CEVA, Inc (CEVA) Fair Value & Analysis
Technology · US · Market cap $1.4B
Fair value as of: Jun 24, 2026
Analysis
CEVA, Inc (CEVA) currently trades at $45.48, while our model-based Fair Value estimate is $36.23 — implying the stock looks roughly 20.3% 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
CEVA, Inc. provides silicon and software intellectual property (IP) solutions to semiconductor and original equipment manufacturer companies in the United States, Europe, the Middle East, the Asia Pacific, and internationally. The company offers PentaG-RAN, a hardware and software IP for implementing L1 PHY baseband processing in 5G and 5G-A base station and other cellular infrastructure system-on-chips (SoCs); Ceva XC20 DSPs and the PentaG2 platform support 5G/5G Advanced baseband for mobile broadband, RedCap, and IoT devices; Ceva-BX2 baseband processor; Ceva-XC21, high-efficiency vector DSP cores for 5G and 5G-advanced; Ceva-XC23, DSP for 5G and 5G-advanced; and Ceva-Waves Bluetooth platform, a set of hardware IP, software modules, and radios addressing a range of processes and nodes. It also provides Ceva-Waves Wi-Fi platform, a set of hardware IP and CPU-agnostic host software for energy-efficient SoC implementation of Wi-Fi subsystems; Ceva-Waves ultra-wideband platform; Ceva-…
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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.