GlobalFoundries Inc. Ordinary Shares vs Innodata Inc — how do they compare? GlobalFoundries Inc. Ordinary Shares trades at $50.2 (market cap $26.80B), while Innodata Inc trades at $63.19 (market cap $2.18B). The key difference: GlobalFoundries Inc. Ordinary Shares is far larger — about 12.3× Innodata Inc's market cap, and GlobalFoundries Inc. Ordinary Shares pays a 1% dividend while Innodata Inc pays none. Which is the better fit depends on your goals — on Pluang, investors hold GlobalFoundries Inc. Ordinary Shares for 0 Days and Innodata Inc for 19 Days on average.
| GFS | INOD | |
|---|---|---|
Market Cap | $26.80B | $2.18B |
Volume | 2,967,337 | 1,415,262 |
Sector | Technology | Technology |
52-Week High | $89.96 | $121.50 |
52-Week Low | $32.24 | $34.45 |
Typical Hold Time | 0 Days | 19 Days |
Enterprise Value | $26.09B | $1.93B |
Dividend Yield | 1% | — |
Signals from Pluang's Aura AI — not financial advice
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INOD trades at $63.42, down 4.26% today, but maintains strong technical support near $63. The company demonstrates robust fundamentals with revenue growing from $252M in 2025 to $317M in 2026 and net income expanding from $32M to $46M. Recent quarterly earnings consistently beat expectations, with Q1 2026 EPS of $0.42 surpassing the $0.13 estimate. Analyst sentiment remains positive with a 66.7% buy rating consensus.
INOD presents growth potential through its AI data engineering services and new motion-capture lab expansion, though premium valuation metrics (P/E 49.12, P/S 6.91) and customer concentration risks warrant caution. The stock's technical positioning near key support levels combined with strong earnings momentum supports a constructive outlook for investors seeking AI infrastructure exposure.
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GlobalFoundries is a semiconductor foundry that manufactures chips for other companies. Its technologies serve automotive, communications, industrial, and consumer markets.
Read more on GFS →Innodata is a global data engineering company that provides solutions for training AI models. It helps enterprises solve complex data challenges through high-quality data annotation and digital transformation.
Read more on INOD →