Can i have mutliple labels for a single image in an image classification scenario
If I am building a model where I need to predict the vehicle, color of it, and make of it, then can I use all the labels for a single image and build my model around it.

Like for a single image of a vehicle which is a car (car1.jpg) will have labels like - Sedan(Make), Blue(Color) and Car(Type of vehicle). Can I make a single model for this or I will have to make 3 separate models for this problem.

You can have a single model with multiple outputs. As you seem interested with image processing, detection models for example (like SSD, RFCN, etc.) have multiple outputs, one for classes, one for box coordinates. Take a look a the page 3 of this article for the "feature extractor"/"classifier" split.

In fact, you will have a first common part of your model (with mostly the convolution layers to extract your features).
Deeper in your model, you will have separate parts, one for each kind of prediction.
