Update: If I disable the GPU using the following code the differences become very very small on the order of 1e-8 instead of 8e-2. Seems like a GPU driver problem import tensorflow as tf # Disable all GPUS tf.config.set_visible_devices([], 'GPU') visible_devices = tf.config.get_visible_devices() for device in visible_devices: assert device.device_type != 'GPU' import tensorflow as tf import numpy as np import pandas as pd # Setup model input_shape = (10, 5) model_tst = tf.keras.Sequential() model_tst.add(tf.keras.Input(shape=input_shape)) model_tst.add(tf.keras.layers.LSTM(100, return_sequences=True)) model_tst.add(tf.keras.layers.Dense(2, activation="sigmoid")) model_tst.summary() optimizer = tf.keras.optimizers.Adam(learning_rate=0.01) loss = tf.keras.losses.BinaryCrossentropy(from_logits=False) model_tst.compile( loss=loss, optimizer=optimizer, # metrics=[tf.keras.metrics.BinaryCrossentropy() metrics=["mse" ] ) # Generate step data random_input = np.ones((11, 10, 5)) random_input[:, 8:, :] = 99 # Predictions random_output2 = model_tst.predict(random_input, batch_size=1)[0, :, :].reshape(10, 2) random_output3 = model_tst.predict(random_input, batch_size=10)[0, :, :].reshape(10, 2) # Compare results diff2 = random_output3 - random_output2 pd.DataFrame(diff2).T

deleting