Billing and Cost Control

QCOS implements a rigorous cost governance structure for corporate quantum environments. Every physical execution consumes billing credits based on shots, gate count, and active qubits. Using the client.billing and client.ledger namespaces, you can calculate cost estimations, download corporate pricebooks, run cost comparison scenarios, and generate audit-ready usage reports.

1. Calculating Execution Credit Estimates

Before executing large workloads on physical QPUs (such as AWS Braket or IBM Quantum), estimate the cost programmatically to prevent unexpected charges or quota violations:

from softqcos_sdk import QCOSClient

client = QCOSClient()

# Estimate cost for running an 8-qubit circuit with 100,000 shots
estimation = client.ledger.estimate(
    backend="ibm_brisbane",
    shots=100000,
    num_qubits=8
)
print("--- Compute Estimation Report ---")
print(estimation)

# The job submission response itself also reports cost state up front:
job = client.jobs.submit(qasm=qasm, backend_id="ibm_brisbane", shots=100000)
print(f"Required Credits:  {job['credits_required']}")
print(f"Cost basis:        {job['cost_basis']}")
print(f"Approval Required: {job['approval_required']}")

2. Comparing Price Scenarios

If you want to choose the most cost-effective hardware for a specific circuit depth and shot size, use the scenarios engine to compare providers side-by-side:

# ROI scenario analysis: conservative / base / aggressive, side by side
scenarios = client.billing.scenarios(
    provider="ibm",
    projects_per_year=4,
    experiments_per_project=12,
    shots_per_eval=50000
)

for name in ("conservative", "base", "aggressive"):
    print(name, scenarios[name])
print("Pricebook version:", scenarios["pricebook_version"])

# Provider comparison for a given workload volume
comparison = client.billing.compare_providers(evaluations=100, shots_per_eval=1000)
print(comparison)

3. Retrieving Corporate Pricebooks

To print or audit all unit credit costs currently configured for your organization:

# Fetch the ROI pricebook (the assumptions the ROI model runs on)
pricebook = client.billing.pricebook()
print(pricebook)

4. Querying Ledger Audits & Usage Reports

To retrieve detailed usage metrics of compute credits consumed by user, project, and dataset:

# Retrieve current usage data from the ledger
usage_report = client.ledger.usage()
print(usage_report)

# Audit and chargeback reports
audit = client.ledger.audit()

Python SDK

Billing & Cost Control

Billing and Cost Control

1. Calculating Execution Credit Estimates

2. Comparing Price Scenarios

3. Retrieving Corporate Pricebooks

4. Querying Ledger Audits & Usage Reports

​Billing and Cost Control

​1. Calculating Execution Credit Estimates

​2. Comparing Price Scenarios

​3. Retrieving Corporate Pricebooks

​4. Querying Ledger Audits & Usage Reports

Billing and Cost Control

1. Calculating Execution Credit Estimates

2. Comparing Price Scenarios

3. Retrieving Corporate Pricebooks

4. Querying Ledger Audits & Usage Reports