@Bhack That’s a great hint! It worked.
def run_inference(image):
    g.interpreter.set_tensor(g.input_details[0]['index'], image)
    g.interpreter.invoke()
    outputs = g.interpreter.get_tensor(g.output_details[0]['index'])[0]
    return outputs

@app.before_request
def load_model():
    g.interpreter = tf.lite.Interpreter(model_path="quant_model.tflite")
    g.interpreter.allocate_tensors()
    g.input_details = g.interpreter.get_input_details()
    g.output_details = g.interpreter.get_output_details()

But truly said it seems, taking time as same as loading model every time.