Quantum computer roadmaps for various qubit modalities and vendors, including references to official sources. Qubit modalities include superconductors, trapped ions, neutral atoms, quantum dots, photonics, spin (i.e. nitrogen vacancy centres in diamond), NMR, and quantum annealers. For each quantum computer generation, the number of physical qubits, and, where available, quantum volume, logical qubits, relaxation times, and gate fidelity statistics are listed.
A visual representation of this data is available in Roads to Quantum Advantage. For more details on the different technologies, please check What is Quantum Computing?
| Organization | Modality | Designation | Year | Qubits (physical)The actual number of physical qubits on the quantum device. This is the maximally addressable qubits in quantum algorithms, although in practice that number is lower due ancillary qubits needed in error correction schemes. | Qubits (logical)The number of logical (a.k.a. algorithmic) qubits that can be addressed in quantum algorithms. Ideally, this is the base-2 logarithm of the quantum volume. | Quantum volumeA NISQ-era metric that assumes square circuits of qubits and measures the effective number of qubits multiplied by the circuit depth (i.e. number of layers) in which quantum algorithms can be run within acceptable tolerances. | QumodesNumber of quantized beams of (squeezed) light in continuous-variable photonic quantum computers. | T1 (μs)The T1 time is the relaxation time, which measures the characteristic time to go from the |1⟩ to the |0⟩ state. | T2 (μs)T2 measures characteristic time of decoherence due to dephasing, the randomization of the qubit phase, and phase breaking, the loss of superposition. |
Fidelity
|
Notes |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Alibaba | Superconductors | 2018/Q1 | 11 | 2022/Q2 | 2 | 99.97% (1Q) 99.72% (2Q) |
Fluxonium qubits | ||||
| Alpine Quantum Technologies | Tapped ions | Pine | 2022/Q1 | 20 | |||||||
| Atom Computing | Neutral atoms | Phoenix | 2021/Q3 | 100 | |||||||
| 2024 | 1,180 | ||||||||||
| Baidu | Superconductors | Qian Shi | 2022/Q3 | 10 | 31.0 | 8.7 | 99.8% (1Q) 96.60% (2Q) |
Median instead of mean T1/T2 values | |||
| ColdQuanta | Neutral atoms | 2021/Q3 | 100 | ||||||||
| 2022 | 300 | ||||||||||
| Hilbert | 2024 | 1,000 | |||||||||
| D-Wave | Annealer | 2007 | 28 | ||||||||
| One | 2011/Q2 | 128 | |||||||||
| Two | 2013/Q2 | 512 | |||||||||
| 2X | 2015/Q3 | 1,152 | |||||||||
| 2000Q | 2017/Q1 | 2,048 | |||||||||
| Advantage | 2020/Q3 | 5,760 | |||||||||
| Advantage 2 | 2024 | 7,440 | |||||||||
| Fujitsu | Superconductors | 2023 | 64 | ||||||||
| 2026 | 1,000 | ||||||||||
| Superconductors | Foxtail | 2016 | 9 | ||||||||
| 2017 | 20 | 99.5% (2Q) | |||||||||
| Bristlecone | 2018/Q1 | 72 | 99.9% (1Q) 99.4% (2Q) 99.0% (readout) |
||||||||
| Sycamore | 2019/Q4 | 53 | 99.85% (1Q) 99.35% (2Q) |
1 qubit out of 54 defective, so 53 'effective' qubits | |||||||
| Sycamore | 2023/Q1 | 72 | >99.85% (1Q) 99.64% (2Q) 96.9% (readout) |
1000:1 error correction overhead estimate unaltered due to extrapolation to distance-25 surface code | |||||||
| 2029 | 1,000,000 | 1,000 | 1000:1 error correction | ||||||||
| IBM | Superconductors | (Tenerife) | 2017/Q1 | 5 | 2 | 4 | 51.1 | 25.9 | 99.90% (gate) 98.64% (readout) |
||
| (Tokyo) | 2018/Q1 | 20 | 3 | 8 | 84.3 | 49.6 | 99.81% (gate) 93.21% (readout) |
||||
| Falcon (Johannesburg) | 2019/Q4 | 27 | 4 | 16 | |||||||
| Hummingbird (Raleigh) | 2020/Q1 | 65 | 5 | 32 | |||||||
| Falcon R4 (Montreal) | 2020/Q3 | 27 | 7 | 128 | 109.09 | 97.17 | 99.96% (1Q) 98.58% (2Q) 97.69% (SPAM) |
||||
| Eagle | 2021/Q4 | 127 | 6 | 64 | |||||||
| Falcon R10 (Prague) | 2022/Q2 | 27 | 9 | 512 | |||||||
| Osprey | 2022/Q4 | 433 | 10 | 1,024 | Estimated QV based on doubling every 6–12 months | ||||||
| Condor | 2023/Q4 | 1,121 | 12 | 4,096 | |||||||
| Flamingo | 2024 | 1,386 | 14 | 16,384 | |||||||
| Kookaburra | 2025 | 4,158 | 16 | 65,536 | |||||||
| 2030 | 17 | 100,000 | |||||||||
| Intel | Quantum dots | 2018/Q2 | 2 | ||||||||
| 2022/Q1 | 3 | ||||||||||
| Tunnel Falls | 2022/Q4 | 12 | |||||||||
| Superconductors | 2017/Q4 | 17 | |||||||||
| Tangle Lake | 2018/Q3 | 49 | |||||||||
| IonQ | Trapped ions | Harmony | 2019 | 11 | 3 | 8 | 99.72% (1Q) 96.54% (2Q) 99.71% (SPAM) |
||||
| Aria | 2020/Q4 | 32 | 22 | 4,000,000 | 99.98% (1Q) 99.3% (2Q) |
13:1 error correction | |||||
| Forte | 2022/Q2 | 32 | 25 | ||||||||
| 2023 | 29 | ||||||||||
| 2024 | 35 | ||||||||||
| 2025 | 64 | ||||||||||
| 2026 | 256 | ||||||||||
| 2027 | 1,024 | ||||||||||
| IQM | Superconductors | Spark | 2021/Q4 | 5 | |||||||
| 2023/Q4 | 20 | ||||||||||
| Radiance | 2024 | 54 | Expected Q3 | ||||||||
| Radiance | 2025 | 150 | Expected Q1 | ||||||||
| Pasqal | Neutral atoms | 2022/Q3 | 324 | Lab hardware, not commercial yet | |||||||
| 2024 | 1,000 | ||||||||||
| OQC | Superconductors | Lucy | 2022/Q1 | 8 | 1 | 2 | 99.91% (1Q) 94.16% (2Q) 90.44% (SPAM) |
||||
| Origin Quantum | Superconductors | Wuyuan I | 2020/Q3 | 6 | Wuyuan II | 2023/Q1 | 24 | ||||
| PsiQuantum | Photonics | 2025 | 1,000,000 | 300 | |||||||
| Quandela | Photonics | Ascella | 2022/Q4 | 5 | |||||||
| 2023 | 12 | ||||||||||
| Quantinuum | Trapped ions | H1-1 | 2020/Q3 | 20 | 7 | 128 | |||||
| H1-1 | 2021/Q1 | 20 | 9 | 512 | 99.97% (1Q) 99.5% (2Q) |
||||||
| H1-1 | 2021/Q3 | 10 | 10 | 1,024 | |||||||
| H1-2 | 2021/Q4 | 20 | 11 | 2,048 | |||||||
| H1-2 | 2022/Q2 | 12 | 12 | 4,096 | |||||||
| H1-1 | 2022/Q3 | 20 | 13 | 8,192 | 99.9959% (1Q) 99.71% (2Q) 99.72% (SPAM) |
Arbitrary-angle gates | |||||
| H1-1 | 2023/Q1 | 20 | 15 | 32,768 | 99.9955% (1Q) 99.795% (2Q) 99.69% (SPAM) |
Arbitrary-angle gates | |||||
| H2-1 | 2023/Q2 | 32 | 16 | 65,536 | 99.997% (1Q) 99.8% (2Q) 99.8% (SPAM) |
All-to-all connectivity | |||||
| H3 | 2025 | 17 | 100,000 | Estimated QV based on 5× each year | |||||||
| H4 | 2027 | 21 | 500,000 | ||||||||
| H5 | 2029 | 24 | 2,500,000 | ||||||||
| Quantum Brilliance | Spin | Gen1 | 2021/Q2 | 5 | |||||||
| 50 | |||||||||||
| QuantWare | Supercondcutors | Tenor | 2023/Q1 | 64 | |||||||
| QuEra | Neutral atoms | Aquila | 2023/Q4 | 256 | 99.9% (initialization) 62% (readout) |
Post-computation QEC on non-universal gate set with [[8,3,2]] colour code only | |||||
| 2024 | 256 | 10 | Built-in QEC | ||||||||
| 2025 | 3,000 | 30 | Built-in QEC | ||||||||
| 2026 | 10,000 | 100 | Built-in QEC | ||||||||
| 2025 | 1,024 | ||||||||||
| QuiX | Photonics | 2020/Q4 | 12 | ||||||||
| 2022/Q1 | 20 | ||||||||||
| 2023 | 50 | ||||||||||
| Rigetti | Superconductors | Agave | 2017/Q2 | 8 | 13.38 | 15.05 | 95% (1Q) 87% (2Q) |
||||
| Aspen-1 | 2018/Q4 | 16 | 8 | 12 | 93.23% (1Q) 90.84% (2Q) |
||||||
| Aspen-4 | 2019/Q1 | 13 | 3 | 8 | 30.47 | 20.13 | 99.88% (1Q) 94.42% (2Q) |
||||
| Aspen-9 | 2021/Q2 | 32 | 3 | 8 | 33 | 16 | 99.39% (1Q) 94.28% (2Q" |
Median instead of mean values | |||
| Aspen-11 | 2021/Q4 | 40 | 3 | 8 | 30 | 14 | 99.55% (1Q) 92.15% (2Q) 96.78% (SPAM) |
||||
| Aspen-M | 2022/Q1 | 80 | 3 | 8 | 29 | 22 | 98.94% (1Q) 91.13% (2Q) 96.95% (SPAM) |
||||
| Lyra | 2023 | 336 | |||||||||
| 2025 | 1,000 | ||||||||||
| 2027 | 4,000 | ||||||||||
| SpinQ | NMR | Gemini | 2021 | 2 | |||||||
| Triangulum | 2022 | 3 | |||||||||
| SQC | Quantum dots | 2023 | 10 | ||||||||
| 2030 | 100 | ||||||||||
| USTC | Photonics | Jiuzhang | 2020/Q4 | 76 | |||||||
| Jiuzhang 2.0 | 2021/Q4 | 113 | |||||||||
| Jiuzhang 3.0 | 2023/Q4 | 255 | |||||||||
| Superconductors | Zuchongzhi | 2021/Q2 | 66 | ||||||||
| Zuchongzhi 2 | 2023/Q2 | 176 | |||||||||
| Xanadu | Photonics | X2 | 2018 | 2 | |||||||
| X12 | 2019 | 12 | |||||||||
| X24 | 2020 | 24 | |||||||||
| Borealis | 2022/Q2 | 216 |