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Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →A quantum-computing ETF targets companies selected for a relationship to quantum computing and related technologies; a broad technology ETF is designed to cover a wider technology-sector or technology-index universe. The label alone does not tell you how much of a thematic fund’s holdings earn revenue from quantum computing. To compare funds, check each one’s current index rules, holdings, concentration, costs and risks. Defiance Quantum ETF (QTUM) offers a documented example of a quantum-themed fund, but the available information here does not support a like-for-like comparison with a specific broad technology ETF.
What is the difference between a quantum computing ETF and a tech ETF?
The central difference is the selection rule. A thematic ETF selects companies because their businesses, products or services relate to a particular theme. A broad technology ETF generally follows a wider technology-sector or technology-index definition. The exact boundaries depend on the fund’s current prospectus and index methodology.
That distinction matters because a thematic label is not proof that every holding is a pure-play quantum-computing company, or that quantum computing is a material source of its revenue. Read the index rules and the fund’s holdings rather than relying on its name.
How QTUM defines its quantum-and-machine-learning exposure
Defiance Quantum ETF (ticker QTUM) seeks to track, before fees and expenses, the BlueStar Quantum Computing and Machine Learning Index. Its April 30, 2026 summary prospectus describes passive index tracking. A September 2, 2026 supplement later replaced the prospectus’s index description, so the supplement is essential when assessing the methodology. SEC-filed QTUM summary prospectus
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The updated description says the index is a modified equal-weighted portfolio of companies whose business activities, products and/or services relate to quantum-computing and machine-learning technology. The supplement’s definition of machine learning reaches beyond companies that sell quantum computers: it includes AI-based search and large language models, associated advanced computing hardware, big-data-related companies and AI-as-a-service. MarketVector Indexes GmbH is identified as the index provider. September 2, 2026 prospectus supplement
This breadth is why holdings matter. A company can qualify through a relationship to machine learning or its supporting infrastructure, not only through selling quantum-computing systems. The index’s thematic connection therefore should not be read as a measure of how much of each holding’s business depends on quantum computing.
Older methodology figures are dated context
The April 2026 prospectus described semiannual screening and reconstitution, along with market-capitalization and investibility criteria. It also reported that, as of March 31, 2026, the index had 82 constituents, including 20 listed on non-U.S. exchanges, and was concentrated in semiconductors with significant exposure to other information-technology industries, including software. Those figures predate the September methodology update; they do not establish the post-supplement index composition or QTUM’s current holdings. Consult the latest holdings and filings for a current picture.
Is a quantum ETF more focused than a technology ETF?
It is more focused by theme, but that does not automatically mean it holds only quantum-computing companies or is more concentrated by issuer than a particular technology ETF. QTUM’s updated index definition includes several machine-learning and AI-related categories. Whether it is narrower in actual holdings, geography, company size or sector weights than a particular broad fund can only be answered by comparing their current holdings and rules.
No specific broad technology ETF is documented here well enough for a numerical, fund-to-fund comparison. Avoid inferring a competitor’s fees, holdings, performance or risk from the category label. Use the following checklist with the current prospectus, index methodology and holdings for both funds:
- Index scope and selection: What relationship to quantum computing or machine learning qualifies a company for the thematic index? What sector, index or eligibility rules govern the broader fund?
- Holdings and concentration: Compare the largest positions, number of holdings, issuer weights and exposure to semiconductors and software.
- Geography and company size: Check domestic and international listings and the mix of large-, mid- and small-cap companies.
- Costs: Compare operating expenses, while also considering trading costs, bid-ask spreads and any brokerage charges.
- Turnover and implementation: Review rebalancing frequency, reported turnover, tracking difference and liquidity.
- Risk and portfolio role: Consider technology-sector overlap, thematic or business-model uncertainty, concentration and the possibility that ETF shares trade above or below net asset value. A targeted thematic position and a broader sector position serve different purposes; suitability depends on the rest of your portfolio and your risk tolerance.
QTUM’s disclosed expenses, turnover and past returns
QTUM’s April 30, 2026 summary prospectus reports total annual fund operating expenses of 0.40%. Brokerage commissions and financial-intermediary charges may be additional. This figure is specific to QTUM and is not evidence that it costs more or less than a broad technology ETF. QTUM summary prospectus filed with the SEC
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For the fiscal year ended December 31, 2025, the prospectus reports portfolio turnover of 42% of average portfolio value. Trading costs are not included in the operating-expense figure, and turnover can affect taxes in taxable accounts. Compare turnover and implementation costs using the same period and disclosures for any other fund.
For periods ended December 31, 2025, the prospectus reports QTUM before-tax returns of 36.35% for one year, 22.62% annualized for five years and 23.41% annualized since its September 4, 2018 inception. The same table reports S&P 500 Total Return Index returns of 17.88%, 14.42% and 14.29%, respectively; index returns do not deduct fees, expenses or taxes. These historical figures are not a comparison with a broad technology ETF and do not predict future results. The prospectus cautions that past performance does not necessarily indicate future performance.
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QTUM’s SEC-filed summary prospectus identifies risks associated with emerging technologies, quantum computing and machine learning, information technology and semiconductors, smaller- or mid-cap securities, index providers, tracking error, securities lending, and ETF shares trading at premiums or discounts to net asset value. It also discusses rapid technological change and obsolescence, competition, uncertain demand, regulation, reliance on intellectual-property rights, and potential cost or development effects from tariffs on specialized components and raw materials.
These are QTUM-specific disclosures, not a finding that every quantum ETF has identical risks or that a broad technology ETF is safer. A fair risk comparison requires the other fund’s own current prospectus and holdings. In particular, examine whether both funds share large technology or semiconductor positions, and whether the thematic fund adds concentration or business-model uncertainty relative to the rest of your portfolio.
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