Compare Consolidated Edison, Inc. (ED) vs Rigetti Computing Inc (RGTI) Price & Performance
Price performance (Past 24H)
Key statistics
Key statistics
Consolidated Edison, Inc. vs Rigetti Computing Inc — how do they compare? Consolidated Edison, Inc. trades at $105.92 (market cap $39.20B), while Rigetti Computing Inc trades at $14 (market cap $4.72B). The key difference: Consolidated Edison, Inc. is far larger — about 8.3× Rigetti Computing Inc's market cap, and Consolidated Edison, Inc. pays a 3.31% dividend while Rigetti Computing Inc pays none. Which is the better fit depends on your goals — on Pluang, investors hold Consolidated Edison, Inc. for 75 Days and Rigetti Computing Inc for 35 Days on average.
| ED | RGTI | |
|---|---|---|
Market Cap | $39.20B | $4.72B |
Volume | 2,142,900 | 17,136,381 |
Sector | Utilities | Technology |
52-Week High | $115.46 | $56.34 |
52-Week Low | $95.37 | $12.90 |
Typical Hold Time | 75 Days | 35 Days |
Enterprise Value | $66.05B | $4.33B |
Dividend Yield | 3.31% | — |
Aura AI Summary
Signals from Pluang's Aura AI — not financial advice
Aura AI Summary
Signals from Pluang's Aura AI — not financial advice
Consolidated Edison (ED) trades at $105.94, up 1.23% today, near the consensus price target of $106.33. The stock shows a mixed technical picture with a bullish overall signal but bearish moving averages, while fundamentals reflect steady utility performance with 2025 revenue of $16.92B and net income of $2.02B. Recent news highlights its $24.8B economic impact in New York and upcoming investor webcast, reinforcing its stable dividend aristocrat status.
ED offers a defensive investment with a reliable dividend and moderate growth, but faces risks from high debt levels and interest expenses. Analyst sentiment is cautious with 62.96% hold ratings, suggesting limited near-term upside despite solid cash flow generation. The stock's appeal lies in its income stability amid economic uncertainty, though execution on capital expenditures remains key to sustaining growth.
RGTI trades at $13.89, down 4.8% in the last session, amid bearish technical signals but strong analyst support. The company shows minimal revenue of $7.09M (2025) with significant losses (-$216.21M net income), though recent quarters saw mixed earnings beats. Positive sentiment stems from quantum computing sector momentum and strategic partnerships, yet high valuation ratios (P/S 349.79) and negative cash flow pose challenges.
Outlook: Analyst consensus is bullish (85.7% buy ratings) with a $21.67 price target, suggesting 56% upside, but high execution risks and cash burn require caution. Investment opportunity hinges on commercial scaling of quantum technology, while risks include sustained losses and competitive pressure in the emerging quantum sector.
Returns comparison
Trailing returns across standard periods
Returns comparison
Trailing returns across standard periods
Investor sentiment on Pluang
What Pluang investors did over the last 30 days
Investor sentiment on Pluang
What Pluang investors did over the last 30 days
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About Consolidated Edison, Inc.
Con Ed is a holding company for Consolidated Edison of New York, or CECONY, and Orange & Rockland, or O&R. These utilities provide steam, natural gas, and electricity to customers in southeastern New York—including New York City—and small parts of New Jersey. The two utilities will generate nearly all of Con Ed's earnings once it closes the sale of its clean energy business to RWE. Con Ed's clean energy business owns the second-largest portfolio of utility-scale solar projects in the U.S. Following the sale, Con Ed's only non-utility earnings will come from investments in gas and electric transmission.
Read more on ED →About Rigetti Computing Inc
Rigetti Computing, Inc. is a pioneer in quantum computing, focusing on developing and deploying quantum-classical computing systems. The company designs and fabricates superconducting quantum processors and integrates them with a full-stack software and control platform. Rigetti offers access to its quantum computers through the cloud, aiming to solve complex computational problems that are intractable for classical computers, with applications in finance, chemistry, and machine learning.
Read more on RGTI →
