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Stable Diffusion 2.1 Versus 1.5

Stable Diffusion (SD) is a popular latent artificial intelligence (AI) art generation model that allows you to generate photorealistic images and pieces of digital art using simple text prompts and source images.

Currently, there are several versions of the SD model out there. Although these versions are designed to achieve the same goals, each version comes with more advanced features and capabilities than its predecessor. So, you have to understand what each of these models can give you before you select one for your project.

Whether you’re using a free AI generator or a subscription-based one, you must ensure that the model you have can be trained easily and quickly to generate high-quality images. In this article, we will evaluate SD 2.1 and 1.5 models.

What Is Stable Diffusion 2.1?

Stable Diffusion 2.1 is the advanced version of Stable Diffusion 2 and its predecessors. With SD 2.1, you can generate realistic AI images with superior quality than the ones generated by previous versions.

Features of Stable Diffusion 2.1

There are several unique features and perks with SD 2.1, including:


OpenCLIP is a text encoder developed by LIAON to help you generate images using natural language processing technology. With this feature, your SD model can produce images with amazing resolution. Your image pixels can range between 512 by 512 and 768 by 768 pixels.

Ability to Handle Longer and Complex Texts   

The new version of Stable Diffusion 2 is capable of generating photorealistic images from long and intricate text prompts. It does this without losing reliability or consistency.

Therefore, you can expect your model to give you the exact type of image described in the text prompt. This feature is enabled by the massive volume of vocabulary and the attention machinery of OpenCLIP.

Negative Prompt Function

Negative Prompt Function feature allows you to specify what you don’t want in your final image using text prompts. So, if you generate an image and discover an unwanted element in it, you can remove it using the negative prompt function.

What Is Stable Diffusion 1.5?

The Stable Diffusion 1.5 model is one of the oldest versions of SD. It’s a diffusion-based AI model that generates images from text prompts.

Text prompts in SD 1.5 are encoded using an encoder that converts images into covert representations. This autoencoder uses the eight down-sampling factor and aligns images of the H X W x 3 shape with a latent of the H/f x W/f x 4 shape.

This version of the SD model uses a secure pre-trained encoder, ViT-L/14, to encode text prompts. It uses its cross-attention capabilities to merge non-pooled outputs with the UNet backbone.

What’s the Difference Between Stable Diffusion 2.1 and 1.5?

As more versions of the Stable Diffusion model continue to emerge, members of the SD community have the enormous task of evaluating the strengths and weaknesses of each version so that users can make informed decisions.

Some have even published content describing the Dreamshaper XL model as well as the SD checkpoint merger and LoRA (low-ranking adaptation) capabilities. If you’re not sure whether to use SD 1.5 or 2.1, here are the main differences between the two:


SD v2.1 replaced the previous text encoder used by SD v1.5 (OpenAI’s CLIP) with OpenCLIP. The new encoder is trained on a recognized dataset, which is a subset of LAION-5B with the ability to filter out NSFW visuals.

Negative Prompts

Negative prompting enables SD v2.1 to generate more realistic images by eliminating unwanted elements of your text prompts. This is a major improvement from SD v1.5.

Textual Inversion

This is the ability of your SD model to use a few reference images to generate ‘text’ that represents those images. This function seems to favour SD v2.1 rather than SD v1.5. 

Final Thoughts

This information should help you choose the version of Stable Diffusion that suits your needs. Check out the ease of AI image generation with NightCafe today!

Create jaw-dropping art in seconds with AI

This is the most fun I've had on the internet in a long long time

u/DocJawbone on Reddit

Fun Fast Free