Best Condos Under 1 Million Singapore: 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 — Best Condos Under 1 Million Singapore — is the practical way to narrow the search from impossible to tractable. The category lens (budget-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 condominiums have recorded transactions below $1 million, making them accessible entry points for first-time buyers and budget-conscious investors in Singapore.
- TREASURES @ G20 averages $558,000 per transaction — well under $1M.
- Sub-$1M condos are accessible to first-time buyers with a single income.
- Budget entry points often mean smaller units or older developments in OCR districts.
Rankings
| # | Name | District | Avg Price | Avg PSF | Txns |
|---|---|---|---|---|---|
| 1 | TREASURES @ G20 | D14 | $558,000 | $1,225 psf | 13 |
| 2 | GLASGOW RESIDENCE | D19 | $585,000 | $1,398 psf | 9 |
| 3 | EDENZ LOFT | D14 | $602,333 | $1,403 psf | 9 |
| 4 | PRESTIGE LOFT | D15 | $603,250 | $1,614 psf | 4 |
| 5 | TREASURES@G19 | D14 | $609,800 | $1,475 psf | 5 |
| 6 | PAVILION SQUARE | D14 | $611,947 | $1,476 psf | 19 |
| 7 | LA FLEUR | D14 | $617,917 | $1,438 psf | 12 |
| 8 | SUITES@BRADDELL | D13 | $618,913 | $1,471 psf | 7 |
| 9 | THE HILLFORD | D21 | $621,096 | $1,359 psf | 98 |
| 10 | LANDED HOUSING DEVELOPMENT | D5 | $623,495 | $218 psf | 42 |
| 11 | THE EBONY | D14 | $631,833 | $1,611 psf | 6 |
| 12 | OCEAN FRONT SUITES | D17 | $633,771 | $1,461 psf | 14 |
| 13 | PRIME RESIDENCE | D14 | $634,597 | $1,420 psf | 8 |
| 14 | THE COTZ | D15 | $638,214 | $1,507 psf | 14 |
| 15 | SUITES@CHANGI | D14 | $638,667 | $1,497 psf | 12 |
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Top 3 Highlights
Evaluating the Best Condos Under 1 Million Singapore 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 — absolute price ceiling matters most. Below $1M in Singapore typically means OCR or shoebox units. Below $500K is increasingly limited to shoebox studio or older 99-year leasehold in fringe districts.
- 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 Best Condos Under 1 Million Singapore 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 budget-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
Can I find a good condo in Singapore for under $1 million?
What should I look out for with sub-$1M condos?
Are sub-$1M condos suitable for investment?
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.