GDS Holdings (GDS) Accumulated Expenses (2015 - 2026)
GDS Holdings (GDS) reported Accumulated Expenses of $214.71 million for the quarter ended Jun 30, 2026, up 3.8% from $206.76 million a year earlier and up 18.6% from the prior quarter.
GDS Holdings (GDS) Accumulated Expenses (2015 - 2026) Analysis & Trends
As of Dec 31, 2025, GDS Holdings posted Accumulated Expenses of $205.51 million, up 8.0% from the prior year.
- Accumulated Expenses has increased for three consecutive years, though with a five-year compound annual growth rate of -2.1% (years ended Dec 2020 to Dec 2025).
- By year, Accumulated Expenses came in at $190.3 million in the year ended Dec 31, 2024 (+2.5%), $185.68 million in the year ended Dec 31, 2023 (+9.2%), $170.08 million in the year ended Dec 31, 2022 (-60.9%) and $434.76 million in the year ended Dec 31, 2021 (+90.1%).
- Five-year quarterly Accumulated Expenses spans a low of $168.51 million in the quarter ended Dec 31, 2022 and a high of $419.11 million in the quarter ended Dec 31, 2021.
- Year over year, Accumulated Expenses gained in five of the last eight quarters, with growth averaging 6.3%.
- The high point for year-over-year Accumulated Expenses in five years was the quarter ended Dec 31, 2021 (growth of 99.0%); the low point was the quarter ended Dec 31, 2022 (a decline of 59.8%).
- Per Business Quant data, the three quarters before the quarter ended Jun 30, 2026 came in at $181 million (quarter ended Mar 31, 2026), $202.63 million (quarter ended Dec 31, 2025) and $216.87 million (quarter ended Sep 30, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Microsoft | 3,896.21 Bn | 3,819.37 Bn | 60.48 Bn |
| 2 | International Business Machines | 229.69 Bn | 180.50 Bn | 9.91 Bn |
| 3 | Cloudflare | 111.07 Bn | 94.60 Bn | 499.52 Mn |
| 4 | Equinix | 94.03 Bn | 82.59 Bn | 1.40 Bn |
| 5 | Nebius | 39.19 Bn | 12.62 Bn | 448.70 Mn |
| 6 | CoreWeave | 32.35 Bn | 19.44 Bn | 1.70 Bn |
| 7 | Verisign | 28.07 Bn | 25.28 Bn | 384.60 Mn |
| 8 | Nutanix | 18.63 Bn | 10.32 Bn | 651.35 Mn |
| 9 | GoDaddy | 14.53 Bn | 10.11 Bn | 828.20 Mn |
| 10 | GDS Holdings | 4.30 Bn | -3.97 Bn | 97.55 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 214.45 Mn |
| Mar 31, 2026 | 180.64 Mn |
| Dec 31, 2025 | 172.30 Mn |
| Sep 30, 2025 | 216.86 Mn |
| Jun 30, 2025 | 436.68 Mn |
| Mar 31, 2025 | 193.63 Mn |
| Dec 31, 2024 | 176.57 Mn |
| Sep 30, 2024 | 218.71 Mn |
| Jun 30, 2024 | 193.73 Mn |
| Mar 31, 2024 | 179.61 Mn |
| Dec 31, 2023 | 161.16 Mn |
| Sep 30, 2023 | 174.17 Mn |
| Jun 30, 2023 | 176.15 Mn |
| Mar 31, 2023 | 202.37 Mn |
| Dec 31, 2022 | 146.05 Mn |
| Sep 30, 2022 | 251.51 Mn |
| Jun 30, 2022 | 333.48 Mn |
| Mar 31, 2022 | 395.27 Mn |
| Dec 31, 2021 | 420.51 Mn |
| Sep 30, 2021 | 306.95 Mn |
GDS Holdings Accumulated 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=accumulated-expenses&ticker=GDS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-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=accumulated-expenses&ticker=GDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();