Rigetti Computing (RGTI) Total Liabilities (2020 - 2026)
Rigetti Computing (RGTI) reported Total Liabilities of $110.8 million for Q2 2026, up 32.8% from $83.43 million a year earlier and up 65.2% from the prior quarter.
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Analysis
Rigetti Computing (RGTI) Total Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Rigetti Computing posted Total Liabilities of $120.38 million, down 23.9% from FY2024.
- Total Liabilities has a five-year compound annual growth rate of 30.1% (FY2020 to FY2025).
- By year, Total Liabilities came in at $158.2 million in FY2024 (+214.4%), $50.33 million in FY2023 (-5.4%), $53.22 million in FY2022 (-54.9%) and $117.96 million in FY2021 (+265.2%).
- Five-year quarterly Total Liabilities spans a low of $34.41 million in Q3 2024 and a high of $404.22 million in Q3 2021.
- Year over year, Total Liabilities gained in six of the last eight quarters, with growth averaging 123.6%.
- The high point for year-over-year Total Liabilities in five years was Q3 2025 (growth of 651.0%); the low point was Q3 2022 (a decline of 88.4%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $67.09 million (Q1 2026), $120.38 million (Q4 2025) and $258.45 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 260.12 Bn | 245.19 Bn | 2.30 Bn | 20.97 Bn |
| 2 | CrowdStrike Holdings | 232.49 Bn | 212.89 Bn | 1.10 Bn | 6.89 Bn |
| 3 | Fortinet | 125.70 Bn | 111.63 Bn | 1.64 Bn | 9.31 Bn |
| 4 | Snowflake | 110.19 Bn | 97.50 Bn | 1.04 Bn | 6.54 Bn |
| 5 | Datadog | 92.71 Bn | 74.35 Bn | 881.34 Mn | 3.18 Bn |
| 6 | Zscaler | 34.07 Bn | 20.19 Bn | - | 5.27 Bn |
| 7 | Okta | 33.06 Bn | 23.16 Bn | 641.00 Mn | 2.17 Bn |
| 8 | Axon Enterprise | 30.90 Bn | 25.43 Bn | 546.45 Mn | 3.81 Bn |
| 9 | MongoDB | 28.04 Bn | 18.51 Bn | 569.77 Mn | 797.71 Mn |
| 10 | Rigetti Computing | 3.89 Bn | 2.19 Bn | 2.19 Mn | 110.80 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 110.80 Mn |
| Mar 31, 2026 | 67.09 Mn |
| Dec 31, 2025 | 120.38 Mn |
| Sep 30, 2025 | 258.45 Mn |
| Jun 30, 2025 | 83.43 Mn |
| Mar 31, 2025 | 62.01 Mn |
| Dec 31, 2024 | 158.20 Mn |
| Sep 30, 2024 | 34.41 Mn |
| Jun 30, 2024 | 40.25 Mn |
| Mar 31, 2024 | 46.54 Mn |
| Dec 31, 2023 | 50.33 Mn |
| Sep 30, 2023 | 52.51 Mn |
| Jun 30, 2023 | 49.21 Mn |
| Mar 31, 2023 | 52.44 Mn |
| Dec 31, 2022 | 53.22 Mn |
| Sep 30, 2022 | 46.78 Mn |
| Jun 30, 2022 | 58.49 Mn |
| Mar 31, 2022 | 81.92 Mn |
| Dec 31, 2021 | 117.96 Mn |
| Sep 30, 2021 | 404.22 Mn |
API Access
Rigetti Computing Total Liabilities 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=total-liabilities&ticker=RGTI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "RGTI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=total-liabilities&ticker=RGTI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();