Baidu (BIDU) Accumulated Expenses (2009 - 2025)
Baidu (BIDU) posted Accumulated Expenses of $4.0 million for Q2 2026, little changed on a QoQ basis from $4.0 million in Q1 2026, and down 33.33% year-over-year from $6.0 million in Q2 2025.
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Analysis
Baidu (BIDU) Accumulated Expenses (2009 - 2025) Analysis & Trends
Baidu has reported Accumulated Expenses for 18 years, with the latest figure at $4.0 million in Q2 2026.
- On a quarterly basis, Accumulated Expenses fell 33.33% year-over-year to $4.0 million in Q2 2026; TTM through Jun 2026 was $4.0 million, a 33.33% decrease from a year earlier, with the FY2025 full-year figure at $1.3 billion, up 6.93% from the prior year.
- Accumulated Expenses was $4.0 million for Q2 2026 at Baidu, roughly flat from $4.0 million in the prior quarter.
- The five-year high for Accumulated Expenses was $1.2 billion in Q4 2023, with the low at $4.0 million in Q1 2026.
- Average Accumulated Expenses over 5 years is $279.9 million, with a median of $10.5 million recorded in 2023.
- The sharpest annual moves came in 2023 and 2025: Accumulated Expenses rose 0.05% in 2023, then slumped 99.58% in 2025.
- Over 5 years, Accumulated Expenses stood at $1.2 billion in 2022, then climbed by 0.05% to $1.2 billion in 2023, then retreated by 2.14% to $1.2 billion in 2024, then plunged by 99.58% to $5.1 million in 2025, then declined by 21.19% to $4.0 million in 2026.
- The last three Accumulated Expenses figures came in at $4.0 million (Q2 2026), $4.0 million (Q1 2026), and $5.1 million (Q4 2025), per Business Quant data.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palo Alto Networks | 320.54 Bn | 317.47 Bn | 2.30 Bn |
| 2 | CrowdStrike Holdings | 268.77 Bn | 263.80 Bn | 1.10 Bn |
| 3 | Fortinet | 131.12 Bn | 127.05 Bn | 1.64 Bn |
| 4 | Snowflake | 118.02 Bn | 115.67 Bn | 1.04 Bn |
| 5 | Datadog | 90.27 Bn | 85.29 Bn | 881.34 Mn |
| 6 | Axon Enterprise | 36.61 Bn | 35.93 Bn | 546.45 Mn |
| 7 | Zscaler | 34.97 Bn | 31.49 Bn | - |
| 8 | MongoDB | 34.51 Bn | 32.10 Bn | 569.77 Mn |
| 9 | Okta | 34.32 Bn | 32.02 Bn | 641.00 Mn |
| 10 | Baidu | 30.55 Bn | 8.15 Bn | 1.76 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 1.26 Bn |
| Dec 31, 2024 | 1.22 Bn |
| Dec 31, 2023 | 1.24 Bn |
| Dec 31, 2022 | 1.24 Bn |
| Dec 31, 2021 | 1.54 Bn |
| Dec 31, 2020 | 1.25 Bn |
| Dec 31, 2019 | 125.90 Mn |
| Dec 31, 2018 | 135.29 Mn |
| Dec 31, 2017 | 268.88 Mn |
| Dec 31, 2016 | 211.79 Mn |
| Dec 31, 2015 | 255.44 Mn |
| Dec 31, 2014 | 602.02 Mn |
| Dec 31, 2013 | 374.87 Mn |
| Dec 31, 2012 | 155.71 Mn |
| Dec 31, 2011 | 86.12 Mn |
| Dec 31, 2010 | 44.71 Mn |
| Dec 31, 2009 | 23.90 Mn |
| Sep 30, 2009 | 97.50 Mn |
| Jun 30, 2009 | 71.13 Mn |
| Mar 31, 2009 | 60.17 Mn |
API Access
Baidu Accumulated 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=accumulated-expenses&ticker=BIDU&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "BIDU", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=BIDU&period=max&api_key=YOUR_API_KEY");
const data = await res.json();