Vuzix Corporation (VUZI) Fair Value & Analysis
Technology · US · Market cap $234M
Fair value as of: Jun 25, 2026
Analysis
Vuzix Corporation (VUZI) currently trades at $2.81, while our model-based Fair Value estimate is $1.67 — implying the stock looks roughly 40.6% overvalued today. We read business quality at 95/100 (high quality), in the Technology sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: low).
About the company
Vuzix Corporation designs, manufactures, and markets artificial intelligence (AI)-powered smart glasses, waveguides, and augmented reality (AR) technologies in North America, Europe, the Asia Pacific, and internationally. The company offers smart glasses that include M Series, Vuzix Blade, Vuzix Shield, and Vuzix Ultralite Z100; Mobilium logistics mobility software solution; waveguide optics; and display engines. It provides engineering services and original design manufacturers (ODM)/original equipment manufacturers (OEM) component solutions. It also offers head-mounted smart display and wearable computing devices. The company sells its products through direct sales, value-added resellers, distributors, ODM and OEM partnerships, and online stores, as well as various Vuzix operated web stores in the United States, Europe, and Japan. It serves the enterprise, medical, defense, security, and consumer markets. The company was formerly known as Icuiti Corporation and changed its name to…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.