State of OME.TV

Live statistics for Ome.tv, built from real encounters: where the strangers connect from, when the platform is busiest, how long a conversation actually lasts, and how much of what you meet is recorded video rather than a live camera.

The data is collected by the members running OmeUndfnd. No individual person, account or address appears anywhere on this page. Every figure is a total or a share, and anything with too small a sample is left out rather than published.

Window
last 30 days
Snapshot
2026-11-14, 14:22 UTC
Rebuilt
every 3 hours

What this window says

58.4%

of encounters came from Poland

The 20 published countries account for 93.8% between them. 202 more were seen in the window and fell under the publishing floor.

51.7%

land between 19:00 and 01:00 UTC

The busiest 6 hours of the day carry more than half of everything. The European morning is close to empty.

9.5%

of conversations get past fifteen seconds

Of the ones that do, 25.3% reach a minute. 0.4% of all encounters pass five minutes.

11,898

addresses are carrying a bot signal right now

The most common is frozen frame, on 10,299 of them.

Headline totals

3,746,706
Strangers identified
222
Countries reached
8,939
Hours on camera
4,047
Active members
3,136,252
Encounters sampled
The basis for everything below

Divided by the people who produced it, that is 926 lookups, 775 encounters and 133 minutes on camera per active member over the window.

Who is in this sample. Every figure below describes the strangers our members were matched with, not the Ome.tv population as a whole. Random matching is not evenly random across the world, and our own community is concentrated in Europe, which pulls the country and network tables toward it. The rhythm, duration, camera and bot figures are far less sensitive to that than the geography is.

The last 30 days

+20% week over week

120,861 lookups on an average day, busiest was Oct 24 with 196,414, quietest Oct 15 with 41,763

Oct 14Oct 29Nov 13
Show the daily numbers
Oct 1451,176
Oct 1541,763
Oct 1670,012
Oct 1762,102
Oct 1845,696
Oct 1950,934
Oct 2075,764
Oct 21104,562
Oct 22108,136
Oct 23156,157
Oct 24196,414
Oct 25101,219
Oct 26125,988
Oct 27134,351
Oct 28147,083
Oct 29160,395
Oct 30167,583
Oct 31194,538
Nov 1154,896
Nov 2113,789
Nov 392,645
Nov 495,345
Nov 5102,212
Nov 6131,997
Nov 7173,701
Nov 8115,725
Nov 9136,277
Nov 10173,014
Nov 11173,629
Nov 12177,985
Nov 13111,618

Where people connect from

Share of every encounter in the window, addresses we cannot place are in none of these

  • PolandPL58.4%
  • GermanyDE15.8%
  • United StatesUS3.8%
  • United KingdomGB3.4%
  • SpainES2.3%
  • RomaniaRO1.4%
  • CanadaCA1.1%
  • SwedenSE0.9%
  • NetherlandsNL0.9%
  • FranceFR0.7%
  • AustriaAT0.7%
  • ItalyIT0.7%
  • BrazilBR0.6%
  • PeruPE0.6%
  • CzechiaCZ0.5%
  • HungaryHU0.5%
  • BulgariaBG0.4%
  • IndiaIN0.4%
  • TürkiyeTR0.4%
  • BelgiumBE0.3%

These 20 cover 93.8% of encounters. Another 202 countries appeared in the window and stayed under the fifty-encounter floor.

The cities behind those countries

Same denominator as the countries, so a city is directly comparable to its country

  • WarsawPL7.4%
  • KatowicePL3.2%
  • KrakowPL2.2%
  • PoznanPL1.7%
  • LodzPL1.6%
  • WroclawPL1.6%
  • GdanskPL1.5%
  • BerlinDE1.0%
  • LondonGB0.9%
  • Frankfurt am MainDE0.9%
  • DusseldorfDE0.9%
  • SzczecinPL0.8%

A city appears here only once at least 50 encounters came from it. Smaller places are dropped rather than published, at that size a city name stops being a statistic.

The networks on the other side

Which operators the strangers you meet are connecting through

  • Orange Polska Spolka Akcyjna13.5%
  • P4 Sp. z o.o.11.4%
  • T-Mobile Polska S.A.6.6%
  • Deutsche Telekom AG4.6%
  • Polkomtel Sp. z o.o.4.4%
  • Vodafone GmbH4.0%
  • Telefonica Germany GmbH & Co.OHG3.3%
  • Netia SA3.0%
  • VECTRA S.A.1.9%
  • 1&1 Versatel GmbH1.3%

A network is a property of an address, never of a person. Operators below fifty encounters are left out, and these are shares of all encounters: the 10 above carry 54% between them and the rest is a long tail of smaller operators. Mobile carriers rank high here because a phone is how a large share of this platform connects.

When the platform is busiest

Peaks at 23:00 UTC, Saturday is the busiest day

00:0012:0023:00

Hour of day, UTC

Prime time. 51.7% of all encounters fall in the 6 hours between 19:00 and 01:00 UTC.

By day of week

  • Mon11.2%
  • Tue11.4%
  • Wed12.7%
  • Thu15.3%
  • Fri15.7%
  • Sat17.0%
  • Sun16.7%

The weekend takes 33.7% of the week, which is 16.9% on an average Saturday or Sunday against 13.3% on an average weekday. Weekdays are stated per day so the two are comparable.

Show the hourly numbers
00:00 UTC9.5%
01:00 UTC8.0%
02:00 UTC6.1%
03:00 UTC3.9%
04:00 UTC2.6%
05:00 UTC1.5%
06:00 UTC0.9%
07:00 UTC0.8%
08:00 UTC0.6%
09:00 UTC0.7%
10:00 UTC0.9%
11:00 UTC1.0%
12:00 UTC1.3%
13:00 UTC1.8%
14:00 UTC2.5%
15:00 UTC2.9%
16:00 UTC3.3%
17:00 UTC4.3%
18:00 UTC5.1%
19:00 UTC5.9%
20:00 UTC7.7%
21:00 UTC8.7%
22:00 UTC9.7%
23:00 UTC10.2%

How long a conversation lasts

91% of encounters are over within fifteen seconds

  • under 15 seconds90.5%
  • 15 seconds – 1 minute7.1%
  • 1 – 5 minutes2.0%
  • over 5 minutes0.4%

Read it conditionally. The first bucket swamps the rest, so the number that says whether a conversation actually starts is this one: of the 9.5% that survive fifteen seconds, 25.3% go on to pass a minute.

Measured from connection to disconnection on encounters members sampled, bucketed before it ever leaves the browser. A duration is stored as one of these four bands and never as a number that could fingerprint a session.

What you actually meet

Camera behaviour, automated estimates and the bot network's tally

4.0%
Frames with the camera off
Measured per sampled frame
56.4%
Connections with a visible face
Of connections the face model sampled
11,898
Addresses flagged as bots
By the member detection network
23
Average estimated age
Single-frame estimate, aggregated

Estimated gender split

91% mean confidence

Read male 67%33% read female

What gave the bots away

  • Frozen frame10,299
  • Looping video2,303

Addresses per signal. One address can trip several signals, so these do not add up to the total above.

Gender and age are automated estimates from sampled frames, aggregated across everyone. They describe the platform, not any individual, and no per-person record is kept.

Where the map has been corrected

Network blocks members have re-placed by hand, and how many cleared the agreement gate

915
Blocks corrected
636 in the last 30 days
0
Corrections being served
Cleared 5 votes at 60% agreement
320
Members who filed one
58 blocks still contested
  • Poland0 live, 56 contested684
  • Germany0 live, 2 contested121
  • United States0 live, 0 contested22
  • Bulgaria0 live, 0 contested18
  • United Kingdom0 live, 0 contested11
  • Romania0 live, 0 contested10
  • Spain0 live, 0 contested9
  • Latvia0 live, 0 contested5

Unlike everything else on this page, this table is cumulative rather than a rolling 30 days: a correction is a lasting claim about a network block, so it does not expire. A block is only served once it has 5 votes and one place, counting towns within 25 km of it, holds at least 60% of the vote, which is why live is smaller than corrected. Where the two lookup sources disagree by more than 50 km, 3 votes at 70% are enough. A VIP vote counts as one, and a free member can vote from level 15 with a vote worth half. Contested means members disagree and no place has cleared that bar, so nothing is served for it and the panel shows the runners up instead. Countries with fewer than 5 corrections are left out, since there is no consensus to describe yet. Separately, members have filed 4,659 accuracy ratings across 1,271 internet providers (3,041 saying the reading matched, 1,618 saying it did not). Those are not broken down by country on purpose: a rating is about a provider, and a provider does not have one.

The people behind the numbers

Members running OmeUndfnd, who collect everything above

4,389
Joined this window
10,705
Sign-ins
50m
Talk time per active day
Per member, on days they showed up

Questions this report answers

How many people use Ome.tv?

Nobody outside Ome.tv can answer that, and this report does not pretend to. What it counts is encounters: connections that members running the OME.UNDFND overlay were actually matched with, in a rolling 30 day window. That is a large continuous sample of the platform rather than a headcount of it, and every share on this page is a share of that sample.

In the current window: 3,136,252 encounters sampled and 3,746,706 addresses looked up, across 222 countries, by 4,047 active members.

Which countries are most active on Ome.tv?

The country table ranks where the strangers our members met were connecting from, resolved from the connection address. Read it as a picture of who our members get matched with, not as global market share: matching is influenced by where you are yourself, so a country being large here partly reflects where our own userbase sits. Countries with fewer than fifty encounters in the window are left out entirely.

Right now: Poland 58.4%, Germany 15.8%, United States 3.8%.

When is Ome.tv busiest?

Traffic follows a daily curve with a clear night peak and a dead zone in the European morning, and a weekly one on top of it. The hour chart is published in UTC, because a single shared clock is the only way the number means the same thing to every reader, and it can be switched to your own timezone on the page.

Right now the busy window is 19:00 to 01:00 UTC, holding 51.7% of encounters, and Saturday is the busiest day of the week.

How long does a typical Ome.tv conversation last?

Most of them are over before they start. Skipping is the default behaviour on a random video chat, so the distribution is dominated by connections that end within seconds, and the interesting figure is the conditional one: of the conversations that survive the first fifteen seconds, how many make it to a minute. Durations are bucketed into four bands in the browser before anything is sent, so no exact session length is ever stored.

Right now 9.5% get past fifteen seconds, 2.4% past a minute and 0.4% past five.

What is the gender split on Ome.tv?

The split published here is an automated estimate. A model running on the member's own machine reads sampled frames, and only the counts leave the browser. It describes the people our members were matched with, it carries the error rate of any face model, and it is published with its mean confidence rather than as a fact. No per-person record is kept and no image is uploaded.

Right now: 67% read male, 33% read female, at 91% mean confidence, with an average estimated age of 23.

How many people have their camera off?

Camera state is measured per sampled frame rather than per person: a frame is classed as dark, and the share is dark frames against all sampled frames. That covers people with the camera genuinely off as well as unlit rooms and covered lenses, which is why it is reported as frames rather than as users.

Right now 4.0% of sampled frames are dark, and a face is visible on 56.4% of the connections the model analysed.

How many bots are on Ome.tv?

What gets counted is addresses currently carrying a bot signal, not accounts and not people. A signal is raised by the detection network when the video on the other side looks like a recording rather than a live camera: a loop, a frozen frame, overlaid graphics, or the same face appearing from many unrelated addresses. One address can raise several signals, so the per-signal counts deliberately do not add up to the total.

Right now 11,898 addresses carry at least one signal, most often frozen frame.

Is Ome.tv still active?

The 30 day trend on this page is the honest answer to that, and it is republished every half hour. It counts lookups our members ran rather than the platform's own traffic, so treat it as a pulse rather than a user count: it moves with real activity, and the week on week comparison is calculated across complete days only, because the day in progress is always short.

Right now: 120,861 lookups on an average day, up 20% against the week before.

What happens when an Ome.tv IP location is wrong?

Members can correct it, and the correction is what the map is built from. A correction is filed against a network block rather than a single address, because addresses inside a block move between customers and the block does not. Nothing is served on one person saying so: a corrected place has to be agreed on independently by several members, with one place holding a clear majority of their votes, before it replaces what the commercial sources say. Blocks that do not clear that bar are marked contested and the panel shows the competing places with their shares instead of picking one.

To date: 915 blocks corrected by 320 members across 8 countries, of which 0 have cleared 5 votes at 60% agreement and are being served. 58 are still contested.

Can I use these numbers in an article or a video?

Yes, with a link back to this page so a reader can see the method and the window the figures came from. The same snapshot is available as JSON at /api/platform-report if you would rather read it as data. Please quote the window with the number: everything here is a rolling 30 days and it moves.

How these numbers are made

Where it comes from. Members running the OmeUndfnd extension look up the addresses they connect to and, optionally, let an on-device model sample frames of the video. Both arrive here already reduced to counters. The window is a rolling 30 days.

What is never published. Nothing on this page is per-person or per-address. No query behind it selects an account id or an IP, demographics are published only as shares, and any bucket with fewer than fifty observations is dropped rather than rounded: a country, city or network with a handful of encounters is a handful of identifiable evenings, not a statistic.

What the estimates are worth. Gender, age and camera state come from an automated model reading sampled frames; they carry the error rate you would expect of that and are published with their confidence rather than as facts. Bot flags are crowd-sourced signals about video content, not verdicts about people.

Where the shares come from. Every percentage is a share of all encounters in the window, never a share of the rows that happened to be published. That is why the country, city and network tables each add up to less than 100: addresses we cannot place, and buckets under the floor, are counted in the denominator and shown in no row.

The words on this page

Encounter
One connection to one stranger. The same person reached twice is two encounters, and there is no way to tell from this data that it was the same person.
Lookup
A member asking what a connection address resolves to. The product action, and the pulse the trend chart follows.
Share
A percentage of every encounter in the window. Shares are allowed to add up to less than 100: addresses that cannot be placed, or that fall under the publishing floor, are in no bucket at all.
Correction
A member telling us that the city on a network block is wrong, and which one it should be. Filed against the block, never against a person, and a member may file one per block.
Block
A range of neighbouring addresses handled as one unit, since a provider assigns them together and they move between customers as a group. Corrections and consensus are both per block.
Contested
A block where members disagree and no single place holds enough of the vote to be served. Nothing is published for it, and the runners up are shown with their shares instead.
Active member
Someone who spent at least one minute on camera in the window. Not a signup, and not a session.
Talk time
Minutes a member spent on a call with a stranger, summed per member per day. Older windows also counted minutes with the overlay open and nobody on the call.
Signal
A crowd-sourced observation about the video on an address: looping, frozen, overlaid, or one face seen from many addresses. A signal is about content, never a verdict about a person.
Suppressed bucket
A row with fewer than fifty observations. It is dropped rather than published or rounded, which is why a blank here means "too small to publish" and never "zero".

Rebuilt every 3 hours. This snapshot: 2026-11-14, 14:22 UTC.Figures are identical for every visitor. There is no per-viewer slicing behind this page.

Using these numbers

Quote anything here with a link back to this page, so a reader can see the method and the window it came from. The figures move: they are a rolling 30 days, rebuilt every half hour. The same snapshot is available as JSON if you would rather read it as data.

State of OME.TV, OME.UNDFND platform report, snapshot 2026-11-14, 14:22 UTC (rolling 30 day window). https://ome.undfnd.eu/state-of-ometv

Raw snapshot: /api/platform-report returns exactly the figures rendered above, as JSON, with no key and no sign-in.