Top Developers Total Units: a spotlight on Singapore condos meeting this specific criterion. Use this lens to filter the broader market down to a manageable shortlist matched to your specific buyer profile and priority weighting. The category is best understood through transacted-data verification rather than asking-price snapshots (as of 2026-Q1).
Singapore’s private residential market spans approximately 3,500 condo projects across 28 districts. Filtering to a specific spotlight category — Top Developers Total Units — is the practical way to narrow the search from impossible to tractable. The category lens (scale-focused) matches buyers whose priorities align with the spotlight criterion.
The dataset to read is the URA Property Data portal for verified transacted caveats, supplemented by ShiokNest’s per-project aggregations covering price, rental, walkability, en-bloc, and investment scores. The price heatmap visualises district-level concentration; the comparison tool lets you place candidates side-by-side.
The cost-of-entry context applies to every category: SORA-pegged mortgages at ~4% effective via the MAS SORA dashboard, BSD progressive 1%–6%, ABSD by buyer profile per the IRAS ABSD schedule. The category lens doesn’t change the tax or financing framework — it changes which projects are in the shortlist.
Overview
These developers have the largest portfolio of residential units tracked on ShiokNest.
- CITY DEVELOPMENTS LTD leads with 8,180 total units across its portfolio.
- Top developers often have stronger track records for build quality and after-sales service.
- Developer reputation can influence resale value and buyer confidence.
Rankings
| # | Name | Projects | Total Units | Segments |
|---|---|---|---|---|
| 1 | CITY DEVELOPMENTS LTD | 38 | 8,180 | CCR,OCR,RCR |
| 2 | HONG REALTY (PRIVATE) LIMITED | 5 | 6,789 | CCR,OCR |
| 3 | CITY DEVELOPMENTS LIMITED | 12 | 3,687 | CCR,OCR,RCR |
| 4 | FAR EAST ORGANIZATION | 19 | 3,091 | CCR,OCR,RCR |
| 5 | Tripartite Developers Pte Ltd | 7 | 2,766 | OCR |
| 6 | FCL PEAK PTE LTD | 3 | 2,686 | OCR |
| 7 | Sim Lian (Treasure) Pte Ltd | 1 | 2,203 | OCR |
| 8 | GOODLAND HOMES PTE LTD | 2 | 2,021 | OCR |
| 9 | KEPPEL LAND | 3 | 2,012 | OCR,RCR |
| 10 | MCC LAND (SINGAPORE) PTE LTD | 4 | 1,988 | OCR |
Top 3 Highlights
Evaluating the Top Developers Total Units category requires the following framework:
- Verified transacted data — asking prices and developer marketing materials are not the authoritative source. Pull recent caveats from URA REALIS for the projects you shortlist.
- Category-specific KPIs — project-specific attributes per the theme — verify each via URA caveats and ShiokNest project data.
- Tenure and lease-decay considerations — freehold projects avoid the 30-year financing minimum and 60-year CPF cap path entirely. 99-year leasehold faces these constraints as the building ages.
- Capital-appreciation trajectory — cross-reference each candidate against URA Property Price Index sub-segment performance over 3–5 years to identify outperformers and underperformers within the category.
For the Top Developers Total Units shortlist specifically, the buyer should run each candidate through three lenses: (a) cost via the BSD/ABSD calculator, (b) financing via the mortgage calculator at the relevant SORA-linked rate, and (c) yield via the buy-to-rent ROI calculator. The composite output is a cost-and-return picture across the shortlist.
The macro context matters even at the spotlight-category level. The current 60% foreigner ABSD plus 20% SC second-property ABSD constrains demand particularly in CCR luxury and shoebox investor stock; OCR upgrader categories and 3-bedroom family stock face less demand-side pressure. Category-level analysis should therefore consider not just the project attributes but also the buyer cohort dominating recent transactions in that segment. Use the URA segment data for cohort context.
Forward-looking dimensions: GLS-driven new-launch supply, en-bloc activity in surrounding plots, and MRT-line extensions can change the spotlight-category landscape over time. The URA GLS schedule and the LTA Land Transport Master Plan are the canonical forward references.
- First-time SC buyer: Use the spotlight category as a starting filter but verify each candidate against the standard buyer framework (BSD/ABSD, TDSR, MRT, school). The 0% ABSD on first SC purchase is your biggest advantage; deploy CPF strategically via the CPF optimizer.
- HDB upgrader: For scale-focused priorities, balance the category criterion against the upgrade-path requirement (typically 3-bedroom family stock in RCR/OCR). Some spotlight categories may include units outside your typical search range.
- Investor (yield focus): If the category is yield-aligned, the shortlist is your target pool. If not yield-aligned, verify each candidate’s gross yield separately via URA rental caveats before treating it as investor-grade.
- Investor (capital appreciation focus): Cross-reference shortlist candidates against 3–5 year transacted-price trajectory. The category criterion alone doesn’t guarantee appreciation; tenure, district trajectory, and en-bloc potential are independent factors.
- Foreign buyer (60% ABSD): At 60% ABSD, only categories with strong long-horizon owner-occupier or trophy-asset positioning justify the entry. Yield-focused categories rarely work for foreign buyers under current cooling measures. Verify FTA-eligibility (US / Swiss / Liechtenstein / Norway / Iceland) before assuming the standard rate applies.
- Verify each candidate via the URA Property Data portal for transacted caveats.
- Use the ShiokNest comparison tool to place 2–3 candidates side-by-side on price, PSF, yield, walkability, and en-bloc scores.
- Calculate upfront cost via the BSD/ABSD stamp duty calculator for each candidate at your buyer profile.
- Stress-test affordability via the mortgage calculator and the TDSR/MSR affordability calculator.
- For investor analysis, run the buy-to-rent ROI calculator at current SORA-linked rates.
- Cross-reference district-level concentration via the price heatmap and the district comparison calculator.
Bull case for the spotlight category: The category lens identifies a high-conviction shortlist matched to specific buyer priorities — far more efficient than browsing the entire market. Concentration within a verified category often produces better outcomes than breadth across mediocre matches.
Bear case for over-narrowing: Filtering too aggressively risks missing units that meet the spirit (but not exactly the letter) of the category criterion. A unit that’s 550m from MRT but offers better view and tenure may outperform a 480m unit on overall buyer value. Use the category as a starting filter, not a final gate.
Frequently Asked Questions
Does the developer matter when buying a condo?
Who are the largest condo developers in Singapore?
Do top developers charge more?
How current is the data?
URA caveats lodge with a typical 4–6 week reporting lag from transaction date. The shortlist reflects the most recent quarter or two of verified transactions. Rental caveats carry a longer 1–2 quarter lag. For real-time market context, cross-reference active listings on 99.co or PropertyGuru, but treat those as asking, not transacted, prices.
Should I prioritise yield or capital appreciation for this category?
The honest answer depends on holding horizon and tax position. Yield-focused investors typically prefer smaller units in well-connected RCR/OCR; capital-appreciation-focused investors typically prefer larger units in freehold prime CCR/RCR. Run both scenarios through the buy-to-rent ROI calculator with realistic exit-price assumptions.
Methodology & Sources
Figures below are drawn from all available transaction periods and revised on demand.
Transaction data sourced from URA.
- Rankings require a minimum number of transactions to qualify.
- Averages are used for price and PSF metrics; yields are estimated from average rent and average sale price.
- Last updated: 18 Jul 2026.
We report medians (not means) so a single outlier transaction cannot skew district-level figures. PSF = price per square foot.