Where are the 60 million params of AlexNet?
I forgot to flatten between the last Conv2D layer and the first fully-connected layer.
model = tf.keras.models.Sequential([
    tf.keras.layers.Conv2D(96, 11, strides=4, activation=&quot;relu&quot;, input_shape=[227,227,3]),
    tf.keras.layers.MaxPooling2D(pool_size=(3,3), strides=(2,2)),
    tf.keras.layers.Conv2D(256, 5, activation=&quot;relu&quot;, padding=&quot;SAME&quot;),
    tf.keras.layers.MaxPooling2D(pool_size=(3,3), strides=(2,2)),
    tf.keras.layers.Conv2D(384, 3, activation=&quot;relu&quot;, padding=&quot;SAME&quot;),
    tf.keras.layers.Conv2D(384, 3, activation=&quot;relu&quot;, padding=&quot;SAME&quot;),
    tf.keras.layers.Conv2D(256, 3, activation=&quot;relu&quot;, padding=&quot;SAME&quot;),
    tf.keras.layers.Flatten(), # &lt;-- This layer
    tf.keras.layers.Dense(4096, activation=&quot;relu&quot;),
    tf.keras.layers.Dense(4096, activation=&quot;relu&quot;),
    tf.keras.layers.Dense(1000, activation=&quot;softmax&quot;),
])

Once added, I get the 62 million params:
Model: &quot;alex_net&quot;
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
conv2d (Conv2D)              multiple                  34944     
_________________________________________________________________
conv2d_1 (Conv2D)            multiple                  614656    
_________________________________________________________________
conv2d_2 (Conv2D)            multiple                  885120    
_________________________________________________________________
conv2d_3 (Conv2D)            multiple                  1327488   
_________________________________________________________________
conv2d_4 (Conv2D)            multiple                  884992    
_________________________________________________________________
max_pooling2d (MaxPooling2D) multiple                  0         
_________________________________________________________________
flatten (Flatten)            multiple                  0         
_________________________________________________________________
dense (Dense)                multiple                  37752832  
_________________________________________________________________
dense_1 (Dense)              multiple                  16781312  
_________________________________________________________________
dense_2 (Dense)              multiple                  4097000   
=================================================================
Total params: 62,378,344
Trainable params: 62,378,344
Non-trainable params: 0
_________________________________________________________________

Even if it's a mistake from me, I leave it here for understanding purposes.