Applied Optoelectronics (AAOI) Inventory (2012 - 2026)
Applied Optoelectronics (AAOI) recorded Inventory of $278.79 million in Q2 2026, up 100.8% from $138.87 million a year earlier and up 35.2% from the prior quarter.
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Analysis
Applied Optoelectronics (AAOI) Inventory (2012 - 2026) Analysis & Trends
At the end of FY2025, Applied Optoelectronics reported Inventory of $183.11 million, up 107.8% from FY2024.
- Annual Inventory has a five-year compound annual growth rate of 10.6% (FY2020 to FY2025).
- Across earlier years, Inventory came in at $88.14 million in FY2024 (+38.0%), $63.87 million in FY2023 (-19.8%), $79.68 million in FY2022 (-13.9%) and $92.52 million in FY2021 (-16.2%).
- The Q2 2026 figure is the highest quarterly Inventory in data going back to Q4 2012.
- On a year-over-year basis, Inventory has increased for seven consecutive quarters, with growth averaging 94.0% over the last eight quarters.
- Peak year-over-year performance for Inventory in the last five years was growth of 164.4% in Q3 2025, against a decline of 32.5% in Q2 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $206.25 million (Q1 2026), $183.11 million (Q4 2025) and $170.21 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Inventory (Qtr) |
|---|---|---|---|---|---|
| 1 | Apple | 5,040.97 Bn | 4,788.46 Bn | 54.77 Bn | 11.09 Bn |
| 2 | Cisco Systems | 424.45 Bn | 360.38 Bn | 11.06 Bn | 5.69 Bn |
| 3 | Dell Technologies | 313.76 Bn | 269.51 Bn | 9.83 Bn | 21.29 Bn |
| 4 | Arista Networks | 232.68 Bn | 186.14 Bn | 1.91 Bn | 2.54 Bn |
| 5 | Sandisk | 202.67 Bn | 191.19 Bn | 7.58 Bn | 2.70 Bn |
| 6 | Seagate Technology Holdings | 152.82 Bn | 147.82 Bn | 1.90 Bn | 1.57 Bn |
| 7 | Sony | 149.85 Bn | 87.11 Bn | 6.53 Bn | 8.43 Bn |
| 8 | Western Digital | 130.59 Bn | 118.72 Bn | 2.03 Bn | 1.51 Bn |
| 9 | Hewlett Packard Enterprise | 77.78 Bn | 55.65 Bn | 4.93 Bn | 11.82 Bn |
| 10 | Applied Optoelectronics | 6.32 Bn | 5.04 Bn | 53.21 Mn | 278.79 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 278.79 Mn |
| Mar 31, 2026 | 206.25 Mn |
| Dec 31, 2025 | 183.11 Mn |
| Sep 30, 2025 | 170.21 Mn |
| Jun 30, 2025 | 138.87 Mn |
| Mar 31, 2025 | 102.31 Mn |
| Dec 31, 2024 | 88.14 Mn |
| Sep 30, 2024 | 64.38 Mn |
| Jun 30, 2024 | 54.32 Mn |
| Mar 31, 2024 | 54.32 Mn |
| Dec 31, 2023 | 63.87 Mn |
| Sep 30, 2023 | 67.53 Mn |
| Jun 30, 2023 | 66.32 Mn |
| Mar 31, 2023 | 70.19 Mn |
| Dec 31, 2022 | 79.68 Mn |
| Sep 30, 2022 | 94.26 Mn |
| Jun 30, 2022 | 98.18 Mn |
| Mar 31, 2022 | 92.01 Mn |
| Dec 31, 2021 | 92.52 Mn |
| Sep 30, 2021 | 94.51 Mn |
API Access
Applied Optoelectronics 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=AAOI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "inventory", "ticker": "AAOI", "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=AAOI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();