Market research
IONQ IONQ Inc
NYSE USD Technology
Latest close
As of 30 Oct 2026
Test a moving-average rule with historical data.
Market facts
- Market cap
- 13B
- P/E ratio
- Not available
- Analyst target
- 64.0607
- Dividend yield
- Not available
- Beta
- 3.36
Profile
Instrument facts
- Exchange
- NYSE
- Currency
- USD
- Sector
- Technology
- Industry
- Computer Hardware
- ISIN
- Not available
- Market cap
- 13B
- P/E ratio
- Not available
- Analyst target
- 64.0607
- Dividend yield
- Not available
- Beta
- 3.36
About
About IONQ Inc
IonQ, Inc. develops quantum computing systems in the United States, Switzerland, and Internationally. It sells access to quantum computers of various qubit capacities. The company also makes access to its quantum computers through cloud platforms, such as Amazon Web Services (AWS), Braket, Microsoft's Azure Quantum, and Google's Cloud Marketplace, as well as through its cloud service. The company engages in quantum-safe communications and quantum detection systems. It provides contracts associated with the design, development, construction, and sale of specialized quantum computing hardware systems; maintenance and support services; and consulting services related to co-developing algorithms on quantum computing systems. In addition, it provides semiconductor manufacturing services. The company has a collaboration agreement with University of Chicago. The company was founded in 2015 and is headquartered in College Park, Maryland.
Research context
IONQ Inc appears in PyInvesting’s US Stock catalogue. The price history above describes this recorded instrument; it does not by itself identify a company’s business or establish a continuous investment return.
- Currency
- USD
- Sector
- Technology
- Industry
- Computer Hardware
These are the latest stored catalogue classifications, not a historical classification snapshot. An issuer description, classification effective date or currency may be unavailable. Check the issuer’s own disclosures and the observation dates before using these fields for research.
Review backtest assumptions and evidence before treating a chart or stored history as a research result.
Community
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