Recommend

Advanced · technical

Paste your raw circuit metrics (qubit count, depth, 2-qubit gates) and Qlro ranks every device. For domain users, the industry workloads entry point is faster — pick a business problem and we generate the circuit for you.

Your Workload Spec

WCPP Pipeline

Profiling workload...
Computing axis weights...
Scoring 13 devices...
Applying geometric mean composition...

Your Workload Requirements

What your workload asks for across the 4 capability axes

Dominant axis: Φ (Coherence) at 39%

Γ Connectivity
21%
Φ Coherence
39%
F Fidelity
39%
T Throughput
0%

Device Match

How each device's capabilities fit your requirements

Best Match

H2-2

quantinuum · 56Q
$125K+/mo /runQueue: N/A
0.8423
fit score
PARTIALLY ESTIMATED
Γ
0.88w=0.21
Φ
0.75w=0.39
F
0.94w=0.39
T
0.51w=0.00
Second Best

ibm_boston

ibm · 156Q
Free /runQueue: ~2 min
0.6297
fit score
Γ
0.82w=0.21
Φ
0.42w=0.39
F
0.82w=0.39
T
0.51w=0.00
Why H2-2 wins
1.

H2-2 leads on Φ (Coherence) — the dominant axis for this workload (39% weight). Its coherence score (0.75) is 77% higher than ibm_boston.

2.

Total fit score is 1.34× higher than the next alternative. Under the WCPP geometric mean, this gap reflects compound advantages across multiple axes — not a single metric.

Audit-ready decision record

Export this recommendation as a signed PDF

Freeze the current inputs + ranking + reasoning + Metriq snapshot provenance into an immutable decision record with a citable URL. Procurement / audit / research-justification workflows can attach the PDF to demonstrate how the device choice was made.

Includes content hash + citable URL + optional snapshot DOI.

H2-2 has partially estimated axis values (population priors). Actual performance may differ. Validate empirically before committing.

Powered by WCPP v0.8 · Data from Metriq