From zero to generating stunning images — how AI image generation works, which models to use, and prompt tips that actually work.
AI image generation has gone from a research curiosity to a mainstream creative tool in just a few years. In 2026, anyone can type a text description and get a photorealistic image, a stylized illustration, or an abstract piece of art in seconds. But the landscape can be overwhelming — dozens of models, confusing terminology, and wildly varying quality. This guide covers everything a beginner needs to know.
AI image generation is the process of creating images from text descriptions (called “prompts”) using artificial intelligence models. You describe what you want — “a golden retriever wearing sunglasses on a beach at sunset” — and the AI produces an image matching that description.
The technology behind it is based on neural networks that have been trained on billions of image-text pairs. These models learned the relationship between words and visual concepts, so when you say “sunset,” the model knows what warm orange-pink light looks like, how it interacts with objects, and how to render it convincingly.
Modern AI image generators can produce:
Most AI image generators use a technique called “diffusion.” Here’s the simplest way to understand it:
Think of it like a sculptor starting with a rough block of marble. Each denoising step is like a chisel stroke, gradually revealing the image hidden in the noise. Your text prompt acts as the blueprint that guides where the chisel strikes.
The magic is in the training: the model learned to denoise images by seeing billions of examples. It knows that the noise pattern at step 15 should look like rough shapes, at step 30 should show clear composition, and at step 50 should have fine details. Your prompt steers the process toward the specific image you described.
Not all models use diffusion, though. Newer architectures like autoregressive models (BitDance) generate images token-by-token, similar to how large language models generate text. These can be faster and sometimes handle complex scenes better. For a deeper dive into architectures, read our guide on understanding AI models.
AI image models aren’t one-size-fits-all. Different models excel at different tasks:
Apefx offers 27+ models. Here are the ones beginners should know:
Cost: 1 credit. Speed: near-instant. Think of this as your drafting tool. When you’re figuring out a prompt — testing compositions, trying keywords, iterating fast — Flux 2 Klein gives you a preview in under 2 seconds. The quality is good (not ultra), but the speed is unmatched. Use it for exploration, then switch to a premium model for the final render.
Cost: 5 credits. Speed: fast. Quality: high. This is the reliable all-rounder. Consistently good output across styles, fast enough for iteration, affordable enough for volume work. If you’re not sure which model to use, start here.
Cost: 15 credits. Speed: medium. Quality: ultra. Powered by Google’s Gemini 3 Pro, this is the highest-quality model on the platform. Exceptional character consistency, stunning detail, and nuanced prompt interpretation. Use it for hero images, final renders, and anything where quality is the priority.
Cost: 8 credits. Speed: medium. Quality: high. Built for design and marketing use cases. Clean compositions, excellent typography, production-ready output. If you’re creating social media assets, ads, or brand materials, this is your model.
Cost: 4 credits. Speed: fast. Quality: high. An autoregressive model that excels at photorealistic output. Fast, affordable, and remarkably lifelike. Great for product photography, portraits, and any scene that needs to look like a real photograph.
Cost: 7 credits. Speed: fast. Quality: high. From xAI (Elon Musk’s AI company), Grok Imagine brings creative interpretation and artistic flair. It often surprises with unexpected compositions and imaginative interpretations of prompts. Available in standard and unrestricted (🌶️) modes.
Here’s how to generate your first image in under 2 minutes:
With 50 free credits, you can generate approximately 10 images with Flux Pro, 50 instant previews with Flux 2 Klein, or 3 ultra-quality images with Nano Banana Pro. Mix and match to explore.
The quality of your output depends heavily on your prompt. Here are the fundamentals:
A strong prompt typically includes: Subject + Setting + Style + Lighting + Technical details
“A young woman reading a book in a sunlit café, morning light through large windows, warm color palette, shallow depth of field, 85mm portrait lens, photorealistic”
AI models were trained on images paired with their descriptions, which often include technical terms. These terms give you precise control:
For a deeper exploration of effective prompts, check out our 10 AI art prompts that always work.
Some models support negative prompts — things you don’t want in the image. Common negative prompts include: “blurry, low quality, distorted hands, extra fingers, watermark.” This helps the model avoid common artifacts.
The most productive workflow is rapid iteration. Use Flux 2 Klein (1 credit) to test your prompt 5–10 times, adjusting wording each time. Once you find a prompt that consistently produces the composition you want, switch to a premium model like Nano Banana Pro for the final high-quality render.
Now that you understand the basics, here’s where to go next:
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