We propose a new generative adversarial network (GAN) for image compression with novel discriminator and generator loss functions and a simple entropy estimation approach. Our new loss functions outperform the current GAN loss for low bitrate image compression. Our entropy estimation approach does not require extra convolution layers but still works well to constrain the number of bits during training.