I have post the issue to tensorflow and keras-team.Cause the can't reproduce the issu, they suggest I post the issue to apple team. I'm using MacBook Air with M1 chip. OS version is Big Sur 11.4. which python /Users/dmitry/Applications/Miniforge3/bin/python I run the following code using tensorflow-macos and tensorflow_macos, respectively. import tensorflow as tf mnist = tf.keras.datasets.mnist (x_train, y_train), (x_test, y_test) = mnist.load_data() x_train, x_test = x_train / 255.0, x_test / 255.0 model = tf.keras.models.Sequential([ tf.keras.layers.Flatten(input_shape=(28, 28)), tf.keras.layers.Dense(128, activation='relu'), tf.keras.layers.Dropout(0.2), tf.keras.layers.Dense(10) ]) predictions = model(x_train[:1]).numpy() tf.nn.softmax(predictions).numpy() loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True) loss_fn(y_train[:1], predictions).numpy() model.compile(optimizer = 'sgd', loss = loss_fn) model.fit(x_train, y_train, epochs=100) I got this! with tensorflow-macos and python3.9: Epoch 1/100 1875/1875 [==============================] - 8s 4ms/step - loss: 0.7026 Epoch 2/100 1875/1875 [==============================] - 8s 4ms/step - loss: 0.3872 Epoch 3/100 1875/1875 [==============================] - 8s 4ms/step - loss: 0.3284 Epoch 4/100 1875/1875 [==============================] - 8s 4ms/step - loss: 0.2891 Epoch 5/100 1875/1875 [==============================] - 8s 4ms/step - loss: 0.2622 with tensorflow_macos and python3.8 env: Epoch 1/100 1875/1875 [==============================] - 1s 276us/step - loss: 1.2181 Epoch 2/100 1875/1875 [==============================] - 1s 270us/step - loss: 0.4678 Epoch 3/100 1875/1875 [==============================] - 1s 269us/step - loss: 0.3935 Epoch 4/100 1875/1875 [==============================] - 1s 271us/step - loss: 0.3507 Epoch 5/100 1875/1875 [==============================] - 1s 270us/step - loss: 0.3231 Why tensorflow-macos is so slower than tensorflow_macos?Did I miss something?