Photronics (PLAB) Inventory (2010 - 2026)
Photronics' Inventory was $64.75 million in fiscal Q3 2026 (quarter ended Aug 2, 2026), up 2.0% from $63.49 million a year earlier but down 4.5% from the prior quarter.
Photronics (PLAB) Inventory (2010 - 2026) Analysis & Trends
At the end of FY2025 (ended Oct 31, 2025), Inventory at Photronics came in at $61.77 million, up 9.3% from FY2024.
- Inventory shows a five-year compound annual growth rate of 1.5% (FY2020 to FY2025).
- In earlier fiscal years, Inventory was $56.53 million in FY2024 (+13.1%), $49.96 million in FY2023 (-1.6%), $50.75 million in FY2022 (-8.1%) and $55.25 million in FY2021 (-3.5%).
- Quarterly Inventory has moved between $49.96 million (fiscal Q4 2023) and $67.83 million (fiscal Q2 2026) over five years.
- Compared with a year earlier, Inventory has increased for nine straight quarters, with growth averaging 10.6% over the last eight quarters.
- The best year-over-year quarter for Inventory over five years was fiscal Q3 2025 (growth of 14.5%); the worst was fiscal Q1 2023 (a decline of 14.8%).
- Per Business Quant data, PLAB's Inventory in the three fiscal quarters before Q3 2026 was $67.83 million (Q2 2026), $62.65 million (Q1 2026) and $61.77 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Inventory (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,336.80 Bn | 5,110.96 Bn | 72.14 Bn | 31.58 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,231.73 Bn | 1,856.59 Bn | 27.22 Bn | 12.10 Bn |
| 3 | Broadcom | 1,600.76 Bn | 1,526.80 Bn | 20.46 Bn | 4.52 Bn |
| 4 | Micron Technology | 1,026.72 Bn | 932.36 Bn | 47.05 Bn | 10.37 Bn |
| 5 | Advanced Micro Devices | 902.60 Bn | 859.34 Bn | 6.20 Bn | 8.47 Bn |
| 6 | Asml Holding | 648.24 Bn | 603.93 Bn | 5.90 Bn | 13.43 Bn |
| 7 | Intel | 470.34 Bn | 339.47 Bn | 6.51 Bn | 12.49 Bn |
| 8 | Lam Research | 327.33 Bn | 304.13 Bn | 3.48 Bn | 4.28 Bn |
| 9 | Applied Materials | 323.38 Bn | 288.82 Bn | 4.59 Bn | 6.56 Bn |
| 10 | Photronics | 1.68 Bn | -855.25 Mn | 71.73 Mn | 64.75 Mn |
Historic Data
| Date | Value |
|---|---|
| Aug 2, 2026 | 64.75 Mn |
| May 3, 2026 | 67.83 Mn |
| Feb 1, 2026 | 62.65 Mn |
| Oct 31, 2025 | 61.77 Mn |
| Aug 3, 2025 | 63.49 Mn |
| May 4, 2025 | 61.20 Mn |
| Feb 2, 2025 | 57.58 Mn |
| Oct 31, 2024 | 56.53 Mn |
| Jul 28, 2024 | 55.47 Mn |
| Apr 28, 2024 | 54.26 Mn |
| Jan 28, 2024 | 50.68 Mn |
| Oct 31, 2023 | 49.96 Mn |
| Jul 30, 2023 | 55.38 Mn |
| Apr 30, 2023 | 54.94 Mn |
| Jan 29, 2023 | 52.80 Mn |
| Oct 31, 2022 | 50.75 Mn |
| Jul 31, 2022 | 50.31 Mn |
| May 1, 2022 | 57.94 Mn |
| Jan 30, 2022 | 61.97 Mn |
| Oct 31, 2021 | 55.25 Mn |
Photronics Inventory 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=inventory&ticker=PLAB&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "inventory", "ticker": "PLAB", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=inventory&ticker=PLAB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();