Pdf Solutions (PDFS) EV to EBIT (2011 - 2026)
Pdf Solutions' (PDFS) EV to EBIT came in at 144.97 for Q2 2026, down 96.5% from 4129.03 a year earlier but up 78.8% from the prior quarter.
Pdf Solutions (PDFS) EV to EBIT (2011 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, EV to EBIT at Pdf Solutions was 139.42, down 94.7% year-over-year; for FY2025, it came in at 185.72, down 81.4% from FY2024.
- In prior years, Pdf Solutions' EV to EBIT was 1000.90 in FY2024.
- Quarterly EV to EBIT has run from a low of 81.09 in Q1 2026 to a high of 4129.03 in Q2 2025 over five years.
- According to Business Quant data, EV to EBIT for the three prior quarters was 81.09 (Q1 2026), 185.72 (Q4 2025) and 339.26 (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Nvidia | 5,362.56 Bn | 5,136.72 Bn | 72.14 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,228.93 Bn | 1,853.79 Bn | 27.22 Bn |
| 3 | Broadcom | 1,613.65 Bn | 1,539.69 Bn | 20.46 Bn |
| 4 | Micron Technology | 1,034.76 Bn | 940.40 Bn | 47.05 Bn |
| 5 | Advanced Micro Devices | 904.00 Bn | 860.74 Bn | 6.20 Bn |
| 6 | Asml Holding | 651.05 Bn | 606.74 Bn | 5.90 Bn |
| 7 | Intel | 472.60 Bn | 341.74 Bn | 6.51 Bn |
| 8 | Lam Research | 329.18 Bn | 305.98 Bn | 3.48 Bn |
| 9 | Applied Materials | 324.43 Bn | 289.87 Bn | 4.59 Bn |
| 10 | Pdf Solutions | 1.80 Bn | 1.58 Bn | 42.42 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 144.97 |
| Mar 31, 2026 | 81.09 |
| Dec 31, 2025 | 185.72 |
| Sep 30, 2025 | 339.26 |
| Jun 30, 2025 | 4,129.03 |
| Dec 31, 2024 | 1,000.90 |
| Dec 31, 2023 | 965.68 |
| Sep 30, 2023 | 329.19 |
| Jun 30, 2023 | 315.85 |
| Mar 31, 2023 | 640.56 |
| Mar 31, 2018 | 2,092.96 |
| Dec 31, 2017 | 2,120.48 |
| Sep 30, 2017 | 187.19 |
| Jun 30, 2017 | 87.88 |
| Mar 31, 2017 | 66.29 |
| Dec 31, 2016 | 46.41 |
| Sep 30, 2016 | 33.29 |
| Jun 30, 2016 | 23.95 |
| Mar 31, 2016 | 22.04 |
| Dec 31, 2015 | 10.97 |
Pdf Solutions EV to EBIT 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=ev-to-ebit&ticker=PDFS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ev-to-ebit", "ticker": "PDFS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=ev-to-ebit&ticker=PDFS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();