Vishay Precision (VPG) Cost of Revenue (2010 - 2026)
Vishay Precision (VPG) recorded Cost of Revenue of $51.5 million in Q2 2026, up 15.5% from $44.57 million a year earlier and unchanged from the prior quarter.
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Analysis
Vishay Precision (VPG) Cost of Revenue (2010 - 2026) Analysis & Trends
On a TTM basis, Vishay Precision's Cost of Revenue came in at $201.49 million as of Jul 4, 2026, up 12.2% year-over-year; for FY2025, it came in at $187.77 million, up 3.7% from FY2024.
- Annual Cost of Revenue has a five-year compound annual growth rate of 2.6% (FY2020 to FY2025).
- Across earlier years, Cost of Revenue came in at $180.99 million in FY2024 (-11.6%), $204.71 million in FY2023 (-3.9%), $212.98 million in FY2022 (+10.5%) and $192.78 million in FY2021 (+16.5%).
- The Q2 2026 figure is the highest quarterly Cost of Revenue since Q2 2023.
- On a year-over-year basis, Cost of Revenue has increased for four consecutive quarters, with growth averaging 3.1% over the last eight quarters.
- Peak year-over-year performance for Cost of Revenue in the last five years was growth of 24.9% in Q1 2022, against a decline of 13.7% in Q2 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $51.48 million (Q1 2026), $50.91 million (Q4 2025) and $47.6 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cost of Rev (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 388.70 Bn | 360.40 Bn | 7.76 Bn | 12.78 Bn |
| 2 | Amphenol | 214.42 Bn | 209.12 Bn | 3.55 Bn | 5.21 Bn |
| 3 | Deere | 185.30 Bn | 194.07 Bn | 4.66 Bn | 7.95 Bn |
| 4 | Eaton | 169.35 Bn | 166.59 Bn | 2.86 Bn | 5.68 Bn |
| 5 | Parker-Hannifin | 122.64 Bn | 120.77 Bn | 2.25 Bn | 3.51 Bn |
| 6 | Vertiv Holdings | 97.12 Bn | 87.74 Bn | 1.23 Bn | 2.04 Bn |
| 7 | Emerson Electric | 90.13 Bn | 82.89 Bn | 2.66 Bn | 2.22 Bn |
| 8 | 3M | 83.49 Bn | 64.94 Bn | 2.68 Bn | 3.82 Bn |
| 9 | Illinois Tool Works | 74.89 Bn | 71.45 Bn | 1.90 Bn | 2.40 Bn |
| 10 | Vishay Precision | 2.03 Bn | 1.69 Bn | 32.44 Mn | 51.50 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 4, 2026 | 51.50 Mn |
| Apr 4, 2026 | 51.48 Mn |
| Dec 31, 2025 | 50.91 Mn |
| Sep 27, 2025 | 47.60 Mn |
| Jun 28, 2025 | 44.57 Mn |
| Mar 29, 2025 | 44.70 Mn |
| Dec 31, 2024 | 44.88 Mn |
| Sep 28, 2024 | 45.47 Mn |
| Jun 29, 2024 | 44.95 Mn |
| Mar 30, 2024 | 45.69 Mn |
| Dec 31, 2023 | 51.03 Mn |
| Sep 30, 2023 | 49.92 Mn |
| Jul 1, 2023 | 52.09 Mn |
| Apr 1, 2023 | 51.67 Mn |
| Dec 31, 2022 | 56.54 Mn |
| Oct 1, 2022 | 52.74 Mn |
| Jul 2, 2022 | 51.28 Mn |
| Apr 2, 2022 | 52.42 Mn |
| Dec 31, 2021 | 55.14 Mn |
| Oct 2, 2021 | 50.13 Mn |
API Access
Vishay Precision Cost of Revenue 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=cost-of-revenue&ticker=VPG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cost-of-revenue", "ticker": "VPG", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=cost-of-revenue&ticker=VPG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();