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API Reference
Predictions
Adme

Estimate cost for an ADME prediction

predictions.adme.estimate_cost(AdmeEstimateCostParams**kwargs) -> AdmeEstimateCostResponse
POST/compute/v1/predictions/adme/estimate-cost

Estimate the cost of an ADME prediction without creating any resource or consuming GPU.

ParametersExpand Collapse
input: Input
molecules: Iterable[InputMolecule]

Molecules to score (1-128 per request). Results are returned in the same order as this list.

smiles: str

SMILES string of the molecule to predict ADME properties for.

minLength1
id: Optional[str]

Optional client-provided identifier. Returned as external_id in the matching output item.

minLength1
maxLength128
model: Literal["adme-v1"]

Model to use for prediction

idempotency_key: Optional[str]

Client-provided key to prevent duplicate submissions on retries

maxLength255
workspace_id: Optional[str]

Target workspace ID (admin keys only; ignored for workspace keys)

ReturnsExpand Collapse
class AdmeEstimateCostResponse: …

Estimate response with monetary values encoded as decimal strings to preserve precision.

breakdown: Breakdown

Cost breakdown for the billed application.

application: Literal["structure_and_binding", "small_molecule_design", "small_molecule_library_screen", 4 more]
One of the following:
"structure_and_binding"
"small_molecule_design"
"small_molecule_library_screen"
"protein_design"
"protein_redesign"
"protein_library_screen"
"adme"
cost_per_unit_usd: str

Estimated cost per displayed unit as a decimal string, rounded up to 4 decimal places. This may include token-size multipliers or generation overhead; estimated_cost_usd is the authoritative total.

num_units: int

Number of billable units in the estimate. The unit depends on the endpoint: samples for structure-and-binding, molecules for ADME, and requested proteins or molecules for design/screen endpoints.

disclaimer: str
estimated_cost_usd: str

Estimated total cost as a decimal string

Estimate cost for an ADME prediction

import os
from boltz_api import Boltz

client = Boltz(
    api_key=os.environ.get("BOLTZ_API_KEY"),  # This is the default and can be omitted
)
response = client.predictions.adme.estimate_cost(
    input={
        "molecules": [{
            "smiles": "x"
        }]
    },
    model="adme-v1",
)
print(response.breakdown)
{
  "breakdown": {
    "application": "structure_and_binding",
    "cost_per_unit_usd": "0.0500",
    "num_units": 1
  },
  "disclaimer": "This is an estimate only and may differ from your actual charges. Final billing is based on exact token counts computed at run time. For large library screens, the estimate is extrapolated from a sample and may be less accurate for highly variable inputs.",
  "estimated_cost_usd": "0.0500"
}
Returns Examples
{
  "breakdown": {
    "application": "structure_and_binding",
    "cost_per_unit_usd": "0.0500",
    "num_units": 1
  },
  "disclaimer": "This is an estimate only and may differ from your actual charges. Final billing is based on exact token counts computed at run time. For large library screens, the estimate is extrapolated from a sample and may be less accurate for highly variable inputs.",
  "estimated_cost_usd": "0.0500"
}