Updated August 27, 2026
Every Koreatown apartment building this desk has closed — the date, the size, the price and the price per door. Not a selection. The list is generated from the transaction archive each time this page is built, so it cannot drift from what it describes.
21 buildings · 465 units · $80.2M · 2012–2025
| Closed | Building | Units | Price | Per unit |
|---|---|---|---|---|
| 2012-12 | 2858 Leeward Avenue | 30 | $1,739,000 | $57,967 |
| 2014-02 | 811-817 Oxford Ave | 26 | $3,605,000 | $138,654 |
| 2014-06 | 240 S Catalina St | 20 | $1,735,000 | $86,750 |
| 2015-04 | 654 N Normandie Ave | 9 | $1,400,000 | $155,556 |
| 2015-05 | 2960 James M Wood Blvd | 12 | $1,050,000 | $87,500 |
| 2015-06 | 2743 James M Wood Blvd | 8 | $1,100,000 | $137,500 |
| 2015-06 | 1121-1131 Washington Blvd | 20 | $1,675,000 | $83,750 |
| 2015-06 | 744 Beacon Ave | 96 | $8,850,000 | $92,188 |
| 2015-06 | 1136 S Westmoreland Ave | 8 | $1,325,000 | $165,625 |
| 2015-10 | 220 S Commonwealth Ave | 24 | $3,815,000 | $158,958 |
| 2018-02 | 350 S Reno St | 36 | $15,215,000 | $422,639 |
| 2018-06 | 514 S Gramercy Pl | 24 | $6,100,000 | $254,167 |
| 2018-06 | 532 S Gramercy Pl | 24 | $5,600,000 | $233,333 |
| 2018-11 | 2960 James M Wood Blvd | 12 | $1,510,000 | $125,833 |
| 2018-11 | 934 Arapahoe St | 13 | $2,175,000 | $167,308 |
| 2021-01 | 311 S New Hampshire Ave | 16 | $3,600,000 | $225,000 |
| 2022-03 | 827 S Gramercy Dr | 30 | $8,500,000 | $283,333 |
| 2022-04 | 839 S St Andrews Pl | 31 | $6,000,000 | $193,548 |
| 2024-05 | 444 S Manhattan Pl | 12 | $2,530,000 | $210,833 |
| 2025-11 | 204 S Serrano Ave | 4 | $1,240,000 | $310,000 |
| 2025-11 | 944 S Park View St | 10 | $1,400,000 | $140,000 |
It is $158,958 per unit, and it describes almost none of these buildings.
Look at the per-door column. The cheapest and dearest closings in this record are more than seven times apart — a spread wider than any other submarket in the book, inside a neighborhood you can walk across in half an hour. That is not noise. It is what Koreatown actually is, and the reasons are set out in the 7.3× spread inside one submarket.
The buildings are bigger. This record holds a 96-unit building; the largest in the Hollywood record is 75, and West Hollywood's is 22. Larger buildings trade lower per door across this record pooled — what building size actually does to price — and that single 96-unit closing sits at the bottom of the Koreatown range.
It is not the whole explanation, though. Koreatown's own size bands do not descend, and its four-to-ten-unit buildings price near its eleven-to-twenty-five-unit ones. The distribution is low across the board, not just at the large end.
The rent gap is deeper. Koreatown's stock is overwhelmingly pre-1978 and inside the City of Los Angeles, and much of it has been held by the same owners for decades. Long tenancies under a rent cap produce in-place rents well below market — which is simultaneously why the income looks modest and why value-add buyers pay attention.
The years cluster. Seven of these closings happened in a single year. Transaction volume in this submarket is not evenly spread, and a per-door figure from one of the quiet years carries less information than the sample size suggests. The year-by-year view, with the counts visible, is at what a Koreatown door has cost.
2960 James M Wood Blvd appears twice — sold, and then sold again for the next owner three and a half years later at 44% more. That is not a duplicate; it is two separate closings on the same building, and the interval is a real data point. See the building's history.
Two buildings on S Gramercy Place closed on the same day — 514 and 532, both 24 units, at prices 9% apart. That pair is worth its own read: two buildings, one day.
Because a track record a reader cannot inspect is a claim rather than evidence. Every row links to that building's own page, and every figure is computed from the archive rather than typed — the methodology sets out how, and what this record does not contain.
If you own a Koreatown building, the useful question is which of these rows yours most resembles, and why.
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