diff --git a/ml_peg/analysis/non_covalent_interactions/NCIA_HB300SPXx10/analyse_NCIA_HB300SPXx10.py b/ml_peg/analysis/non_covalent_interactions/NCIA_HB300SPXx10/analyse_NCIA_HB300SPXx10.py
new file mode 100644
index 000000000..fc62b9669
--- /dev/null
+++ b/ml_peg/analysis/non_covalent_interactions/NCIA_HB300SPXx10/analyse_NCIA_HB300SPXx10.py
@@ -0,0 +1,177 @@
+"""Analyse NCIA HB300SPXx10 benchmark."""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+from ase import units
+from ase.io import read, write
+import pytest
+
+from ml_peg.analysis.utils.decorators import (
+    build_table,
+    plot_density_scatter,
+)
+from ml_peg.analysis.utils.utils import build_d3_name_map, load_metrics_config, mae
+from ml_peg.app import APP_ROOT
+from ml_peg.calcs import CALCS_ROOT
+from ml_peg.models.get_models import load_models
+from ml_peg.models.models import current_models
+
+MODELS = load_models(current_models)
+D3_MODEL_NAMES = build_d3_name_map(MODELS)
+
+EV_TO_KCAL = units.mol / units.kcal
+CALC_PATH = CALCS_ROOT / "non_covalent_interactions" / "NCIA_HB300SPXx10" / "outputs"
+OUT_PATH = APP_ROOT / "data" / "non_covalent_interactions" / "NCIA_HB300SPXx10"
+
+METRICS_CONFIG_PATH = Path(__file__).with_name("metrics.yml")
+DEFAULT_THRESHOLDS, DEFAULT_TOOLTIPS, DEFAULT_WEIGHTS = load_metrics_config(
+    METRICS_CONFIG_PATH
+)
+
+
+def labels() -> list:
+    """
+    Get list of system names.
+
+    Returns
+    -------
+    list
+        List of all system names.
+    """
+    for model in MODELS:
+        labels_list = sorted([path.stem for path in (CALC_PATH / model).glob("*.xyz")])
+        break
+    return labels_list
+
+
+@pytest.fixture
+def interaction_energies() -> dict[str, list]:
+    """
+    Get interaction energies for all systems.
+
+    Returns
+    -------
+    dict[str, list]
+        Dictionary of all reference and predicted interaction energies.
+    """
+    results = {"ref": []} | {mlip: [] for mlip in MODELS}
+
+    ref_stored = False
+
+    for model_name in MODELS:
+        for label in labels():
+            atoms = read(CALC_PATH / model_name / f"{label}.xyz")
+            if not ref_stored:
+                results["ref"].append(atoms.info["ref_int_energy"] * EV_TO_KCAL)
+
+            results[model_name].append(atoms.info["model_int_energy"] * EV_TO_KCAL)
+
+            # Write structures for app
+            structs_dir = OUT_PATH / model_name
+            structs_dir.mkdir(parents=True, exist_ok=True)
+            write(structs_dir / f"{label}.xyz", atoms)
+
+        ref_stored = True
+    return results
+
+
+@pytest.fixture
+@plot_density_scatter(
+    filename=OUT_PATH / "figure_ncia_hb300spxx10_density.json",
+    title="Interaction energy density plot",
+    x_label="Reference energy / kcal/mol",
+    y_label="Predicted energy / kcal/mol",
+    annotation_metadata={"system_count": "Systems"},
+)
+def interaction_density(interaction_energies: dict[str, list]) -> dict[str, dict]:
+    """
+    Build density scatter inputs for interaction energies.
+
+    Parameters
+    ----------
+    interaction_energies
+        Reference and predicted interaction energies per model.
+
+    Returns
+    -------
+    dict[str, dict]
+        Mapping of model names to density-plot payloads.
+    """
+    ref_vals = interaction_energies["ref"]
+    density_inputs: dict[str, dict] = {}
+    for model_name in MODELS:
+        preds = interaction_energies.get(model_name, [])
+        density_inputs[model_name] = {
+            "ref": ref_vals,
+            "pred": preds,
+            "meta": {"system_count": len([val for val in preds if val is not None])},
+        }
+    return density_inputs
+
+
+@pytest.fixture
+def get_mae(interaction_energies) -> dict[str, float]:
+    """
+    Get mean absolute error for energies.
+
+    Parameters
+    ----------
+    interaction_energies
+        Dictionary of reference and predicted energies.
+
+    Returns
+    -------
+    dict[str, float]
+        Dictionary of predicted energy errors for all models.
+    """
+    results = {}
+    for model_name in MODELS:
+        results[model_name] = mae(
+            interaction_energies["ref"], interaction_energies[model_name]
+        )
+    return results
+
+
+@pytest.fixture
+@build_table(
+    filename=OUT_PATH / "ncia_hb300spxx10_metrics_table.json",
+    metric_tooltips=DEFAULT_TOOLTIPS,
+    thresholds=DEFAULT_THRESHOLDS,
+    mlip_name_map=D3_MODEL_NAMES,
+)
+def metrics(get_mae: dict[str, float]) -> dict[str, dict]:
+    """
+    Get all metrics.
+
+    Parameters
+    ----------
+    get_mae
+        Mean absolute errors for all models.
+
+    Returns
+    -------
+    dict[str, dict]
+        Metric names and values for all models.
+    """
+    return {
+        "MAE": get_mae,
+    }
+
+
+def test_ncia_hb300spxx10(
+    metrics: dict[str, dict],
+    interaction_density: dict[str, dict],
+) -> None:
+    """
+    Run NCIA HB300SPXx10 test.
+
+    Parameters
+    ----------
+    metrics
+        All new benchmark metric names and dictionary of values for each model.
+    interaction_density
+        Density-scatter inputs for all models (drives saved plots).
+    """
+    return
diff --git a/ml_peg/analysis/non_covalent_interactions/NCIA_HB300SPXx10/metrics.yml b/ml_peg/analysis/non_covalent_interactions/NCIA_HB300SPXx10/metrics.yml
new file mode 100644
index 000000000..45388b831
--- /dev/null
+++ b/ml_peg/analysis/non_covalent_interactions/NCIA_HB300SPXx10/metrics.yml
@@ -0,0 +1,7 @@
+metrics:
+  MAE:
+    good: 0.0
+    bad: 10
+    unit: kcal/mol
+    tooltip: Mean Absolute Error for all systems
+    level_of_theory: CCSD(T)
diff --git a/ml_peg/app/non_covalent_interactions/NCIA_HB300SPXx10/app_NCIA_HB300SPXx10.py b/ml_peg/app/non_covalent_interactions/NCIA_HB300SPXx10/app_NCIA_HB300SPXx10.py
new file mode 100644
index 000000000..2b3288dec
--- /dev/null
+++ b/ml_peg/app/non_covalent_interactions/NCIA_HB300SPXx10/app_NCIA_HB300SPXx10.py
@@ -0,0 +1,80 @@
+"""Run NCIA HB300SPXx10 app."""
+
+from __future__ import annotations
+
+from dash import Dash
+from dash.html import Div
+
+from ml_peg.app import APP_ROOT
+from ml_peg.app.base_app import BaseApp
+from ml_peg.app.utils.build_callbacks import plot_from_table_cell
+from ml_peg.app.utils.load import read_density_plot_for_model
+from ml_peg.models.get_models import get_model_names
+from ml_peg.models.models import current_models
+
+MODELS = get_model_names(current_models)
+BENCHMARK_NAME = "NCIA HB300SPXx10"
+DOCS_URL = (
+    "https://ddmms.github.io/ml-peg/user_guide/benchmarks/"
+    "non_covalent_interactions.html#ncia-hb300spxx10"
+)
+DATA_PATH = APP_ROOT / "data" / "non_covalent_interactions" / "NCIA_HB300SPXx10"
+
+
+class NCIANHB300SPXx10App(BaseApp):
+    """NCIA HB300SPXx10 benchmark app layout and callbacks."""
+
+    def register_callbacks(self) -> None:
+        """Register callbacks to app."""
+        density_plots: dict[str, dict] = {}
+        for model in MODELS:
+            density_graph = read_density_plot_for_model(
+                filename=DATA_PATH / "figure_ncia_hb300spxx10_density.json",
+                model=model,
+                id=f"{BENCHMARK_NAME}-{model}-density",
+            )
+            if density_graph is not None:
+                density_plots[model] = {"MAE": density_graph}
+
+        plot_from_table_cell(
+            table_id=self.table_id,
+            plot_id=f"{BENCHMARK_NAME}-figure-placeholder",
+            cell_to_plot=density_plots,
+        )
+
+
+def get_app() -> NCIANHB300SPXx10App:
+    """
+    Get NCIA HB300SPXx10 benchmark app layout and callback registration.
+
+    Returns
+    -------
+    NCIANHB300SPXx10App
+        Benchmark layout and callback registration.
+    """
+    return NCIANHB300SPXx10App(
+        name=BENCHMARK_NAME,
+        description=(
+            "Performance in predicting ionic hydrogen bond interaction energies "
+            "for the NCIA HB300SPXx10 dataset (ionic dimers from HB300). "
+            "Reference data from CCSD(T) calculations."
+        ),
+        docs_url=DOCS_URL,
+        table_path=DATA_PATH / "ncia_hb300spxx10_metrics_table.json",
+        extra_components=[
+            Div(id=f"{BENCHMARK_NAME}-figure-placeholder"),
+        ],
+    )
+
+
+if __name__ == "__main__":
+    # Create Dash app
+    full_app = Dash(__name__, assets_folder=DATA_PATH.parent.parent)
+
+    # Construct layout and register callbacks
+    benchmark_app = get_app()
+    full_app.layout = benchmark_app.layout
+    benchmark_app.register_callbacks()
+
+    # Run app
+    full_app.run(port=8057, debug=True)
diff --git a/ml_peg/calcs/non_covalent_interactions/NCIA_HB300SPXx10/calc_NCIA_HB300SPXx10.py b/ml_peg/calcs/non_covalent_interactions/NCIA_HB300SPXx10/calc_NCIA_HB300SPXx10.py
new file mode 100644
index 000000000..13ae44b02
--- /dev/null
+++ b/ml_peg/calcs/non_covalent_interactions/NCIA_HB300SPXx10/calc_NCIA_HB300SPXx10.py
@@ -0,0 +1,141 @@
+"""
+Compute the NCIA HB300SPXx100.
+
+Journal of Chemical Theory and Computation 2020 16 (10), 6305-6316.
+"""
+
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Any
+
+from ase import Atoms, units
+from ase.io import read, write
+import pytest
+from tqdm import tqdm
+
+from ml_peg.calcs.utils.utils import download_s3_data
+from ml_peg.models.get_models import load_models
+from ml_peg.models.models import current_models
+
+MODELS = load_models(current_models)
+
+KCAL_TO_EV = units.kcal / units.mol
+
+OUT_PATH = Path(__file__).parent / "outputs"
+
+
+def get_ref_energies(data_path: Path) -> dict[str, float]:
+    """
+    Get reference energies.
+
+    Parameters
+    ----------
+    data_path
+        Path to data.
+
+    Returns
+    -------
+    dict[str, float]
+        Loaded reference energies.
+    """
+    ref_energies = {}
+
+    with open(data_path / "NCIA_HB300SPXx10_benchmark.txt") as lines:
+        for i, line in enumerate(lines):
+            if i < 3:
+                continue
+            items = line.strip().split()
+            label = items[0]
+            ref_energy = float(items[1]) * KCAL_TO_EV
+            ref_energies[label] = ref_energy
+
+    return ref_energies
+
+
+def get_monomers(atoms: Atoms) -> tuple[Atoms, Atoms]:
+    """
+    Get ASE atoms objects of the monomers.
+
+    Parameters
+    ----------
+    atoms
+        ASE atoms object of the structure.
+
+    Returns
+    -------
+    tuple[Atoms, Atoms]
+        Tuple containing the two monomers.
+    """
+    if isinstance(atoms.info["selection_a"], str):
+        a_ids = [int(id) for id in atoms.info["selection_a"].split("-")]
+        a_ids[0] -= 1
+    else:
+        a_ids = [int(atoms.info["selection_a"]) - 1, int(atoms.info["selection_a"])]
+
+    if isinstance(atoms.info["selection_b"], str):
+        b_ids = [int(id) for id in atoms.info["selection_b"].split("-")]
+        b_ids[0] -= 1
+    else:
+        b_ids = [int(atoms.info["selection_b"]) - 1, int(atoms.info["selection_b"])]
+
+    atoms_a = atoms[a_ids[0] : a_ids[1]]
+    atoms_b = atoms[b_ids[0] : b_ids[1]]
+    assert len(atoms_a) + len(atoms_b) == len(atoms)
+
+    atoms_a.info["charge"] = int(atoms.info["charge_a"])
+    atoms_a.info["spin"] = 1
+
+    atoms_b.info["charge"] = int(atoms.info["charge_b"])
+    atoms_b.info["spin"] = 1
+    return (atoms_a, atoms_b)
+
+
+@pytest.mark.parametrize("mlip", MODELS.items())
+def test_ncia_hb300spxx10(mlip: tuple[str, Any]) -> None:
+    """
+    Run NCIA HB300SPXx10 barriers benchmark.
+
+    Parameters
+    ----------
+    mlip
+        Name of model use and model to get calculator.
+    """
+    model_name, model = mlip
+    calc = model.get_calculator()
+
+    # Read in data and attach calculator
+    data_path = (
+        download_s3_data(
+            filename="NCIA_HB300SPXx10.zip",
+            key="inputs/non_covalent_interactions/NCIA_HB300SPXx10/NCIA_HB300SPXx10.zip",
+        )
+        / "NCIA_HB300SPXx10"
+    )
+    ref_energies = get_ref_energies(data_path)
+
+    calc = model.get_calculator()
+    # Add D3 calculator for this test
+    calc = model.add_d3_calculator(calc)
+
+    for label, ref_energy in tqdm(ref_energies.items()):
+        xyz_fname = f"{label}.xyz"
+        atoms = read(data_path / "geometries" / xyz_fname)
+        atoms_a, atoms_b = get_monomers(atoms)
+        atoms.info["spin"] = 1
+        atoms.info["charge"] = int(atoms_a.info["charge"] + atoms_b.info["charge"])
+        atoms.calc = calc
+        atoms_a.calc = calc
+        atoms_b.calc = calc
+
+        atoms.info["model_int_energy"] = (
+            atoms.get_potential_energy()
+            - atoms_a.get_potential_energy()
+            - atoms_b.get_potential_energy()
+        )
+        atoms.info["ref_int_energy"] = ref_energy
+        atoms.calc = None
+
+        write_dir = OUT_PATH / model_name
+        write_dir.mkdir(parents=True, exist_ok=True)
+        write(write_dir / f"{label}.xyz", atoms)