---
title: "IONQ vs QBTS"
canonical: "https://supercyclehq.com/compare/ionq-vs-qbts"
type: "comparison"
dataAsOf: "2026-11-06"
tickers: ["IONQ", "QBTS"]
license: "Free to use and quote with attribution to supercyclehq.com. Do not redistribute as a dataset."
disclaimer: "Informational only, not investment advice. The AI Exposure Score is Supercycle's editorial opinion. Agent portfolios are simulated paper portfolios run by AI."
---

# IonQ (IONQ) vs D-Wave Quantum (QBTS)

Both are tracked in the Supercycle AI universe. End-of-day data, updated nightly.

| Measure | IONQ | QBTS |
| --- | --- | --- |
| AI Exposure Score | 30 (Growing) | 55 (Strategic) |
| Price | $32.62 | $10.68 |
| Market cap | $14.0B | $4.1B |
| Change 1d | +23.42% | +18.01% |
| Change 30d | -17.31% | -26.85% |
| Change 1y | -44.96% | -63.80% |
| P/E | n/a | n/a |
| Buildout layers | Quantum Computing | Quantum Computing |

## IonQ (IONQ)

**AI exposure:** Sells access to trapped-ion quantum computers through cloud providers and research contracts, pitched partly at future AI and optimization workloads. Exposure is speculative optionality, since useful quantum advantage for AI remains years away.

IonQ sits in the Quantum Computing layer of the AI buildout as a long-horizon bet. Its trapped-ion quantum computers are pitched partly at future AI and optimization workloads that classical machines handle poorly. Today it earns revenue from cloud access and research contracts while the technology matures. The exposure is speculative optionality: useful quantum advantage for AI remains years away, so the AI connection is about where quantum could plug in, not current demand.

Full profile: https://supercyclehq.com/stock/ionq.md

## D-Wave Quantum (QBTS)

**AI exposure:** D-Wave sells quantum annealing systems and Leap cloud access for optimization and hybrid quantum-classical machine learning workloads. The stock trades as a frontier compute bet adjacent to AI, and exposure hinges on quantum proving useful for commercial AI-scale problems.

D-Wave sits in the Quantum Computing layer as a frontier compute bet adjacent to the AI buildout. Its annealing systems and Leap cloud service target optimization and hybrid quantum-classical machine learning, workloads that overlap with where AI is headed. The exposure hinges on quantum computing proving useful for commercial AI-scale problems, which remains an open question. Supercycle scores its AI exposure at 55 out of 100.

Full profile: https://supercyclehq.com/stock/d-wave-quantum.md

## Related comparisons

- [IONQ vs RGTI](https://supercyclehq.com/compare/ionq-vs-rgti.md)

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Source: https://supercyclehq.com/compare/ionq-vs-qbts. Data as of 2026-11-06. Prices are end-of-day closes, never live.

Informational only, not investment advice. The AI Exposure Score is Supercycle's editorial opinion. Agent portfolios are simulated paper portfolios run by AI.

Free to use and quote with attribution to supercyclehq.com. Do not redistribute as a dataset.