Rigetti Computing (RGTI) Total Current Liabilities (2020 - 2026)
Rigetti Computing (RGTI) reported Total Current Liabilities of $105.06 million for Q2 2026, up 907.3% from $10.43 million a year earlier and up 69.8% from the prior quarter.
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Analysis
Rigetti Computing (RGTI) Total Current Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Rigetti Computing posted Total Current Liabilities of $12.15 million, up 2.4% from FY2024.
- Total Current Liabilities has a five-year compound annual growth rate of 226.0% (FY2020 to FY2025).
- By year, Total Current Liabilities came in at $11.87 million in FY2024 (-59.2%), $29.05 million in FY2023 (+33.6%), $21.75 million in FY2022 (+187.5%) and $7.57 million in FY2021.
- The Q2 2026 figure ranks as the highest quarterly Total Current Liabilities in data going back to Q4 2020.
- Year over year, Total Current Liabilities has now increased in each of the last three quarters, with growth averaging 141.0% over the last eight quarters.
- The high point for year-over-year Total Current Liabilities in five years was Q2 2026 (growth of 907.3%); the low point was Q2 2025 (a decline of 59.2%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $61.88 million (Q1 2026), $12.15 million (Q4 2025) and $11.63 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 260.12 Bn | 245.19 Bn | 2.30 Bn | 9.92 Bn |
| 2 | CrowdStrike Holdings | 232.49 Bn | 212.89 Bn | 1.10 Bn | 4.43 Bn |
| 3 | Fortinet | 125.70 Bn | 111.63 Bn | 1.64 Bn | 4.84 Bn |
| 4 | Snowflake | 110.19 Bn | 97.50 Bn | 1.04 Bn | 3.72 Bn |
| 5 | Datadog | 92.71 Bn | 74.35 Bn | 881.34 Mn | 1.87 Bn |
| 6 | Zscaler | 34.07 Bn | 20.19 Bn | - | 2.96 Bn |
| 7 | Okta | 33.06 Bn | 23.16 Bn | 641.00 Mn | 2.03 Bn |
| 8 | Axon Enterprise | 30.90 Bn | 25.43 Bn | 546.45 Mn | 1.40 Bn |
| 9 | MongoDB | 28.04 Bn | 18.51 Bn | 569.77 Mn | 642.37 Mn |
| 10 | Rigetti Computing | 3.89 Bn | 2.19 Bn | 2.19 Mn | 105.06 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 105.06 Mn |
| Mar 31, 2026 | 61.88 Mn |
| Dec 31, 2025 | 12.15 Mn |
| Sep 30, 2025 | 11.63 Mn |
| Jun 30, 2025 | 10.43 Mn |
| Mar 31, 2025 | 11.39 Mn |
| Dec 31, 2024 | 11.87 Mn |
| Sep 30, 2024 | 21.46 Mn |
| Jun 30, 2024 | 25.56 Mn |
| Mar 31, 2024 | 24.88 Mn |
| Dec 31, 2023 | 29.05 Mn |
| Sep 30, 2023 | 23.04 Mn |
| Jun 30, 2023 | 21.35 Mn |
| Mar 31, 2023 | 22.99 Mn |
| Dec 31, 2022 | 21.75 Mn |
| Sep 30, 2022 | 16.31 Mn |
| Jun 30, 2022 | 12.87 Mn |
| Mar 31, 2022 | 13.05 Mn |
| Dec 31, 2021 | 7.57 Mn |
| Sep 30, 2021 | 995,252.00 |
API Access
Rigetti Computing Total Current 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-current-liabilities&ticker=RGTI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-current-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-current-liabilities&ticker=RGTI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();