Cost Estimation

Before executing a quantum program, you can estimate the cost using estimate_sample_cost and estimate_sample_batch_cost. These functions return a CostEstimateResult with cost (in USD) and currency fields. Cost estimation is supported for all quantum providers that Classiq integrates with. Each provider uses its own pricing model.

Basic Usage

Single Sample Cost

Use estimate_sample_cost to estimate the cost of sampling a quantum program with given execution preferences:

from classiq import (
    ClassiqBackendPreferences,
    ClassiqSimulatorBackendNames,
    ExecutionPreferences,
    create_model,
    estimate_sample_cost,
    synthesize,
)
from classiq.qmod.builtins.operations import allocate
from classiq.qmod.qfunc import qfunc
from classiq.qmod.qmod_variable import Output, QBit


@qfunc
def main(res: Output[QBit]) -> None:
    allocate(1, res)


qmod = create_model(main)
qprog = synthesize(qmod)

execution_preferences = ExecutionPreferences(
    num_shots=100,
    backend_preferences=ClassiqBackendPreferences(
        backend_name=ClassiqSimulatorBackendNames.SIMULATOR
    ),
)

result = estimate_sample_cost(qprog, execution_preferences)
print(f"Estimated cost: {result.cost} {result.currency}")

Batch Cost Estimation

Use estimate_sample_batch_cost to estimate the cost of sampling with multiple parameter sets:

from classiq import (
    ClassiqBackendPreferences,
    ClassiqSimulatorBackendNames,
    estimate_sample_batch_cost,
    synthesize,
)

qprog = synthesize(qmod)

result = estimate_sample_batch_cost(
    qprog,
    execution_backend=ClassiqBackendPreferences(
        backend_name=ClassiqSimulatorBackendNames.SIMULATOR
    ),
    shots=100,
    params=[{}, {}],  # Two parameter sets
)
print(f"Estimated batch cost: {result.cost} {result.currency}")

Provider-Specific Usage

Cost estimation works with the same backend preferences you use for execution. Configure the backend for your target provider and pass it to the estimation functions.

Classiq Simulators

Classiq simulators support cost estimation without provider credentials.

from classiq import (
    ClassiqBackendPreferences,
    ClassiqSimulatorBackendNames,
    ExecutionPreferences,
    estimate_sample_cost,
)

# All Classiq simulators are supported
backends = [
    ClassiqSimulatorBackendNames.SIMULATOR,
    ClassiqSimulatorBackendNames.SIMULATOR_STATEVECTOR,
    ClassiqSimulatorBackendNames.SIMULATOR_DENSITY_MATRIX,
    ClassiqSimulatorBackendNames.SIMULATOR_MATRIX_PRODUCT_STATE,
]

for backend_name in backends:
    prefs = ExecutionPreferences(
        num_shots=100,
        backend_preferences=ClassiqBackendPreferences(backend_name=backend_name),
    )
    result = estimate_sample_cost(qprog, prefs)
    print(f"{backend_name}: {result.cost} {result.currency}")

Amazon Braket

Cost estimation supports both Braket simulators (SV1, TN1, dm1) and QPUs (e.g., Aspen-11, Lucy).

from classiq import (
    AwsBackendPreferences,
    ExecutionPreferences,
    estimate_sample_cost,
)

# Braket simulators
prefs = ExecutionPreferences(
    num_shots=100,
    backend_preferences=AwsBackendPreferences(
        backend_name="SV1",
        run_via_classiq=True,
    ),
)
result = estimate_sample_cost(qprog, prefs)

# Braket QPU (e.g., Ankaa-3)
prefs_qpu = ExecutionPreferences(
    num_shots=1000,
    backend_preferences=AwsBackendPreferences(
        backend_name="Ankaa-3",
        run_via_classiq=True,
    ),
)
result_qpu = estimate_sample_cost(qprog, prefs_qpu)

When using your own AWS credentials, omit run_via_classiq and provide aws_access_key_id, aws_secret_access_key, s3_bucket_name, and s3_folder.

IonQ

from classiq import (
    IonqBackendPreferences,
    ExecutionPreferences,
    estimate_sample_cost,
)

# IonQ simulator
prefs = ExecutionPreferences(
    num_shots=100,
    backend_preferences=IonqBackendPreferences(
        backend_name="simulator",
        run_via_classiq=True,
    ),
)
result = estimate_sample_cost(qprog, prefs)

# IonQ QPU (e.g., Forte-1)
prefs_qpu = ExecutionPreferences(
    num_shots=1000,
    backend_preferences=IonqBackendPreferences(
        backend_name="qpu.Forte-1",
        run_via_classiq=True,
    ),
)
result_qpu = estimate_sample_cost(qprog, prefs_qpu)

Azure Quantum

from classiq import (
    AzureBackendPreferences,
    ExecutionPreferences,
    estimate_sample_cost,
)

# Azure IonQ simulator
prefs = ExecutionPreferences(
    num_shots=100,
    backend_preferences=AzureBackendPreferences(
        backend_name="ionq.simulator",
    ),
)
result = estimate_sample_cost(qprog, prefs)

# Azure Quantinuum simulator
prefs_quantinuum = ExecutionPreferences(
    num_shots=100,
    backend_preferences=AzureBackendPreferences(
        backend_name="quantinuum.sim.h1-1e",
    ),
)
result_quantinuum = estimate_sample_cost(qprog, prefs_quantinuum)

When using run_via_classiq, omit credentials. Otherwise, provide Azure credentials.

Summary by Provider

Provider	Backend examples
Classiq	simulator, simulator_statevector, simulator_density_matrix, simulator_matrix_product_state
Amazon Braket	SV1, TN1, dm1 (simulators); Aspen-11, Lucy (QPUs)
IonQ	simulator, qpu.aria-1, qpu.forte-1
Azure	ionq.simulator, quantinuum.sim.h1-1e, rigetti.sim.qvm

Use run_via_classiq=True when available to estimate costs without providing provider credentials. Your allocated budget is used for execution.

API Reference

See the execution SDK reference for full details on estimate_sample_cost, estimate_sample_batch_cost, and CostEstimateResult.

AI

Authentication

Modeling

Synthesis

Execution

Analysis

Error Correction

Studio

Applications

Basic Usage

Single Sample Cost

Batch Cost Estimation

Provider-Specific Usage

Classiq Simulators

Amazon Braket

IonQ

Azure Quantum

Summary by Provider

API Reference