GDS Holdings (GDS) Operating Expenses (2015 - 2026)
GDS Holdings (GDS) reported Operating Expenses of -$28.32 million for the quarter ended Jun 30, 2026, compared with -$33.55 million a year earlier.
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Analysis
GDS Holdings (GDS) Operating Expenses (2015 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, GDS Holdings' Operating Expenses came in at -$118.23 million; for the year ended Dec 31, 2025, it came in at $367.53 million, up 146.7% from the prior year.
- Operating Expenses has a five-year compound annual growth rate of 26.4% (years ended Dec 2020 to Dec 2025).
- By year, Operating Expenses came in at $149 million in the year ended Dec 31, 2024 (-74.2%), $577.56 million in the year ended Dec 31, 2023 (+231.7%), $174.1 million in the year ended Dec 31, 2022 and -$166.54 million in the year ended Dec 31, 2021.
- Five-year quarterly Operating Expenses spans a low of -$48.82 million in the quarter ended Mar 31, 2022 and a high of -$27.11 million in the quarter ended Mar 31, 2026.
- Per Business Quant data, the three quarters before the quarter ended Jun 30, 2026 came in at -$27.11 million (quarter ended Mar 31, 2026), -$29.57 million (quarter ended Dec 31, 2025) and -$33.24 million (quarter ended Sep 30, 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Microsoft | 3,964.86 Bn | 3,888.01 Bn | 60.48 Bn | 12.28 Bn |
| 2 | International Business Machines | 222.38 Bn | 173.19 Bn | 9.91 Bn | 7.29 Bn |
| 3 | Cloudflare | 105.62 Bn | 89.15 Bn | 499.52 Mn | 705.21 Mn |
| 4 | Equinix | 96.25 Bn | 84.81 Bn | 1.40 Bn | 1.96 Bn |
| 5 | Nebius | 41.41 Bn | 14.84 Bn | 448.70 Mn | 758.20 Mn |
| 6 | CoreWeave | 33.73 Bn | 20.82 Bn | 1.70 Bn | 2.62 Bn |
| 7 | Verisign | 27.82 Bn | 25.04 Bn | 384.60 Mn | 138.30 Mn |
| 8 | Nutanix | 18.15 Bn | 9.84 Bn | 651.35 Mn | 581.36 Mn |
| 9 | GoDaddy | 13.94 Bn | 9.52 Bn | 828.20 Mn | 955.50 Mn |
| 10 | GDS Holdings | 4.27 Bn | -4.01 Bn | 97.55 Mn | -28.32 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -28.32 Mn |
| Mar 31, 2026 | -27.00 Mn |
| Dec 31, 2025 | -29.15 Mn |
| Sep 30, 2025 | -33.06 Mn |
| Jun 30, 2025 | -33.23 Mn |
| Mar 31, 2025 | -33.95 Mn |
| Dec 31, 2024 | -37.02 Mn |
| Sep 30, 2024 | -30.69 Mn |
| Jun 30, 2024 | -29.82 Mn |
| Mar 31, 2024 | -35.31 Mn |
| Dec 31, 2023 | -35.98 Mn |
| Sep 30, 2023 | -45.33 Mn |
| Jun 30, 2023 | -39.20 Mn |
| Mar 31, 2023 | -43.75 Mn |
| Dec 31, 2022 | -43.03 Mn |
| Sep 30, 2022 | -45.15 Mn |
| Jun 30, 2022 | -44.97 Mn |
| Mar 31, 2022 | -48.76 Mn |
| Dec 31, 2021 | -45.85 Mn |
| Sep 30, 2021 | -41.93 Mn |
API Access
GDS Holdings Operating Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=operating-expenses&ticker=GDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GDS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=GDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();