Midjourney vs. Dall·E 2 vs Stable Diffusion: Side by Side Comparison
Last Updated January 24, 2023
Over the past few years, AI has revolutionized the art industry. Its ability to convert text to images has blown many people’s minds and is now busy ruling the art industry.
Many artists have started using this technology as part of their professional life. The best part is that it is so easy to use that even an average person can use it and make the art of their imagination.
There are many AI Art generators, but the best are Midjourney, Dall·E 2, and Stable Diffusion.
They all have similarities and dissimilarities, which we will look at in today’s blog post.
We’re going to determine which one’s the best, which one’s the cheapest, which produces the best results, and which is the best for you and your projects.
Let’s get into it and discover the best fit for you.
In DALL-E 2, OpenAI has created a generative AI model that generates high-quality images from text. A combination of deep learning techniques, including transformers and GANs, was used to train the model on a dataset of text-image pairs. It can generate images of everyday objects, animals, and even surreal or abstract ideas.
Using the DALL-E model, the user describes the image they want to create in text form. Based on its understanding of the relationship between words and images, the model creates an image that matches the description. The output of the model is a high-quality image that can be displayed or saved.
A designer could use DALL-E to generate images of furniture for use in a virtual environment, or an advertising agency could use it to create advertisements. This technology could also be utilized in the production of medical imaging for complex medical procedures or anatomical structures. Overall, DALL-E and DALL-E 2 represent a significant advancement in AI image generation technology.
Stable Diffusion is another AI Art Generator that uses an entirely different technology. It uses a frozen CLIP ViT-L/14 text encoder to tune the model at text prompts. It starts to process images like a diffusion process. It starts to create an image full of noise and then gradually improves.
Midjourney is another astonishing Art Generator powered by AI. Midjourney is efficient in creating images from user prompts. It supports different styles and makes artwork of your choice. You can create any cinematic style or sci-fi scene with the help of mid-journey.
It uses machine learning algorithms to generate unique and original artworks. The model has been trained on a large dataset of images, which allows it to learn patterns and styles from different art movements and genres. By providing keywords, images, or color palettes, the user can interact with the model to generate original artwork.
Midjourney’s team has used AI-generated artwork as the basis of digital art prints, murals, and installations. In addition to creating art for brands and institutions, the studio also does custom work
Among the growing fields of artificial intelligence-powered art is Midjourney, a form of artistic expression that uses machine learning algorithms to generateforms.
Artificial intelligence-powered art generators like Midjourney are expanding the boundaries of what is possible in art and design by leveraging data and computational power today.
How does AI Image Generators work?
Let’s start with understanding what an AI text-to-image generator is. Well, the software creates an image from a text input also referred to as a prompt.
Now, how does this work? What’s the technology behind it?
To build one of these, you’ll need massive datasets consisting of billions of images and pairs of text to train the AI model.
Midjourney and Dall·E 2 have yet to make their datasets public. However, the open-source AI, “ stable diffusion,” has been more transparent about how it trains its AI.
Stable Diffusion vs Dall-e vs Midjourney: Magic Behind these softwares
Technology Behind Stable Diffusion
First, the AI must learn to make sense of the visual structure of these images and how they relate to their accompanying text.
The next step is the process called diffusion.
Here, visual noise is incrementally added to tiny images, gradually destroying the training image and training the AI to reverse this process of visual noise to the idea that looks like the original training image.
After applying noises to billions of training images, the AI can learn to start with pure visual noise and construct new images from this noise.
This means that a user can now give a text prompt to the AI, say, an apple hanging from the tree, and the AI will use what it has learned about apples and trees to create new or multiple new representations from the noise.
Stable Diffusion also uses regularization techniques to make sure the images are visually and semantically coherent. The model employs a loss function that encourages smooth gradients in the generated images, as well as a perceptual loss that measures the similarity between the generated and reference images.
One of the key advantages of Stable Diffusion is its ability to generate high-quality images with a high degree of diversity and complexity. The model can generate images of a wide range of objects, scenes, and styles, and can be trained on large datasets of images to capture a wide range of visual concepts and patterns.
Technology Behind Midjourney
Midjourney is an AI Image generator that works on prompt. It takes prompts as inputs to create unique images and uses machine learning (ML) algorithms that are trained on large datasets having billions of images.
In their official discord, midjourney is only available via the discord bot. If you want to create art in the mid-journey, just type in /imagine and write your prompt like any other image generator, and the bot will get back to you with your desired result.
Technology Behind Dall·E 2
DALL-E 2 is a state-of-the-art image generation model developed by OpenAI. It uses several advanced deep learning techniques to create DALL-E 2.
One of the key components of DALL-E 2 is the use of transformers, which are neural network architectures that can process sequential data. In DALL-E 2, transformers are used to understand the relationship between the textual input and the generated image.
The transformer architecture encodes the textual input and generates an image representation.
In DALL-E 2, a type of neural network called a generative adversarial network (GAN) is also used to generate new data that is similar to a given dataset. GANs consist of two networks: a generator network and a discriminator network. The generator network takes random noise as input and generates a new image. The discriminator network then evaluates the generated image and determines whether it is real or fake. Through an iterative training process, the generator network learns to generate increasingly realistic images.
Aside from these mechanisms, DALL-E 2 also analyses input data using convolutional neural networks (CNNs). CNNs are used to extract features from the input data and identify patterns that are useful for generating the output.
Comparison between Dall·E 2 vs Stable Diffusion vs Midjourney
Dall·E 2 generates the most realistic photos, while mid-journey tends to have artistic and better-composed sort of images whereas stable diffusion also creates photo-realistic pictures but is still second in both.
In addition, Dall·E 2 has the most straightforward interface, making the whole process easier and more enjoyable. One thing that Dall·E 2 can do what others can’t do is the ability to upload an image and modify part of it to create a new idea.
While Midjourney is a bit more complex, the images it creates are better. Mid-Journey is currently the only AI that produces high-resolution images of 16 by 9 and other ratio images because all the other AIs create square images or very low-resolution images, so this is another plus point for mid-journey.
Another exciting thing about mid-journey, compared to the other two, is that you can give a little information. It has a very high creation process in that it can comprehend complex concepts you give and creates images around the idea itself while other AIs fail to do this because you need to tell them precisely what you want.
Stable diffusion is free to get, but it is complex to set up unless you want to go towards online interfaces like dream studio. It is complicated compared to the two. It is the only open-source AI, meaning you can use it for free by downloading its code to your computer. Now you can use it for free without paying any money. But the problem is if you want to use this software on your computer, you will need beefy graphic cards and high VRAM. You need powerful things on your computer to run something like this. Now one thing that stable diffusion AI is the best as compared to the other two is creating faces. It makes classic results and gives you exact results based on your prompt.
Let’s compare these based on image resolution. Midjourney enables you to change the aspect ratio of your prompt with a maximum resolution of 2048 by 1,280, and Dall·E 2 has 1024 by 1024 pixels image while stable diffusion is even smaller.
In terms of pricing, it’s very direct and not confusing at all.
Let’s talk about Dall·E 2 first. You get 50 free credits for your first month, and 15 will come back each month, and you can buy additional credits.
$15 for 150 credits
Now let’s have a look at the dream studio, the online version of stable diffusion based on credits.
Pricing varies with the number of features you want.
If we talk about mid-journey, it has a subscription model where you can do 200 minutes of GPU per month, which costs $10. Overall, midjourney has an entirely different approach than Dall·E 2 and Stable Diffusion. It allows you to create infinite results once you get a subscription. This is the best feature of Midjourney because endless tries get your creative thinking going, and you can get the best possible results by redoing and trying repeatedly.
Now Let’s look at some of the prompts which will help us understand the accuracy of each platform.
Final Image Side-by-Side Comparison: Best AI Tools
Comparison of the output of the generated images by Dall·E 2, Midjourney and Stable Diffusion by using same ” PROMPT” .
Prompt#1: a digital artwork that depicts an astronaut floating in space, surrounded by colorful nebulas and galaxies
Prompt#2: a 3D landscape of a mystical forest with ancient trees and animals. The woods should have a magical, ethereal atmosphere, with sunlight filtering through leaves.
Prompt#3: a group of playful snowmen enjoying a winter day
Prompt#4: 3D model of an underwater world where colorful coral reefs teeming with exotic sea creatures
Prompt#5: a portrait of a beautiful young girl wearing a stethoscope and glasses, hyper-realistic
Prompt#6: an illustration showing a futuristic,c technologically advanced city having an advanced transportation system with flying drones and robots.
Prompt#7: AI-Powered woman
Prompt#8: a digital landscape of a desert at sunset with palm trees
Prompt#9: a 3D model of a fairy castle at night with fairy lights
Prompt#10: a creepy mythical creature
The most intricate one, or the one which creates more precise images, is stable diffusion, the one that is the most creative is mid-journey, and the one that has the functionality of erasing part of a picture to add another on top is Dall·E 2.
These are some points you want to consider while choosing the right platform for you that best fits your needs.
Spend hours on each of the above AI Art Generators and choose one that suits your style and needs.
Thanks for Reading!
Tech Content Writer
Naima is a skilled and experienced content writer, with a passion for creating high-quality, well-researched articles and blog posts. With her strong writing skills and attention to detail, Naima is able to craft engaging and informative content that resonates with readers.
In addition to her work as a content writer, Naima is also highly interested in technology and artificial intelligence and is always looking for ways to stay up-to-date on the latest trends and developments in these fields.