Key Specifications
Full Specifications
| Qubit Specs | |
| Physical Qubits | 4,400 qubits |
| Technology | Annealing |
| Connectivity | Zephyr |
| Connectivity Degree | 20 neighbors |
| Gate Performance | |
| Features | |
| Mid-Circuit Measurement | No |
| Classical Feedback | No |
| Dynamic Circuits | No |
| Error Mitigation | Not available |
| System | |
| Cooling Method | dilution refrigerator |
| Operating Temp | 0.015 K |
| Native Gates | QUBO, ISING |
| SDK Compatibility | |
| D-Wave Ocean Amazon Braket SDK | |
Cloud Access & Pricing
| Platform | Model | Price | Status | |
|---|---|---|---|---|
| D-Wave Leap Advantage2_prototype2.2 | Per Minute | $2,000.00/min | Available | Run on D-Wave |
| Amazon Braket .../d-wave/Advantage_system6 | Per Task | $0.3000/task Best value
min $0.3000/job
| Available | Run on Amazon |
| qBraid dwave_advantage2_prototype | Credits | $0.3000/task
min $0.3000/job
| Available | Run on qBraid |
Free tiers available:
D-Wave Leap: 1 minute of QPU time per month for academic users; developer plan available
Amazon Braket: Free Simulator usage (SV1, TN1, DM1); no free QPU time
qBraid: 300 qBraid credits on signup; credits can be used across multiple QPU backends
Recommended Use Cases
Combinatorial optimization problems including logistics, scheduling, and portfolio optimization.
Route optimization, fleet management, and supply chain problems.
Risk analysis, Monte Carlo simulation, and derivative pricing acceleration.
Quantum-enhanced ML models, variational classifiers, and kernel methods.
About Annealing Technology
Quantum annealers are special-purpose quantum devices that solve optimization problems by slowly evolving a quantum system from an initial superposition state to the ground state of a problem Hamiltonian encoding the optimization objective. D-Wave systems use superconducting flux qubits in a programmable Ising model. Unlike gate-based QPUs, annealers do not perform universal quantum computation.
Very large qubit counts (5000+ physical qubits), fast sampling times (~microseconds per anneal), and a well-developed software ecosystem (D-Wave Ocean SDK) optimized for combinatorial optimization problems in logistics, finance, and scheduling.
Limited connectivity between qubits requires problem embedding that can consume many physical qubits to represent a single logical variable. Not universal — cannot run arbitrary quantum algorithms. Quantum advantage over classical optimization solvers has not been conclusively demonstrated.
Not applicable — stochastic sampling approach
20 µs per anneal (full problem solve)
Compare D-Wave Advantage2 With Other QPUs
Frequently Asked Questions
How much does it cost to use D-Wave Advantage2?
D-Wave Advantage2 is available on 3 cloud platforms. The most accessible pricing starts from $0.3000/task via Amazon Braket. Pricing models vary by platform and may include per-shot, per-second, or gate-based billing.
What is the gate fidelity of D-Wave Advantage2?
Gate fidelity data for D-Wave Advantage2 has not been publicly disclosed. This is common for early-stage or specialized QPUs.
Which cloud platforms offer D-Wave Advantage2?
D-Wave Advantage2 is available through: D-Wave Leap, Amazon Braket, qBraid.
What qubit technology does D-Wave Advantage2 use?
D-Wave Advantage2 uses Annealing qubit technology. Very large qubit counts (5000+ physical qubits), fast sampling times (~microseconds per anneal), and a well-developed software ecosystem (D-Wave Ocean SDK) optimized for combinatorial optimization problems in logistics, finance, and scheduling. Operating temperature: ~15 mK (dilution refrigerator).
What is the Quantum Volume of D-Wave Advantage2?
Quantum Volume has not been published for D-Wave Advantage2. Quantum annealers use different performance benchmarks such as time-to-solution on optimization problems.
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