diff --git a/docs/examples/iv-modeling/plot_temperature_model_comparison.py b/docs/examples/iv-modeling/plot_temperature_model_comparison.py
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+"""
+Comparing PV Module Temperature Models
+======================================
+
+Examples of calculating PV cell temperature using different temperature models.
+
+Temperature models estimate PV module operating temperature based on
+environmental conditions such as irradiance, air temperature, and wind speed.
+
+This example compares the SAPM, Faiman, and PVsyst temperature models
+using identical environmental inputs. Differences between models illustrate
+how temperature model selection can influence predicted module temperature.
+"""
+
+# %%
+# Overview
+# --------
+#
+# Temperature models estimate PV cell temperature using environmental inputs.
+# Different models use different empirical relationships and assumptions.
+#
+# This example compares the SAPM, Faiman, and PVsyst temperature models
+# using identical weather conditions to illustrate differences in predicted
+# cell temperature.
+
+# %%
+# Import required libraries
+# -------------------------
+
+import pvlib
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+
+# %%
+# Generate example environmental data
+# -----------------------------------
+#
+# We simulate one week of hourly irradiance and temperature conditions.
+# Clear-sky irradiance is generated using pvlib's Location object.
+
+times = pd.date_range(
+    "2019-06-01 00:00",
+    "2019-06-07 23:00",
+    freq="1h",
+    tz="Etc/GMT+7"
+)
+
+location = pvlib.location.Location(32.2, -110.9)
+
+clearsky = location.get_clearsky(times)
+
+poa_global = clearsky["ghi"]
+
+# Create air temperature profile with daily variation
+temp_air = 20 + 10 * np.sin(
+    2 * np.pi * (times.hour - 6) / 24
+)
+
+# Constant wind speed
+wind_speed = np.full(len(times), 1.0)
+
+weather = pd.DataFrame({
+    "poa_global": poa_global,
+    "temp_air": temp_air,
+    "wind_speed": wind_speed,
+}, index=times)
+
+# %%
+# Calculate cell temperature using SAPM model
+# --------------------------------------------
+#
+# The SAPM model uses empirical coefficients based on mounting configuration.
+
+sapm_parameters = pvlib.temperature.TEMPERATURE_MODEL_PARAMETERS[
+    "sapm"
+]["open_rack_glass_glass"]
+
+sapm_temp = pvlib.temperature.sapm_cell(
+    poa_global=weather["poa_global"],
+    temp_air=weather["temp_air"],
+    wind_speed=weather["wind_speed"],
+    a=sapm_parameters["a"],
+    b=sapm_parameters["b"],
+    deltaT=sapm_parameters["deltaT"],
+)
+
+# %%
+# Calculate cell temperature using Faiman model
+# ----------------------------------------------
+#
+# The Faiman model uses heat transfer coefficients to estimate module
+# temperature.
+
+faiman_temp = pvlib.temperature.faiman(
+    poa_global=weather["poa_global"],
+    temp_air=weather["temp_air"],
+    wind_speed=weather["wind_speed"],
+    u0=25,
+    u1=6.84,
+)
+
+# %%
+# Calculate cell temperature using PVsyst model
+# ----------------------------------------------
+#
+# The PVsyst model uses empirical heat loss coefficients.
+
+pvsyst_temp = pvlib.temperature.pvsyst_cell(
+    poa_global=weather["poa_global"],
+    temp_air=weather["temp_air"],
+    wind_speed=weather["wind_speed"],
+    u_c=29,
+    u_v=0,
+)
+
+# %%
+# Combine results into a DataFrame
+# --------------------------------
+
+temperature_models = pd.DataFrame({
+    "SAPM": sapm_temp,
+    "Faiman": faiman_temp,
+    "PVsyst": pvsyst_temp,
+})
+
+# %%
+# Plot temperature model comparison
+# ---------------------------------
+#
+# This plot shows how predicted cell temperature varies across models.
+
+plt.figure(figsize=(10, 5))
+
+temperature_models.plot(ax=plt.gca())
+
+plt.xlabel("Time")
+plt.ylabel("Cell Temperature (°C)")
+plt.title("Comparison of PV Temperature Models")
+
+plt.legend()
+plt.tight_layout()
+plt.show()
+
+# %%
+# Plot temperature differences relative to SAPM
+# ---------------------------------------------
+#
+# This highlights differences between models more clearly.
+
+temperature_difference = temperature_models.subtract(
+    temperature_models["SAPM"], axis=0
+)
+
+plt.figure(figsize=(10, 5))
+
+temperature_difference.plot(ax=plt.gca())
+
+plt.xlabel("Time")
+plt.ylabel("Temperature Difference (°C)")
+plt.title("Temperature Difference Relative to SAPM Model")
+
+plt.legend()
+plt.tight_layout()
+plt.show()
+
+# %%
+# Plot daily average temperature
+# ------------------------------
+#
+# This shows daily trends in temperature prediction.
+
+daily_average = temperature_models.resample("D").mean()
+
+fig, ax = plt.subplots(figsize=(8, 5))
+
+daily_average.plot(kind="bar", ax=ax)
+
+ax.set_ylabel("Average Cell Temperature (°C)")
+ax.set_title("Daily Average Temperature by Model")
+
+plt.tight_layout()
+plt.show()