound estimates of subscription-revenue potential, computed from observed price and subscriber numbers. They do not include PPV unlocks, tips, or DM sales (which can rival subscriptions for top earners), and they do not net out OnlyFans' 20% platform fee. They also assume reported subscriber counts are accurate at the moment of crawl. For a single creator the number can be wrong; for an average across the top 10, 50, or 1,000 in a state or city, the noise mostly averages out.
Every candidate city is validated against a master city reference database. Non-city entries (territories, regions, sub-continents) are rejected. NYC borough entries are consolidated into a single New York City record. Cities are ranked by estimated total creator count, with the top 100 shown.
The Global Cities table ranks the top 100 cities worldwide. The US Cities table ranks the top 100 within the United States only. Los Angeles, New York City, and Las Vegas appear near the top of both, but density rankings differ because the global table uses international population benchmarks.
| Column in Spreadsheet | Type | Description |
|---|---|---|
| State | Raw | US state name; all 50 states are covered |
| Total Models | Extrapolated | Estimated total creators in this state (two-stage extrapolation) |
| Ranking (No. Models) | Calculated | State rank by estimated creator count; 1 = most creators |
| Ranking (By Density) | Calculated | State rank by creators per 100,000 adult residents |
| % Female | Calculated | Share of profiles classified as female, as a direct percentage (e.g. 82.89) |
| % Male | Calculated | Share classified as male (non-trans), as a direct percentage |
| % Trans | Calculated | Share with "trans" in gender field, as a direct percentage |
| Yearly Revenue ($M) | Calculated | Estimated annual creator revenue for this state in millions USD |
| Top 1,000 - Avg Earnings ($/yr) | Calculated | Average estimated annual earnings per creator within the top-1,000-earner bracket for this state, displayed in compact form ($XK / $X.XM) |
| Top 1,000 - Comparable Profession | Reference | A US occupation whose median annual salary is closest to the Top-1,000 average for this state |
| Top 50 - Avg Earnings ($/yr) | Calculated | Same metric, averaged across the top 50 earners |
| Top 50 - Comparable Profession | Reference | A US occupation whose median salary is closest to the Top-50 average for this state |
| Top 10 - Avg Earnings ($/yr) | Calculated | Same metric, averaged across the top 10 earners |
| Top 10 - Comparable Profession | Reference | A US occupation whose median salary is closest to the Top-10 average for this state |
| Column in Spreadsheet | Type | Description |
|---|---|---|
| City | Raw | US city name, validated against master city reference database |
| Country | Raw | All entries are "United States" in this sheet |
| Total Models | Extrapolated | Estimated total creators in this city (two-stage extrapolation) |
| Rank (Models) | Calculated | City rank by estimated creator count within the US top 100 |
| Rank (Density) | Calculated | City rank by creator density relative to city adult population |
| % Female / % Male / % Trans | Calculated | Gender breakdown as direct percentages |
| Yearly OF Model Revenue ($M) | Calculated | Estimated annual creator revenue for this city in millions USD |
| Avg Annual/Model ($) | Calculated | Estimated mean annual creator earnings |
| Min Wage/Yr ($) | Reference | Annual minimum wage applicable to this city in USD |
| % Diff vs Yearly Min Wage | Calculated | Percentage difference between avg model earnings and annual minimum wage |
| Top 1,000 - Avg Earnings ($/yr) | Calculated | Average estimated annual earnings per creator within the top-1,000-earner bracket for this city, in compact form ($XK / $X.XM) |
| Top 1,000 - Comparable Profession | Reference | A US occupation whose median annual salary is closest to the Top-1,000 average for this city |
| Top 50 - Avg Earnings ($/yr) | Calculated | Same metric, averaged across the top 50 earners |
| Top 50 - Comparable Profession | Reference | A US occupation whose median salary is closest to the Top-50 average for this city |
| Top 10 - Avg Earnings ($/yr) | Calculated | Same metric, averaged across the top 10 earners |
| Top 10 - Comparable Profession | Reference | A US occupation whose median salary is closest to the Top-10 average for this city |
| Source | Used For | Link |
|---|---|---|
| OnlyFans | Publicly visible profile data (location, gender, price, followers, subscribers) | onlyfans.com |
| US Census Bureau Economic Census | State-level industry revenue data (NAICS codes, 2022 data) | census.gov/economic-census |
| US Department of Labor | Federal and state minimum wage rates | dol.gov/minimum-wage/state |
| US Census Bureau Population Estimates | State population figures, adult population ratios | census.gov/popest |
| Macrotrends | City metropolitan area population figures (used for city density rankings) | macrotrends.net |
| Numbeo | Cost of living indices by US city (NYC = 100 baseline) | numbeo.com/cost-of-living |
| OnlyFans Financial Reporting | Platform revenue estimates ($7.22B gross, 80% creator share) | fenixintl.com (Companies House filings) |
