Meta Platforms (META) EV to EBITDA (2012 - 2026)
Meta Platforms' (META) quarterly EV to EBITDA came in at 71.64 in Q2 2026, down 19.09% year-over-year from 88.55 in Q2 2025, and up 19.52% quarter-over-quarter from 59.94 in Q1 2026.
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Analysis
Meta Platforms (META) EV to EBITDA (2012 - 2026) Analysis & Trends
Meta Platforms (META) has reported EV to EBITDA for 15 consecutive years, with 71.64 the latest figure, recorded in Q2 2026.
- On a quarterly basis, EV to EBITDA fell 19.09% year-over-year to 71.64 in Q2 2026; TTM through Jun 2026 was 15.47, a 32.71% decrease from a year earlier, with the FY2025 full-year figure at 19.07, down 5.87% from the prior year.
- EV to EBITDA was 71.64 for Q2 2026 at Meta Platforms, up from 59.94 in the prior quarter.
- Over five years, EV to EBITDA peaked at 88.55 in Q2 2025 and troughed at 42.79 in Q4 2022.
- A 5-year average of 67.54 and a median of 67.86 in 2023 frame the typical range for EV to EBITDA.
- Across the five-year window, EV to EBITDA tumbled 38.38% in 2022 and surged 54.55% in 2023, its largest moves.
- Over 5 years, EV to EBITDA stood at 42.79 in 2022, then rose by 19.96% to 51.34 in 2023, then increased by 17.21% to 60.17 in 2024, then increased by 6.68% to 64.19 in 2025, then climbed by 11.6% to 71.64 in 2026.
- The last three EV to EBITDA figures came in at 71.64 (Q2 2026), 59.94 (Q1 2026), and 64.19 (Q4 2025), per Business Quant data.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Alphabet | 4,144.46 Bn | 3,901.99 Bn | 73.85 Bn |
| 2 | Meta Platforms | 1,981.30 Bn | 1,683.82 Bn | 49.47 Bn |
| 3 | Netflix | 296.22 Bn | 256.42 Bn | 6.52 Bn |
| 4 | Alibaba Group Holding | 254.92 Bn | 72.79 Bn | 15.11 Bn |
| 5 | Shopify | 184.25 Bn | 161.43 Bn | 1.71 Bn |
| 6 | Uber Technologies | 142.00 Bn | 113.98 Bn | 6.38 Bn |
| 7 | Booking Holdings | 123.19 Bn | 56.24 Bn | - |
| 8 | PDD Holdings | 110.41 Bn | -141.52 Bn | 9.45 Bn |
| 9 | Spotify Technology | 104.89 Bn | 62.12 Bn | 1.86 Bn |
| 10 | AppLovin | 104.19 Bn | 94.23 Bn | 1.70 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 12.27 |
| Mar 31, 2026 | 12.54 |
| Dec 31, 2025 | 15.59 |
| Sep 30, 2025 | 18.15 |
| Jun 30, 2025 | 18.96 |
| Mar 31, 2025 | 15.53 |
| Dec 31, 2024 | 16.56 |
| Sep 30, 2024 | 17.93 |
| Jun 30, 2024 | 16.97 |
| Mar 31, 2024 | 17.96 |
| Dec 31, 2023 | 14.52 |
| Sep 30, 2023 | 15.07 |
| Jun 30, 2023 | 17.85 |
| Mar 31, 2023 | 13.80 |
| Dec 31, 2022 | 7.28 |
| Sep 30, 2022 | 7.36 |
| Jun 30, 2022 | 8.21 |
| Mar 31, 2022 | 10.75 |
| Dec 31, 2021 | 15.97 |
| Sep 30, 2021 | 16.25 |
API Access
Meta Platforms EV to EBITDA 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-ebitda&ticker=META&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ev-to-ebitda", "ticker": "META", "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-ebitda&ticker=META&period=max&api_key=YOUR_API_KEY");
const data = await res.json();