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AI Image Generator

Realize your ideas — create image from text with AI online

AI Model

Style

Aspect ratio

Blurred result

Explore a new level of creativity

Our advanced text to image AI generator allows you to create unique images and art from a simple description. Enter any prompt and select the art style to get a stunning realization of your idea.

Generate artworks in any style

Look at the examples of images created by our online AI generator to get some inspiration.

You can choose the style in our templates or describe the concept you need comprehensively and thoroughly in the prompt.

AI generated image in sci-fi style

“white dog"
sci - fi style

AI generated image in oil painting style

“girl with hat”
oil painting style

AI generated image in watercolour style

“field with flowers”
watercolour style

AI generated image in cartoon style

“man with beard”
cartoon style

Frequently asked questions

How to get the best result?

Enter a description of what you want to see, and AI will create a unique image based on your input. The more detailed text you make, the easier it will be for AI to understand what result you want to achieve. You may add the art styles for a more impressive artwork, such as Impressionism or Cubism. If you need to improve the result, just try once again or make changes to your prompt. Each time the image generator will create a new image for you.

In what language can I enter a query?

Use English, Spanish, French, Russian, Chinese, or German. Use English for all other languages.

How does AI generate images?

The AI model is trained on a huge array of image-text pairs collected on the internet. That makes it possible to create stunning works based on the user's prompt.

What styles may I use?

Here are some of the styles you can use from our templates: Watercolor; Oil painting; Pencil sketch; Street art; Impressionism; Surrealism; Cubism; Pop art; Fauvism, Cartoon; Sci-Fi, Fantasy; Anime. We will gradually increase the number of styles, but if the style in which you want to create an image is not on the list, try adding its name and description to your text query.

What tariffs users can use this service?

The service is available for users of all tariffs.

Can I save the image I have created?

Yes, after the image has been generated, you can download it to your device.

Why do I have to wait for an image to be created?

When you submit your query, you get into a queue to create an image (your number in the queue and approximate waiting time appears in the message). The image will be created as soon as your turn is up.

Where can the created images and artworks be used?

You can find good examples of using AI-generated images in absolutely different areas, like graphic design, tattoos, or unique screensavers. You are free to implement your most interesting ideas, but remember about ethics and responsibility - it is unacceptable to create content that offends and humiliates other people, nor content that violates copyright and license rights.

What is “negative prompt”?

A negative prompt allows the user to specify what he doesn’t want to see in a generated picture. It may prevent generating specific things, styles, fix some image abnormalities, and greatly improve the quality. The most commonly used negative prompts are: worst quality, normal quality, low quality, low res, blurry, text, watermark, logo, horror, etc. Check some examples:
prompt_mystery_forest

Prompt: Mystery forest

prompt_negative_prompt

Prompt: Mystery forest Negative prompt: fog, darkness

prompt_boy_on_the_moon

Prompt: Boy on the moon

prompt_negative_prompt_boy

Prompt: Boy on the moon Negative prompt: Space suit

What is “seed”?

Every single generated image as a unique attribute called “Seed”. You don't need to come up with the number yourself because it is randomly generated when not specified. Controlling the seed can help you generate reproducible images, experiment with other parameters, or prompt variations. For example, you can type in a prompt “Boy in a T-shirt” and the seed of 538637855, and try just to change the color of a T-shirt in a prompt. The pictures will be almost identical despite the color of a T-shirt. Note: In case you want to control seed, you should type in about 9-digit number, so that it would be sufficient (like in example above).
boy_red

Prompt: Boy in red T-shirt

boy_blue

Prompt: Boy in blue T-shirt

boy_yellow

Prompt: Boy in yellow T-shirt

boy_beige

Prompt: Boy in beige T-shirt

What is “steps”?

Generally speaking, the more steps you use, the better quality you'll achieve. But you shouldn't set steps as high as possible. First, we will introduce you the steps parameter in general. AI models are iterative processes – a repeated cycle that starts with a random noise generated from text input. Some noise is removed with each step, resulting in a higher-quality image over time. The repetition stops when the desired number of steps completes. Around 25 sampling steps are usually enough to achieve high-quality images. Using more may produce a slightly different picture, but not necessarily better quality. For example, compare 10 steps and 50 steps image generations:
prompt_wolf

Prompt: cosmic wolf

prompt_wolf

Prompt: cosmic wolf

prompt_wolf

Prompt: cosmic wolf

What is “sampler”?

The sampler is responsible for carrying out the denoising steps. What is this? To produce an image, AI first generates a completely random image. The noise predictor then estimates the noise of the image. The predicted noise is subtracted from the image. This process is repeated a dozen times. In the end, you get a clean image. This denoising process is called sampling because AI generates a new sample image in each step. The method used in sampling is called the sampler. You can generate pictures of different quality and various degree of realism by choosing different samplers. Here you can see the examples for samplers introduced in BgRem, so that you can choose your favorite for your future generations:
k_dpmpp_2m

k_dpmpp_2m

k_dpmpp_2s_a

k_dpmpp_2s_a

plms

plms

ddim

ddim

k_dpm_fast

k_dpm_fast

k_dpm_adaptive

k_dpm_adaptive

k_lms

k_lms

k_dpm_2

k_dpm_2

k_dpm_2_a

k_dpm_2_a

k_euler

k_euler

k_euler_a

k_euler_a

k_heun

k_heun