Usage and costs

Looking for usage documentation? Check out Classification, Thinking mode and KV cache.

`estimate_cost`

Estimate one operation without uploading data or consuming quota. Only raw row/column counts and the supplied configuration are sent. The server resolves omitted model/ensemble defaults and returns them in result.inputs alongside estimated_cost and pricing_version. Quota v3 must be enabled on the server. Costs are tokens for quota_v3 and legacy cell-prediction credits for legacy_v2. thinking_fit takes no X_test; its default effort is medium. For thinking_predict, supply the fitted model’s version and actual per-base-estimator count. cache_predict assumes a cache hit; fallback or different fitted estimator counts can change the final charge. A quote does not guarantee model access or dataset eligibility.

estimate_cost(
    X_train: np.ndarray | pd.DataFrame,
    X_test: np.ndarray | pd.DataFrame | None = None,
    *,
    model_version: str | None = None,
    operation: Literal["predict", "thinking_fit", "thinking_predict", "cache_predict"] = "predict",
    n_estimators: int | None = None,
    thinking_effort: Literal["medium", "high"] | None = None,
) -> EstimateCostResponse

Parameters

Parameter	Type	Default	Description
`X_train`	`np.ndarray \| pd.DataFrame`	Required	Training data; only its shape is used.
`X_test`	`np.ndarray \| pd.DataFrame \| None`	`None`	Test data; only its shape is used. Omit for `thinking_fit`.
`model_version`	`str \| None`	`None`	Model version to price. Resolved by the server if `None`.
`operation`	`Literal[“predict”, “thinking_fit”, “thinking_predict”, “cache_predict”]`	`"predict"`	Operation to price.
`n_estimators`	`int \| None`	`None`	Number of estimators. Resolved by the server if `None`.
`thinking_effort`	`Literal[“medium”, “high”] \| None`	`None`	Effort level for thinking operations.

Returns

Type	Description
`EstimateCostResponse`	The server’s cost estimate.

Raises ValueError If an input is not two-dimensional or has invalid row or feature counts, if X_train and X_test differ in feature count, if X_test is given for thinking_fit, or if n_estimators is not a positive integer.

`EstimateCostResponse`

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`EstimateCostRequest`

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`QuotaOperation`

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`get_api_usage`

View source

Fetches and formats the current API usage statistics for the user.

get_api_usage() -> str

Returns

Type	Description
`str`	A human-readable string detailing current credit usage, the total limit, and when the limit resets.

Reference

tabpfn

tabpfn-client

tabpfn-extensions

REST API

`estimate_cost`

`EstimateCostResponse`

`EstimateCostRequest`

`QuotaOperation`

`get_api_usage`

​estimate_cost

​EstimateCostResponse

​EstimateCostRequest

​QuotaOperation

​get_api_usage

`estimate_cost`

`EstimateCostResponse`

`EstimateCostRequest`

`QuotaOperation`

`get_api_usage`