Codexis (CDXS) Total Current Liabilities (2010 - 2026)
Codexis' Total Current Liabilities came in at $23.51 million for Q2 2026, up 54.3% from $15.24 million a year earlier and up 58.3% from the prior quarter.
Codexis (CDXS) Total Current Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Codexis' Total Current Liabilities was $25.32 million, up 7.1% from FY2024.
- Total Current Liabilities carries a five-year compound annual growth rate of 0.3% (FY2020 to FY2025).
- Going back by year, Total Current Liabilities was $23.65 million in FY2024 (-34.0%), $35.83 million in FY2023 (-27.0%), $49.07 million in FY2022 (+47.0%) and $33.37 million in FY2021 (+33.6%).
- The five-year range for quarterly Total Current Liabilities is $14.85 million (Q1 2026) to $49.07 million (Q4 2022).
- Year-over-year, Total Current Liabilities increased in two of the last eight quarters, with an average decline of 17.0%.
- The fastest year-over-year change in Total Current Liabilities over five years came in Q3 2021 (growth of 63.3%), and the weakest in Q2 2025 (a decline of 50.1%).
- Business Quant data shows CDXS's Total Current Liabilities at $14.85 million (Q1 2026), $25.32 million (Q4 2025) and $18.48 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 250.84 Bn | 229.99 Bn | 4.88 Bn | 15.07 Bn |
| 2 | Abbott Laboratories | 174.73 Bn | 145.82 Bn | 7.27 Bn | 17.81 Bn |
| 3 | Danaher | 159.85 Bn | 143.67 Bn | 3.61 Bn | 8.11 Bn |
| 4 | Intuitive Surgical | 146.79 Bn | 126.35 Bn | 1.96 Bn | 1.92 Bn |
| 5 | Medtronic | 114.54 Bn | 80.41 Bn | 6.34 Bn | 11.80 Bn |
| 6 | Stryker | 105.67 Bn | 91.79 Bn | 4.50 Bn | 6.68 Bn |
| 7 | Boston Scientific | 63.93 Bn | 58.94 Bn | 3.85 Bn | 6.43 Bn |
| 8 | Becton Dickinson | 50.12 Bn | 47.27 Bn | 2.32 Bn | 9.40 Bn |
| 9 | Edwards Lifesciences | 50.06 Bn | 34.17 Bn | 1.35 Bn | 1.51 Bn |
| 10 | Codexis | 124.29 Mn | -132.76 Mn | 11.40 Mn | 23.51 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 23.51 Mn |
| Mar 31, 2026 | 14.85 Mn |
| Dec 31, 2025 | 25.32 Mn |
| Sep 30, 2025 | 18.48 Mn |
| Jun 30, 2025 | 15.24 Mn |
| Mar 31, 2025 | 20.90 Mn |
| Dec 31, 2024 | 23.65 Mn |
| Sep 30, 2024 | 35.13 Mn |
| Jun 30, 2024 | 30.54 Mn |
| Mar 31, 2024 | 29.08 Mn |
| Dec 31, 2023 | 35.83 Mn |
| Sep 30, 2023 | 38.42 Mn |
| Jun 30, 2023 | 35.74 Mn |
| Mar 31, 2023 | 38.31 Mn |
| Dec 31, 2022 | 49.07 Mn |
| Sep 30, 2022 | 31.91 Mn |
| Jun 30, 2022 | 30.01 Mn |
| Mar 31, 2022 | 29.50 Mn |
| Dec 31, 2021 | 33.37 Mn |
| Sep 30, 2021 | 33.48 Mn |
Codexis 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=CDXS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-current-liabilities", "ticker": "CDXS", "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=CDXS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();