Globalfoundries (GFS) Return on Sales [ROS] (2020 - 2026)
Globalfoundries' Return on Sales [ROS] was 12.11% in Q3 2026, up 0.56 percentage points from 11.55% a year earlier and up 2.37 percentage points from the prior quarter.
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Analysis
Globalfoundries (GFS) Return on Sales [ROS] (2020 - 2026) Analysis & Trends
On a trailing twelve-month basis, Globalfoundries' Return on Sales [ROS] was 11.74% through Sep 30, 2026, up 14.08 percentage points year-over-year; for FY2025, it came in at 11.74%, up 14.91 percentage points from FY2024.
- Return on Sales [ROS] shows a five-year change of +45.87 percentage points (FY2020 to FY2025).
- In earlier years, Return on Sales [ROS] was -3.17% in FY2024 (-18.44 pp), 15.27% in FY2023 (+0.88 pp), 14.39% in FY2022 (+15.30 pp) and -0.91% in FY2021 (+33.23 pp).
- Quarterly Return on Sales [ROS] has moved between -38.31% (Q4 2024) and 17.21% (Q3 2022) over five years.
- Compared with a year earlier, Return on Sales [ROS] was higher in six of the last eight quarters, with an average year-over-year change of +0.10 percentage points.
- The best year-over-year quarter for Return on Sales [ROS] over five years was Q4 2025 (a gain of 52.24 percentage points); the worst was Q4 2024 (a drop of 54.65 percentage points).
- Per Business Quant data, GFS's Return on Sales [ROS] in the three quarters before Q3 2026 was 9.74% (Q2 2026), 11.02% (Q1 2026) and 13.93% (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 4,516.52 Bn | 4,290.68 Bn | 72.14 Bn | 66.24% |
| 2 | Taiwan Semiconductor Manufacturing | 1,945.01 Bn | 1,569.87 Bn | 27.22 Bn | 60.34% |
| 3 | Broadcom | 1,397.97 Bn | 1,324.02 Bn | 20.46 Bn | 53.92% |
| 4 | Micron Technology | 778.23 Bn | 683.86 Bn | 47.05 Bn | 80.68% |
| 5 | Advanced Micro Devices | 731.93 Bn | 680.14 Bn | 7.21 Bn | 21.17% |
| 6 | Asml Holding | 553.38 Bn | 509.07 Bn | 5.90 Bn | - |
| 7 | Intel | 294.27 Bn | 140.33 Bn | 7.10 Bn | 15.27% |
| 8 | Applied Materials | 264.14 Bn | 229.58 Bn | 4.59 Bn | 33.74% |
| 9 | Texas Instruments | 253.31 Bn | 228.18 Bn | 3.89 Bn | 47.46% |
| 10 | Globalfoundries | 21.46 Bn | 10.79 Bn | 571.00 Mn | 12.11% |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 12.11% |
| Jun 30, 2026 | 9.74% |
| Mar 31, 2026 | 11.02% |
| Dec 31, 2025 | 13.93% |
| Sep 30, 2025 | 11.55% |
| Jun 30, 2025 | 11.61% |
| Mar 31, 2025 | 9.53% |
| Dec 31, 2024 | -38.31% |
| Sep 30, 2024 | 10.64% |
| Jun 30, 2024 | 9.50% |
| Mar 31, 2024 | 9.49% |
| Dec 31, 2023 | 16.34% |
| Sep 30, 2023 | 14.09% |
| Jun 30, 2023 | 14.91% |
| Mar 31, 2023 | 15.75% |
| Dec 31, 2022 | 13.71% |
| Sep 30, 2022 | 17.21% |
| Jun 30, 2022 | 14.90% |
| Mar 31, 2022 | 11.60% |
| Dec 31, 2021 | 4.66% |
API Access
Globalfoundries Return on Sales [ROS] 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=return-on-sales-%5Bros%5D&ticker=GFS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "GFS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=return-on-sales-%5Bros%5D&ticker=GFS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();