<p>Yes both of the models can be converted to tflite format. For a step by step procedure please go through this link <a href="https://codelabs.developers.google.com/codelabs/tensorflow-for-poets-2-tflite/#0" rel="noreferrer">Convert to tflite</a>.</p>

<p>The major difference between InceptionV3 and Mobilenet is that Mobilenet uses 
Depthwise separable convolution while Inception V3 uses standard convolution.
This results into lesser number of parameters in MobileNet compared to InceptionV3. However, this results in slight decrease in the performance as well.</p>

<p>In a standard convolution the filter operates on the <strong>M</strong> channels of the input image all-together and outputs <strong>N</strong> feature maps i.e. the matrix multiplication between the input and filter is multidimensional. To make it clear take the filter as a cube of size <strong>D<sub>k</sub> x D<sub>k</sub> x M</strong>, then in standard convolution each element of the cube will multiply with the corresponding element in the input feature matrix and finally after the multiplication the feature maps will be added to output <strong>N</strong> feature maps. </p>

<p>However, in a depthwise separable convolution the <strong>M</strong> single channel filters will operate on a single cube in the input feature and once the <strong>M</strong> filter outputs are obtained a pointwise filter of size <strong>1 x 1 x M</strong> will operate on it to give <strong>N</strong> output feature maps. This can be understood from the figure below from the <a href="https://arxiv.org/pdf/1704.04861.pdf" rel="noreferrer">MobileNet paper</a>.</p>

<p><a href="https://i.stack.imgur.com/snkUUm.png" rel="noreferrer"><img src="https://i.stack.imgur.com/snkUUm.png" alt="Depthwise seprable convolution"></a></p>

<p>To make it more clear please go through the <a href="https://towardsdatascience.com/types-of-convolutions-in-deep-learning-717013397f4d" rel="noreferrer">DataScienceLink</a>.
They have a concrete example on how it reduces the parameters count which I am simply pasting here.</p>

<p><a href="https://i.stack.imgur.com/lJN2X.png" rel="noreferrer"><img src="https://i.stack.imgur.com/lJN2X.png" alt="enter image description here"></a>
<a href="https://towardsdatascience.com/types-of-convolutions-in-deep-learning-717013397f4d" rel="noreferrer">4</a></p>
What is the difference between tensorflow inception and mobilenet
<p>Recently i have been working with tensorflow inception V3 and mobileNet to deploy them for use in Android. While converting retrained model of inception V3 to "tflite" there some issues as the "tflite" model was empty, But when tried with retrained MobileNet model it was successfully converted into "tflite". So basically i have two questions</p>

<ol>
<li>Is it possible to convert inception V3 retrained model to "tflite"?</li>
<li>What is the difference between inception V3 and MobileNet?</li>
</ol>

<p>PS. I have gone through the official documentation link, which only hinted at mobileNet only being </p>

<p><a href="https://www.tensorflow.org/tutorials/image_retraining#other_model_architectures" rel="noreferrer">https://www.tensorflow.org/tutorials/image_retraining#other_model_architectures</a></p>