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FAI vs QTUM

First Trust Bloomberg Artificial Intelligence ETF

FAIBNYSE Arca

Defiance Quantum ETF

QTUMANasdaq

Overlap

Expense ratio

QTUM −0.25pt a year

FAI0.65%QTUM0.40%

Avg volume · 30D

QTUM 5.2×the volume

FAI69.8KQTUM362K

FAI vs QTUM Performance

Oct 31, 2025 – Oct 30, 2026

+17.8%FAI+17.5%QTUM

Oct 31, 2025 to Oct 30, 2026. FAI +17.8%. QTUM +17.5%. Use the arrow keys to read each point.−20%0%40%Oct 2025Apr 2026Oct 2026
Expense ratio
FAI 0.65%
QTUM 0.40%, better
Fund size
FAI $248M
QTUM $5.06B
1Y total return
FAI +17.8%, better
QTUM +17.5%
Yield (12M)
FAI 0.00%
QTUM 1.05%, better
Holdings
FAI 52
QTUM 89
Avg volume (30D)
FAI 69.8K sh
QTUM 362K sh, better
NAV per share
FAI $51.09
QTUM $134.11
52W range

ETF.net Grade

FAI: Cost 52, Risk 67, Mission not scored, Tradability 75, Holdings 34, Durability 61. QTUM: Cost 86, Risk 70, Mission 74, Tradability 70, Holdings 91, Durability 79.
Pillar letters and Scores for FAI, QTUM, with each pillar’s weight
PillarFAIQTUM
Cost30% weightC52A86Higher
Mission25% weightNot scoredA74
Risk15% weightB67A70Higher
Tradability15% weightA75HigherA70
Holdings10% weightD34A91Higher
Durability5% weightB61A79Higher

Rank among Artificial Intelligence funds

Same Category. Both funds are graded against the same funds, so their Grades compare head to head.

Same Category. FAI and QTUM are both graded against the same 30 Artificial Intelligence funds, so their Grades compare head to head.

Artificial Intelligence⁠

Category · 30 funds
See all 30 ›

QTUM ranks 1st and FAI 12th of 30 funds in the Artificial Intelligence Category.

  1. Rank 1AQTUMDefiance Quantum ETFScore 79
  2. Rank 1AXAIXXtrackers Artificial Intelligence and Big Data ETFScore 79
  3. Rank 10BWISEThemes Generative Artificial Intelligence ETFScore 58
  4. Rank 12BFAIFirst Trust Bloomberg Artificial Intelligence ETFScore 57
  5. Rank 13BJHAIJanus Henderson Global Artificial Intelligence ETFScore 56

Our read on each fund

ETF.net Research

FAIBFirst Trust Bloomberg Artificial Intelligence ETF

QTUMADefiance Quantum ETF

In short

FAI No data

QTUM Live since 2018, QTUM turns the quantum-computing story into a plain index fund: about 90 global names spanning quantum hardware and machine learning, for 0.40% a year.

Stated mandate

FAI No data

QTUM The Fund seeks to track, before fees and expenses, the total return of the BlueStar® Quantum Computing and Machine Learning Index. It uses a passive indexing approach.

Why people hold it

FAI No data

  • QTUM 0.40% a year against a 0.68% median for its AI-theme cohort, and it undercuts peers like WTAI (0.45%) and ALAI (0.55%).
  • Rules-based by design: it tracks the BlueStar Quantum Computing and Machine Learning Index, so no manager is hand-picking which quantum story wins.
  • About 90 holdings across global markets, so the theme rides on a basket instead of two or three pure plays.
  • Size and liquidity back it up: a multi-billion-dollar fund that trades actively, and one of the stronger implementations in its thematic peer group.

Worth knowing

FAI No data

  • QTUM Risk is the softest part of the profile. One narrow, early-stage theme in a single asset class means sharper swings than a broad-market fund.
  • The index covers machine learning as well as quantum, so part of the basket is familiar AI exposure rather than quantum specialists.
  • Distributions come quarterly, but a growth theme like this is not built around income.

Full FAI profile⁠

Full QTUM profile⁠

FAI vs QTUM Holdings

How we measure overlap

Each holding counts at its smaller weight in the two funds, summed over the full Holdings. Sector, country and asset class use the same rule on each fund’s split. Cash, FX and derivative lines stay out of the counts. Two bond funds get no overlap figure.

FAI vs QTUM Cost

Overpaying FAI vs QTUM

$4,627

On $10,000 over 30 years. 7% growth a year before fees, expense ratio only.

  • FAI 0.65%

    $12,717

  • QTUM 0.40%

    $8,090

$10,000
30 years

Cost over time

  • FAI 0.65%
  • QTUM 0.40%
  • Overpaying
One line per fund, from year 0 to year 30. Use the arrow keys to read each point.$0$5K$10K$15K051015202530FAI $12,717QTUM $8,090

Year by year

YearFAIQTUMOverpaying
10$1,163$723$440
20$4,440$2,793$1,647
30$12,717$8,090$4,627

Expense ratio

  • 0.65%FAI
  • 0.40%QTUM, cheaper
  • Middle half of Artificial Intelligence funds
  • Median 0.65%

QTUM 5th cheapest of 30 funds

FAI 14th cheapest of 30 funds

FAI vs QTUM Dividends

Last 12 months to Oct 30, 2026
Yield (12M)
FAI 0.00%
QTUM 1.05%, better
Payout (12M)
FAI None
QTUM $1.40
Last payment
FAI No data
QTUM $0.46
Ex-dividend
FAI No data
QTUM Sep 23, 2026
Paid on
FAI No data
QTUM Sep 24, 2026
Frequency
FAI No data
QTUM Quarterly

Distribution history

Per share, 2018 to 2026, same scale for both

FAI1 paymentAll FAI payments⁠
One bar per payment. 1 payment from 2018 to 2026 YTD. Dec 13, 2024 $0.01. Use the arrow keys to read each point.$0$0.50202020232026YTD
QTUMQuarterly · 32 paymentsAll QTUM payments⁠
One bar per payment. 32 payments from 2018 to 2026 YTD. Dec 28, 2018 $0.04; Mar 12, 2019 $0.02; Jun 24, 2019 $0.08; Sep 17, 2019 $0.04; Dec 26, 2019 $0.04; Mar 24, 2020 $0.03; Jun 23, 2020 $0.07; Sep 22, 2020 $0.06; Dec 29, 2020 $0.05; Mar 24, 2021 $0.03; Jun 23, 2021 $0.10; Sep 22, 2021 $0.08; Dec 29, 2021 $0.07; Mar 23, 2022 $0.08; Jun 22, 2022 $0.19; Sep 21, 2022 $0.23; Dec 28, 2022 $0.07; Mar 22, 2023 $0.08; Jun 21, 2023 $0.12; Sep 20, 2023 $0.15; Dec 27, 2023 $0.09; Mar 20, 2024 $0.10; Jun 26, 2024 $0.20; Sep 25, 2024 $0.12; Dec 27, 2024 $0.08; Mar 26, 2025 $0.16; Jun 25, 2025 $0.27; Sep 24, 2025 $0.24; Dec 29, 2025 $0.45; Mar 25, 2026 $0.22; Jun 24, 2026 $0.27; Sep 23, 2026 $0.46. Use the arrow keys to read each point.$0$0.50202020232026YTD

FAI vs QTUM Risk

Fall from peak · 5 years

This chart needs five years of history for both funds.

Risk facts

VolatilityStd dev, 3 years
FAI 31.5%since Dec 2024QTUM 28.6%
Return per unit of riskSharpe ratio, 3 years
FAI 0.89since Dec 2024QTUM 1.30
Worst fallMax drawdown, 5 years
FAI −27.8%since Nov 2024QTUM −38.4%
Market sensitivityBeta, 5 years
FAI 2.10QTUM 1.67

FAI and QTUM in the news

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