Solid Power (SLDP) Operating Expenses (2021 - 2026)
Solid Power (SLDP) recorded Operating Expenses of $30.02 million in Q2 2026, down 10.1% from $33.41 million a year earlier but up 2.0% from the prior quarter.
Solid Power (SLDP) Operating Expenses (2021 - 2026) Analysis & Trends
On a TTM basis, Solid Power's Operating Expenses came in at $118.56 million as of Jun 30, 2026, down 5.3% year-over-year; for FY2025, it came in at $122.58 million, down 2.3% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 55.0% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $125.47 million in FY2024 (+16.1%), $108.03 million in FY2023 (+52.4%), $70.91 million in FY2022 (+142.4%) and $29.26 million in FY2021 (+113.6%).
- Quarterly Operating Expenses has ranged from $8.77 million in Q4 2021 to $33.41 million in Q2 2025 over the past five years.
- On a year-over-year basis, Operating Expenses rose in four of the last eight quarters, with an average year-over-year change of 0.0%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 183.0% in Q1 2022, against a decline of 10.1% in Q2 2026 at the low end.
- Per Business Quant, the preceding three quarters came in at $29.42 million (Q1 2026), $30.14 million (Q4 2025) and $28.98 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Rio Tinto | 182.38 Bn | 151.41 Bn | - | - |
| 2 | Southern Copper | 162.27 Bn | 141.06 Bn | 2.90 Bn | 1.67 Bn |
| 3 | Rio Tinto | 141.19 Bn | 101.69 Bn | - | - |
| 4 | Newmont | 123.87 Bn | 91.88 Bn | 4.03 Bn | 3.02 Bn |
| 5 | Freeport-Mcmoran | 98.50 Bn | 82.54 Bn | 2.19 Bn | 5.03 Bn |
| 6 | Agnico Eagle Mines | 93.51 Bn | 83.14 Bn | 2.43 Bn | 119.48 Mn |
| 7 | Barrick Mining | 69.21 Bn | 44.41 Bn | 2.90 Bn | 165.00 Mn |
| 8 | Nucor | 60.14 Bn | 49.52 Bn | 2.03 Bn | 405.00 Mn |
| 9 | ArcelorMittal | 48.56 Bn | 27.59 Bn | - | -780.00 Mn |
| 10 | Solid Power | 486.98 Mn | -512.87 Mn | -1.85 Mn | 30.02 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 30.02 Mn |
| Mar 31, 2026 | 29.42 Mn |
| Dec 31, 2025 | 30.14 Mn |
| Sep 30, 2025 | 28.98 Mn |
| Jun 30, 2025 | 33.41 Mn |
| Mar 31, 2025 | 30.05 Mn |
| Dec 31, 2024 | 29.48 Mn |
| Sep 30, 2024 | 32.24 Mn |
| Jun 30, 2024 | 32.01 Mn |
| Mar 31, 2024 | 31.73 Mn |
| Dec 31, 2023 | 27.98 Mn |
| Sep 30, 2023 | 27.86 Mn |
| Jun 30, 2023 | 27.08 Mn |
| Mar 31, 2023 | 25.11 Mn |
| Dec 31, 2022 | 21.71 Mn |
| Sep 30, 2022 | 18.41 Mn |
| Jun 30, 2022 | 17.28 Mn |
| Mar 31, 2022 | 13.51 Mn |
| Dec 31, 2021 | 8.77 Mn |
| Sep 30, 2021 | 9.11 Mn |
Solid Power Operating 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=operating-expenses&ticker=SLDP&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SLDP", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=SLDP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();