What is quantum error correction and why does it matter for commercial quantum computing?

The fundamental challenge with quantum computers: quantum states are extremely fragile — interactions with the environment (heat, vibration, electromagnetic noise) cause 'decoherence' (the quantum state is disturbed and the computation fails); current quantum computers make errors at rates of 0.1-1% per gate operation; a useful fault-tolerant quantum computation might require millions of gate operations — even at 0.1% error per gate, this compounds to essentially 100% computation failure. Quantum error correction (QEC): QEC encodes one 'logical qubit' using many 'physical qubits' — using redundancy to detect and correct errors while preserving the quantum information; the most promising QEC codes (surface code, stabilizer codes) require approximately 1,000-10,000 physical qubits to create one reliable logical qubit; this means a fault-tolerant quantum computer solving real problems might require millions of high-quality physical qubits. Why this matters: current quantum computers are called NISQ devices (Noisy Intermediate-Scale Quantum — a term coined by John Preskill); NISQ computers have 10-1,000 qubits but too many errors for large-scale error-corrected computation; quantum advantage for real commercial problems (drug discovery, material simulation, financial optimization) likely requires fault-tolerant logical qubits, which requires millions of physical qubits; the timeframe for reaching this scale is uncertain — estimates range from 5 years to 20+ years; in the meantime, researchers are exploring whether NISQ devices can demonstrate 'quantum advantage' on specific problems using error mitigation (statistical methods to reduce errors without full QEC) rather than error correction.

What kinds of problems could quantum computers solve better than classical computers?

Quantum computers are NOT universally faster than classical computers — they are specifically faster for certain computational problem types where quantum effects provide an advantage. Well-established quantum advantages: cryptography breaking — Shor's algorithm can factor large integers (the basis of RSA encryption) exponentially faster than classical algorithms; this would break current public-key cryptography; governments and cybersecurity firms are investing in 'post-quantum cryptography' to prepare; however, breaking today's encryption requires millions of fault-tolerant qubits — far beyond current NISQ capabilities. Quantum simulation — simulating quantum systems (molecules, materials, chemical reactions) is exponentially hard for classical computers but natural for quantum computers; applications include drug discovery (simulating protein folding and drug binding at quantum level), materials science (designing new superconductors, catalysts, battery materials); even near-term NISQ devices may provide useful quantum chemistry simulation advantages before full fault tolerance is achieved. Optimization — solving complex combinatorial optimization problems (portfolio optimization, logistics routing, protein folding); quantum algorithms (quantum approximate optimization algorithm — QAOA) may provide speedups for certain optimization problems, but the advantage over classical heuristics is not yet proven definitively. Machine learning — quantum machine learning (QML) is an active research area; whether quantum computers provide real advantages for ML training is uncertain; claims of quantum ML advantage have not been definitively demonstrated on useful problems.

What is 'quantum advantage' and has it been demonstrated?

Quantum advantage (sometimes called 'quantum supremacy' in older literature): the point at which a quantum computer performs a specific calculation faster than any classical computer could in a reasonable time. Claimed quantum advantage demonstrations: Google (2019) — Google's Sycamore superconducting processor claimed to perform a specific sampling task in 200 seconds that would take the Summit supercomputer 10,000 years; IBM disputed this claim, arguing the same task could be performed classically in days rather than 10,000 years; the task itself (random circuit sampling) has no direct commercial application — it was chosen specifically because it is hard for classical computers but easy for quantum computers. IBM (2023) — IBM demonstrated quantum advantage on a specific physics simulation task (magnetic system simulation), claiming 100-qubit advantage; again, the problem was chosen to demonstrate quantum advantage rather than being commercially relevant. The key unresolved question: demonstrated quantum advantages so far are for narrow, engineered problems; demonstrating quantum advantage for a commercially relevant problem (drug molecule simulation, financial portfolio optimization, logistics routing) with error rates low enough to beat the best classical algorithms and heuristics remains the holy grail; most quantum computing experts believe this requires fault-tolerant quantum computing with millions of physical qubits — still years away; in the meantime, NISQ quantum computers may have limited, specific use cases where they provide value, but general-purpose quantum advantage over classical computers is not yet achieved.

Is IonQ (IONQ) or Rigetti (RGTI) the better quantum computing investment in 2026?

IonQ is generally considered the higher-quality quantum computing investment among publicly traded pure-plays: its trapped ion qubit fidelity metrics are best-in-class, it has multi-cloud accessibility (AWS, Azure, Google Cloud), and it has won significant government and commercial contracts. Rigetti is higher-risk with more execution challenges and faces head-to-head competition with IBM and Google using the same superconducting approach at orders-of-magnitude larger scale. Neither is appropriate for significant portfolio exposure — both are speculative long-dated bets. If forced to choose, most quantum computing-focused investors prefer IonQ's technology differentiation over Rigetti's scale disadvantage vs IBM.

What government contracts does IonQ have?

IonQ has won contracts from multiple US government agencies including DARPA (Defense Advanced Research Projects Agency), the Air Force Research Laboratory, and the National Science Foundation. These government contracts provide tens of millions of dollars in non-dilutive research funding while the commercial quantum market matures — an important near-term revenue source that reduces IonQ's dependency on commercial enterprise adoption timelines. Rigetti has similarly pursued government contract revenue including DARPA programs. Government quantum computing research spending has been bipartisan, with the National Quantum Initiative Act providing $1.2B+ in federal quantum research funding — benefiting both IonQ and Rigetti through research contracts.

Can IonQ or Rigetti scale to the thousands of qubits needed for fault-tolerant quantum computing?

Both face significant scaling challenges, though through different engineering problems. IonQ's trapped ion approach currently handles 10s of qubits per ion trap — scaling to hundreds or thousands requires photonic interconnects linking multiple ion traps, a significant engineering challenge. IonQ has published roadmaps targeting large-scale modular quantum computing through networked ion traps. Rigetti's superconducting approach is more similar to classical semiconductor manufacturing (potentially enabling more qubits on a chip), but coherence times decrease and error rates increase as superconducting qubit counts scale. IBM's publicly announced superconducting roadmap targets 100,000+ qubit systems by 2033 — Rigetti's resources are insufficient to match this pace, raising questions about whether Rigetti can achieve fault-tolerant scale before being outcompeted by IBM.

Data as of: September 19, 2026

brimindinvest.com / compare / ionq-vs-rigettiLIVE

IONQ

IonQ, Inc. · Technology - Quantum Computing

$40.34

-8.57% this month

VERSUS

COMPARE

RGTI

Rigetti Computing, Inc. · Technology - Quantum Computing

$15.99

-9.71% this month

Comparison scoreboard

IONQ LEADS 3/5

AI Scorei

IONQ ✓52.1

RGTI 37.9

1Y Returni

IONQ -38.36%

RGTI ✓-27.29%

Fwd P/Ei

IONQ ✓-30.87

RGTI -72.18

Target Up.i

IONQ +80.47%

RGTI ✓+93.76%

Op. Margini

IONQ ✓-408.17%

RGTI -546.17%

Metrics last refreshed: 9/19/2026

Quick take

IONQ vs RGTI Stock Comparison 2026: Trapped Ion vs Superconducting Quantum: AI Score, Valuation, Performance and Upside

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IONQ (IonQ) and RGTI (Rigetti Computing) are both early-stage publicly traded quantum computing companies building different types of quantum computers — IonQ uses trapped ion qubits (best current qubit quality, harder to scale) while Rigetti uses superconducting qubits (same approach as IBM and Google, easier to scale in principle but competing with much larger players using the same technology). Both are pre-commercial with minimal revenue relative to market capitalization, and both represent speculative investments in the long-term quantum computing infrastructure opportunity.

IONQ vs RGTI is differentiated qubit technology with superior near-term quality metrics (IonQ's trapped ion approach providing best-available fidelity and coherence times via multi-cloud access, with technological differentiation from superconducting competitors) versus superconducting qubits with vertically integrated manufacturing competing directly with IBM and Google (Rigetti's Fab-1 enabling rapid chip iteration in the dominant quantum hardware paradigm, at a resource disadvantage versus IBM and Google who use the same technology at 100x the R&D scale) — technology differentiation premium versus manufacturing speed with existential scale competition.

Live analysis · updated 9/19/2026

IONQ holds the edge across 3 of 5 key metrics in this comparison. RGTI has delivered stronger 1-year price return (-27.29% vs -38.36%), though IONQ has the better forward P/E setup (-30.87x vs -72.18x for RGTI). IONQ leads on both revenue growth (286.80%) and operating margin (-408.17%), suggesting a stronger fundamental setup on both dimensions. Analyst consensus implies meaningfully more upside for RGTI (+93.76%) than for IONQ (+80.47%).

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Normalized 1Y performance

IONQ

RGTI

Recent returns

IONQ

RGTI

Analyst price targets & sentiment

Human Wall Street analysts' price targets, typically implying a ~12-month view — a separate signal from this site's own AI Prediction Signal further down the page, which is a 5-/30-day machine-learning forecast based on price history alone.

IONQ

Price target range

analyst mean$67.68
current price$40.34

+80.5% upside to analyst mean

RGTI

Price target range

analyst mean$28.81
current price$15.99

+93.8% upside to analyst mean

Who should consider this stock?

IONQ may suit investors who:

Believe trapped ion qubits' superior current quality (fidelity, coherence time, all-to-all connectivity) will provide a durable advantage over superconducting qubits even as both approaches scale toward fault-tolerant quantum computing
Value IonQ's technology differentiation from IBM and Google as protecting against being outcompeted by much larger players using the same underlying physics — IonQ's trapped ion approach is genuinely different from the dominant superconducting paradigm
Are making a speculative long-term bet on quantum computing commercialization and prefer the company with the best current qubit quality metrics as the safest (still highly speculative) bet within the quantum computing cohort

RGTI may suit investors who:

Believe Rigetti's Fab-1 vertical manufacturing integration enables faster qubit design iteration that could allow Rigetti to improve qubit quality and scale faster than the development timelines of outsourced superconducting chip fabrication
See Rigetti's lower market capitalization (versus IonQ) as providing asymmetric upside if the superconducting approach proves commercially viable — accepting higher risk of being outcompeted by IBM/Google in exchange for potentially higher upside if Rigetti establishes a niche
Want superconducting qubit exposure in a small-cap quantum computing company without paying the premium valuation that IonQ has typically commanded relative to its early-stage revenue

Performance & AI score

Performance & AI score
Metric	IONQ	RGTI
AI scorei	52.1	37.9
AI ranki	#415	#1443
Latest closei	$40.34	$15.99
1M returni	-8.57%	-9.71%
6M returni	+26.46%	+3.76%
1Y returni	-38.36%	-27.29%

$10,000 invested — hypothetical growth (dividends reinvested)

How much would $10,000 be worth today if invested at the start of each period, with all dividends reinvested?

$10,000 invested — hypothetical growth (dividends reinvested)
Period	IONQ	RGTI
1Y ago	$6.16K (-38.4%) started 2025-09-17	$7.27K (-27.3%) started 2025-09-17
5Y ago	$40.1K (+301.0%) started 2021-09-17	$16.35K (+63.5%) started 2021-09-17
10Y ago	$37.35K (+273.5%) started 2021-01-04	$16.15K (+61.5%) started 2021-04-22

Hypothetical — past performance does not guarantee future results.

Valuation & upside potential

Valuation & upside potential
Metric	IONQ	RGTI
Market capi	$15.19B	$4.96B
Trailing P/Ei	N/A	N/A
Forward P/Ei	-30.87	-72.18
Price/Salesi	N/A	N/A
EV/Revenuei	50.08	345.78
Analyst targeti	$67.68	$28.81
Target upsidei	+80.47%	+93.76%

Full DCF model for IONQ Full DCF model for RGTI

Growth, profitability & risk

Growth, profitability & risk
Metric	IONQ	RGTI
Revenue growthi	286.80%	185.30%
Earnings growthi	N/A	N/A
EPS growthi	N/A	N/A
FCF margini	-35.61%	+198.11%
Operating margini	-408.17%	-546.17%
Profit margini	0.00%	0.00%
ROIC proxyi	-60.48%	-43.77%
Return on equityi	-60.48%	-43.77%
Dividend yieldi	N/A	N/A
Payout ratioi	0.00%	0.00%
Dividend growth streaki	N/A	N/A
Betai	3.30	2.02
Debt/equityi	1.63	1.43
Current ratioi	10.66	3.94
Quick ratioi	9.92	3.78

Correlation

Over the past year, IONQ and RGTI have moved strongly in the same direction (correlation of 0.85), based on daily returns.

1Y

0.85

-1.0+1.0

5Y

0.56

-1.0+1.0

10Y

0.56

-1.0+1.0

Drawdown & downside risk

Lower drawdown and smaller single-period drops generally indicate a smoother ride, though they do not guarantee lower future risk.

1Y risk snapshot

IONQ max drawdowni67.61%

RGTI max drawdowni77.10%

IONQ max wkly dropi29.63%

RGTI max wkly dropi36.00%

5Y risk snapshot

IONQ max drawdowni90.00%

RGTI max drawdowni96.89%

IONQ max wkly dropi42.22%

RGTI max wkly dropi68.19%

10Y risk snapshot

IONQ max drawdowni90.00%

RGTI max drawdowni96.89%

IONQ max wkly dropi42.22%

RGTI max wkly dropi68.19%

Performance metrics by period

Performance metrics by period
Period	Metric	IONQ	RGTI
1Y	Growthi	-38.36%	-27.29%
	CAGRi	-38.38%	-27.30%
	Volatilityi	94.24%	105.41%
	Sharpe ratioi	-0.10	0.16
	Sortino ratioi	-0.16	0.26
	Max drawdowni	67.61%	77.10%
	Current drawdowni	50.86%	71.62%
	Avg drawdowni	41.56%	57.82%
	Ulcer Indexi	44.55%	61.36%
	Max daily dropi	14.37%	14.86%
	Max wkly dropi	29.63%	36.00%
5Y	Growthi	+300.99%	+63.50%
	CAGRi	+32.02%	+10.33%
	Volatilityi	102.18%	130.39%
	Sharpe ratioi	0.73	0.66
	Sortino ratioi	1.18	1.13
	Max drawdowni	90.00%	96.89%
	Current drawdowni	50.86%	71.62%
	Avg drawdowni	54.27%	64.11%
	Ulcer Indexi	59.45%	70.43%
	Max daily dropi	39.00%	45.41%
	Max wkly dropi	42.22%	68.19%
10Y	Growthi	+273.52%	+61.52%
	CAGRi	+26.01%	+9.28%
	Volatilityi	96.81%	125.37%
	Sharpe ratioi	0.67	0.63
	Sortino ratioi	1.07	1.08
	Max drawdowni	90.00%	96.89%
	Current drawdowni	50.86%	71.62%
	Avg drawdowni	50.75%	59.39%
	Ulcer Indexi	56.51%	67.71%
	Max daily dropi	39.00%	45.41%
	Max wkly dropi	42.22%	68.19%

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+1.1%HOLD

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+6.4%BUY

RGTI

+3.2%HOLD

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Business comparison

Business comparison
Category	IONQ	RGTI
Company	IonQ, Inc.	Rigetti Computing, Inc.
Sector	Technology	Technology
Industry	Computer Hardware	Computer Hardware
Core business	IonQ is a quantum computing company that uses trapped ion technology as its quantum computing platform. In trapped ion quantum computers, individual atomic ions (IonQ uses ytterbium-171 ions) are confined in electromagnetic traps and manipulated with laser pulses to perform quantum computations. Trapped ion qubits are valued for their long coherence times (maintaining quantum states longer than superconducting qubits), high gate fidelities (accuracy of quantum operations), and all-to-all connectivity (any qubit can interact directly with any other qubit without routing overhead). IonQ makes its quantum computers available via cloud access through Amazon Braket (AWS), Azure Quantum (Microsoft), and Google Cloud.	Rigetti Computing develops quantum computers using superconducting quantum circuits — the same physical approach used by IBM, Google, and most major quantum computing research efforts. Rigetti's superconducting qubits are fabricated on silicon wafers using semiconductor manufacturing techniques; the qubits (transmon qubits using Josephson junctions) operate at temperatures near absolute zero (approximately 15 millikelvin) to maintain quantum coherence. Rigetti provides cloud quantum computing access through its Quantum Cloud Services (QCS) platform and through AWS Braket. Rigetti also operates its own full-stack quantum computing manufacturing facility (Fab-1 in Fremont, California) giving it vertical integration from chip fabrication to cloud access.
Investor focus	Investors track IonQ's algorithmic qubit count (a company-defined metric intended to reflect quantum computational power), revenue growth from cloud quantum computing access (per-task fees), government contract revenue, and the company's trajectory toward quantum advantage (demonstrating computational superiority over classical computers in useful applications).	Investors track Rigetti's qubit counts and gate fidelity metrics, revenue from quantum cloud access, Fab-1 manufacturing milestones (the ability to build and iterate quantum chips quickly in-house), government research contracts, and the competitive positioning versus IBM and Google who use the same superconducting approach at much larger scale.

IONQ strengths

Trapped ion technology provides the best qubit quality (fidelity and coherence) available today — IonQ's trapped ion qubits have among the highest gate fidelities (>99.9%) and longest coherence times of any quantum computing platform; high qubit quality reduces error rates and is critical for useful quantum calculations
Multi-cloud availability (AWS, Azure, Google Cloud) maximizes enterprise accessibility — IonQ's quantum computers are accessible through all three major cloud providers; enterprises experimenting with quantum algorithms can use IonQ hardware without specialized infrastructure
IonQ has received significant government and defense research contracts — the U.S. government (DARPA, Air Force Research Lab, NSF) funds quantum computing research; IonQ has won multiple contracts worth tens of millions of dollars, providing non-dilutive revenue funding while the commercial quantum market matures

RGTI strengths

Vertical integration with Fab-1 in-house chip manufacturing allows faster design iteration — Rigetti built its own quantum chip fabrication facility; controlling the full manufacturing stack from design to fabrication enables faster qubit design iterations compared to using external chip foundries; faster iteration = faster qubit quality improvement
Superconducting approach shares technology development learnings with IBM (500+ qubit systems) and Google (Sycamore) — the superconducting qubit approach has the largest global R&D investment; while Rigetti is small versus IBM, lessons from the broader superconducting ecosystem (error correction codes, qubit designs, control electronics) benefit all superconducting players
Existing cloud access through QCS and AWS Braket provides commercial deployment infrastructure — Rigetti's cloud platform enables enterprise customers to run quantum algorithms without hardware access; cloud delivery model is the correct commercial approach for early quantum computing when hardware is expensive and access-intensive

Risks to watch — IONQ

Trapped ion qubits are more difficult to scale to large qubit counts than superconducting approaches — adding more trapped ion qubits requires complex optical systems and ion trap hardware; scaling trapped ion systems to the 1,000+ qubit systems needed for quantum advantage in practical applications is a significant engineering challenge
Quantum computing commercialization timeline is highly uncertain — despite years of investment, meaningful quantum advantage over classical computers for commercially relevant problems has not been demonstrated; investors are buying a long-dated call option on a transformational technology with no guarantee of near-term revenue inflection
Revenue is minimal relative to market capitalization — IonQ's annual revenue is in the tens of millions against a market capitalization that has at times exceeded $5B; the stock's valuation is almost entirely based on future potential rather than current financial performance

Risks to watch — RGTI

Rigetti competes directly with IBM Quantum and Google Quantum AI using the same superconducting approach — IBM has 1,000+ qubit systems and massive R&D investment; Google has demonstrated quantum computational advantage claims; Rigetti's superconducting systems are significantly behind these competitors in qubit count and fidelity
Rigetti has struggled with execution — the company has delayed qubit milestones multiple times; investor confidence in management's ability to execute roadmap commitments has been damaged by repeated timeline slippage on qubit count and fidelity targets
Financial resources are extremely limited relative to competitors — Rigetti is a small company (market cap under $1B at times) competing against IBM (which spends billions annually on quantum R&D) and Google (similar scale); Rigetti's R&D budget is orders of magnitude smaller than its primary superconducting competitors

Frequently asked questions

A qubit (quantum bit) is the fundamental unit of quantum computing — the quantum analog of a classical bit (0 or 1). While a classical bit is always either 0 or 1, a qubit can exist in a 'superposition' of 0 and 1 simultaneously (governed by quantum mechanics); this property, combined with quantum entanglement (qubits can be correlated in ways that classical bits cannot) enables certain computations to run exponentially faster on quantum computers than on classical computers for specific problem types. Trapped ion qubits (IonQ): individual ions (charged atoms) of ytterbium are suspended in electromagnetic traps (Paul traps); the qubit state (0 or 1) is encoded in electronic energy levels of the ion; laser pulses perform quantum gate operations (equivalent to logical operations); advantages — long coherence times (ions maintain quantum states for seconds versus microseconds for superconducting), high gate fidelity (>99.9%), all-to-all connectivity (any ion can interact directly with any other via the shared phonon modes of the ion chain); disadvantages — limited scalability of ion chains (currently 10s of qubits per chain), slow gate times (microseconds for laser pulses vs. nanoseconds for superconducting gates), complex laser optics required. Superconducting qubits (Rigetti, IBM, Google): qubits are built on silicon wafers using microwave-frequency superconducting circuits (transmon qubits based on Josephson junctions — devices where current flows without resistance at cryogenic temperatures); the qubit state is encoded in microwave photon energy levels; advantages — faster gate times (nanosecond operations enable fast quantum circuits), scalable fabrication (same semiconductor techniques as classical chips — potentially enabling thousands of qubits on a chip), rapidly improving coherence via error correction; disadvantages — shorter coherence times than trapped ions, require refrigeration to 15 millikelvin (near absolute zero), connectivity is typically nearest-neighbor on a 2D grid requiring routing overhead.

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