D-Wave Quantum (QBTS): Can It Reclaim the $40 Level?

Key Takeaways

• Investors continue to ask whether D-Wave Quantum Inc. (QBTS) can return to the $40 level, a round-number target cited by several Wall Street firms.
• The main bullish argument centers on an order book that has grown sharply even while reported revenue has remained modest, alongside expanding production deployments and U.S. government support.
• The primary challenges include uneven revenue recognition, widening operating losses, a valuation that embeds significant future growth, and a technical picture that sits below key moving averages.
• Key support rests near the 52-week low around $12.75, with resistance in the low-$20s and again near prior highs around $46.75.
• Reaching $40 would require roughly a 140% advance from recent levels, so the outlook hinges on bookings converting into recognized revenue more rapidly than they have to date.

Why the $40 Level Draws Attention

D-Wave Quantum develops quantum annealing computing systems, software, and services, and it has drawn steady interest within the emerging quantum-computing space. After reaching a peak near $46.75 in late 2025, the stock has retreated and recently traded around $16.50, giving the company a market capitalization near $6.1 billion. That pullback has led many investors to wonder whether QBTS can realistically revisit the $40 mark.

The $40 level is not random. Firms including Cantor Fitzgerald, Jefferies, Craig-Hallum, and Wedbush have issued $40 price targets, positioning the round number in the upper half of the consensus range. Because the stock has already traded above $40, the target represents a return to familiar territory rather than a leap into unknown valuation territory.

Current Market Position

Recent results present a mixed picture. In the latest quarter, revenue held essentially flat year over year at about $3.1 million and fell short of estimates, while the adjusted EBITDA loss widened to roughly $37.1 million amid higher spending on development and commercialization. The company closed the period with approximately $546 million in cash and marketable securities, a sizable buffer that shrank partly due to the roughly $250 million acquisition of Quantum Circuits.

Demand signals, however, strengthened markedly. First-half bookings jumped more than 1,120% year over year to about $35.5 million, and remaining performance obligations rose to roughly $40.7 million. Management expects a meaningful share of that backlog to convert within twelve months, and a roughly $20 million system sale to Florida Atlantic University is slated for delivery and recognition largely in the fourth quarter.

Factors That Could Support Further Gains

The clearest route to $40 runs through revenue conversion. Successful shipment of annealing systems and recognition of the RPO as sales would lift the top line and validate the demand already secured. Management also plans to deliver a 17-qubit gate-based system by the end of 2026 and has mapped a longer roadmap toward fault-tolerant, 100-logical-qubit systems by 2032.

Commercial traction is expanding in ways that could underpin a higher valuation. Six customer applications are now running in production, and production use accounts for more than a third of quantum-computing-as-a-service revenue, a sharp increase from the prior year. Deployments with large customers have shown measurable operational gains, and a partnership in financial-crime detection points to wider enterprise use. U.S. government backing, including up to $100 million under the CHIPS Act, adds further validation of the dual annealing and gate-based strategy. I also checked this using Tickeron’s AI Trend Prediction Engine to see how the broader sector momentum compares.

Obstacles That Could Limit Upside

Several hurdles stand between the current price and $40. Revenue remains lumpy and tied to a small number of large system sales, so quarterly results can vary sharply. The company is still deeply unprofitable, and a valuation that already prices in years of growth leaves little margin for execution shortfalls. Competition from better-funded names such as IonQ (IONQ) and Rigetti Computing (RGTI), along with large technology incumbents, raises the bar for sustained commercial progress.

Volatility is another consideration. With a beta well above 2, QBTS has seen frequent double-digit single-day moves, and recent insider selling adds a note of caution. Failure to convert bookings into revenue could keep the shares range-bound well below the $40 goal.

Analyst Targets and Technical Levels

Analyst sentiment stays largely positive. The consensus recommendation sits in “buy” territory, with an average price target of roughly $35 to $36, a low near $22, and a high near $43 to $45. The $40 objective therefore sits modestly above the consensus average yet receives backing from multiple individual firm targets.

From a technical standpoint the outlook is more guarded. The stock has traded below both its 50-day and 200-day moving averages, signaling a downtrend that has not yet reversed. The 52-week low near $12.75 remains the key support level, while the low-$20s represent an initial resistance that would need to be cleared before a sustained move toward $40 becomes realistic.

Monitoring QBTS with AI Tools

When tracking names like QBTS and the wider quantum-computing group, I often rely on Tickeron’s AI Daily Buy/Sell Signals as part of my routine review. The tool applies artificial intelligence to scan thousands of stocks and ETFs, producing automated Buy, Sell, or Hold signals drawn from technical behavior, trend shifts, and AI-driven analysis. This helps surface fresh ideas, follow existing holdings, and spot changing conditions more quickly than manual checks alone would allow, which is especially useful in volatile sectors where momentum can shift rapidly.

Disclaimer

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Contributor

Sergey Savastiouk|Expert

Sergey Savastiouk, Ph.D. has a degree in Applied Mathematics from Moscow University and has extensive experience as an entrepreneur, investor, manager, and mathematician. His professional expertise is in applied mathematics, mathematical modeling, system and pattern analysis, and software and hardware system integration. He has served as the CEO of several hi-tech start-up companies and nonprofit organizations, which has given him proven capabilities in business strategy for high-tech start-up companies, market assessment, company formation, team building, product development, marketing, and sales. He has published numerous articles in journals and magazines on related fields. As a retail investor, he spent 15 years developing his proprietary trading and quantitative algorithms (now Tickeron’s A.I.), which brought him significant returns in trading the stock market. His current work and goal in founding Tickeron is to bring professional, sophisticated stock market analysis capabilities to retail investors via an easy-to-use interface.

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