Full guide

This comprehensive guide teaches you how to craft compelling prompts for AI image generation. Master the art of prompt engineering to transform your creative visions into stunning visuals.

Note

All example images in this guide were generated using the Pruna-optimized FLUX models on Replicate:

What is an image generation prompt?

A “prompt serves as your creative blueprint” - it’s the textual instruction that guides AI models to generate specific images. Think of it as directing a digital artist who can paint anything you can describe.

Effective prompt engineering involves “strategically crafting descriptions” that communicate your vision clearly and completely. The precision of your language directly influences the quality and accuracy of the generated output.

Prompting principles for image generation

Master these fundamental principles to create compelling prompts that generate better, more accurate results.

✅ DO

❌ DON’T

Use descriptive, direct language

“mountain peak covered in snow”

Use command-style instructions

“please generate a mountain peak covered in snow”

Focus on positive description

“clean-shaven professional headshot”

Describe by negation

“man without facial hair”

Be specific

“oak tree against orange sky”

Be vague or generic

“nice scenery”

Include style and atmosphere

cyberpunk warrior, Mars, crimson sunset

Add unrelated or conflicting elements

“knight in space armor with unicorns and robots”

Use prompt enhancement tools

Refine your prompt using “improve prompt” features

Overcomplicate at first

Start with simple descriptions before adding complexity

Keep styles compatible

Combine styles that naturally work together

Combine impossible or conflicting styles

oil painting + pencil sketch + cubist anime watercolor

Leverage AI-powered suggestions

Use enhancement tools or suggestions when refining prompts

Add unnecessary complexity up front

Begin simple and only add detail as needed

Word Order and Emphasis Placement: Some models prioritize words mentioned earlier in the prompt. So even though the structure above is a recommended best practice, you can experiment with different word orders to emphasize the aspects you want to see in the image.

Length Guidelines: Short prompts (10-20 words) are good for simple concepts, medium prompts (20-50 words) are optimal for most use cases, and long prompts (50+ words) are used for complex scenes with many details.

Iterative Improvement: Generate multiple variations, compare results side by side, identify successful elements, and build a personal prompt library.

Tip

Successful prompts follow a structured approach that prioritizes the most important elements first. This hierarchy ensures the AI focuses on your primary vision before adding supporting details.

Creating a image generation prompt

Every well-crafted prompt contains four key components:

  1. Primary Subject: The central focus of your image

  2. Subject Behavior: Actions, poses, or states

  3. Visual Style: Artistic medium or approach

  4. Environmental Context: Setting, atmosphere, and mood

[Primary Subject] [Subject Behavior] [Visual Style] [Environmental Context]
A purple prune character, reading a book, animation style, in a living room
https://huggingface.co/datasets/pruna-test/documentation-media/resolve/main/prompt_guide/image_generation/basic.jpeg?download=true

Step 1: Define the primary subject

Begin by identifying the main focus of your image. Whether it’s a person, animal, object, or scene, be as descriptive as possible. Avoid command language - describe what exists rather than instructing the AI to create something.

Subject Specification Guidelines:

  • Human Subjects: Include age range, gender, clothing style, posture, facial expression

  • Animal Subjects: Specify breed/variety, size, coloration, behavior, habitat

  • Object Subjects: Detail materials, dimensions, condition, placement

  • Scene Subjects: Define location, time period, weather conditions, atmosphere

"a purple prune character [...]"
https://huggingface.co/datasets/pruna-test/documentation-media/resolve/main/prompt_guide/image_generation/basic.jpeg?download=true

Tip

Detailed subject descriptions lead to more accurate and personalized results.

Step 2: Enhance with descriptive modifiers

Modifiers transform basic descriptions into rich, detailed imagery. These descriptive elements add depth, mood, and visual interest to your prompts.

Essential modifier categories include:

  • Environmental Settings: “urban street at dusk”, “pristine mountain meadow”

  • Artistic Approaches: “watercolor painting”, “digital illustration”, “charcoal sketch”

  • Emotional Atmosphere: “serene and peaceful”, “tense and dramatic”

  • Lighting Conditions: “soft diffused light”, “harsh directional lighting”

  • Color Schemes: “monochromatic blues”, “warm earth tones”

  • Perspective Views: “low angle shot”, “overhead view”

  • Artistic Influences: “inspired by Monet”, “reminiscent of Art Nouveau”

"a happy knitted purple prune character with expressive eyes, cute arms and a roundish body, reading a book, animated style, in a living room"
https://huggingface.co/datasets/pruna-test/documentation-media/resolve/main/prompt_guide/image_generation/detailed.jpeg?download=true

Tip

Descriptive modifiers help you create more detailed and personalized images. For more details, see the Image generation prompt categories section.

Step 3: Apply quality enhancement terms

Quality enhancers are specialized terms that improve the technical and artistic quality of generated images. These “magic words” guide the AI toward higher-quality outputs.

Photography Quality Enhancers: * “ultra-sharp focus”, “professional grade”, “studio quality” * “HDR processing”, “high resolution”, “crystal clear” * “cinematic composition”, “perfect exposure”

Artistic Quality Enhancers: * “museum quality”, “gallery worthy”, “award-winning” * “masterful technique”, “exceptional detail” * “trending on art platforms”, “viral artwork”

Technical Quality Enhancers: * “ray-traced rendering”, “unreal engine quality” * “octane render”, “photorealistic textures”

"low angle shot of a happy knitted purple prune character with expressive eyes, cute arms and a roundish body, reading a book, animated style, in a cozy dimly lit living room during a rainy day"
https://huggingface.co/datasets/pruna-test/documentation-media/resolve/main/prompt_guide/image_generation/descriptive.jpeg?download=true

Tip

Quality enhancement terms help you create more detailed and professional images. For more details, see the Image generation prompt categories section.

Image generation prompt categories

Understanding how specific words and phrases impact your generated images is essential for crafting effective prompts. Each term you include shapes the visual output in predictable ways. This section explains not just what terms to use, but “what visual effects they create” and “how they influence the final image”.

Visual style vocabulary

Visual style terms control the artistic medium, rendering technique, and overall aesthetic approach of your generated images. These keywords transform how subjects appear and what mood the image conveys.

"anime style character portrait of a young woman with large expressive eyes, detailed flowing hair, dynamic pose, cel-shaded art style, vibrant colors, intricate costume design"
https://huggingface.co/datasets/pruna-test/documentation-media/resolve/main/prompt_guide/image_generation/anime.jpeg?download=true

Category

Visual Effect

Character proportions

“anime style” and “chibi” create large eyes (2-3x normal size), stylized proportions, with chibi featuring oversized heads and small bodies for cute/whimsical effects

Animation techniques

“cel-shaded” uses flat color blocks with hard shadows (no gradients), “clean line art” provides sharp definition, “dynamic poses” and “dynamic motion lines” create energetic action with motion lines and exaggerated perspectives

Facial & hair details

“large eyes”, “expressive emotions”, and “exaggerated emotions” create exaggerated facial expressions, while “detailed hair”, “flowing hair”, “stylized hair strands”, and “spiky hair” add complex hair designs with individual strands

Costume & armor

“detailed costumes”, “intricate costumes”, and “detailed armor” add technical details, while “exaggerated emotions” enhances character personality

Specialized styles

“mecha designs” and “sleek mecha designs” create futuristic robotic suits with geometric shapes and sci-fi aesthetics, “fantasy elements” add magical components

Quality terms

“fine details” and “delicate contours” enhance precision, “vibrant colors” increase saturation, “soft shadows with hatching” add shading depth

Genre subtypes

“manga art”, “shonen”, “shojo”, “seinen”, “isekai” define specific anime/manga genres and target audiences

Subject matter vocabulary

Subject matter terms specify what appears in your image - the environments, activities, objects, and contexts that create your visual narrative. These terms define the content and setting of your generated images, working alongside visual style to create complete compositions.

"professional architectural photography of a esthetic living room with artsy prune couch and a painting of a bowl of prunes, HDR processing, ultra-sharp focus, perfect golden hour lighting, cinematic composition"
https://huggingface.co/datasets/pruna-test/documentation-media/resolve/main/prompt_guide/image_generation/physical_spaces.jpeg?download=true

Category

Visual Effect

Interior spaces

“interior design” focuses on room layouts furniture placement and decor styling, “home decor” emphasizes domestic aesthetics, “residential design” creates home-like atmospheres with domestic comfort, “room layouts” establishes spatial arrangements

Architectural focus

“architectural photography” and “professional architectural photography” emphasize structural elements lines and spatial relationships, “building exteriors” shows facade details, “spatial design” and “environmental design” establish layout principles

Commercial environments

“office spaces” creates professional environments with desks computers and work settings, “retail environments” provides commercial spaces with displays and shelving, “commercial spaces” establishes business-oriented atmospheres

Urban contexts

“urban architecture” creates modern city landscapes with buildings and streets, “public spaces” provides open areas like parks plazas for multiple people

Professional photography

“HDR processing” enhances dynamic range, “ultra-sharp focus” provides crisp detail, “perfect golden hour lighting” creates warm illumination, “cinematic composition” adds filmic framing

Artistic interpretations

“watercolor painting style” and “impressionist technique” provide painted versions, “soft pastel colors” add gentle tones, “gentle morning mist” creates atmospheric mood, “peaceful lakeside cottage” establishes serene settings

Advanced prompting strategies

Master these sophisticated techniques to refine your image generation and achieve more precise results.

Prompting specific AI models

Different AI image generation models have distinct strengths and respond optimally to specific prompting strategies. Understanding these differences helps you tailor your approach for better results.

Diffusion-Based Models: These models excel with structured keyword combinations, respond well to technical photography terminology, and benefit from specific artistic style references. They also support comprehensive negative prompt functionality.

Language Model-Based Models: These models prefer natural, conversational descriptions, work effectively with paragraph-style prompts, respond to narrative and contextual details, and have limited negative prompt functionality.

Specialized Platforms: These models favor concise, high-impact phrases, respond well to reference image integration, benefit from artistic movement keywords, and support parameter-based fine-tuning.

Non-English Models: These models may require more verbose prompts to generate accurate results. Prompt adherence is often better when translated to the target language.

Adjusting generation arguments

Beyond crafting effective prompts, understanding and tuning generation parameters can significantly impact the quality and characteristics of your generated images. These parameters control technical aspects of the generation process, such as the number of denoising steps, creative control, and output format.

Important Considerations: Not all models support the same arguments, usage may differ across platforms, start with defaults and gradually adjust to see how changes affect your results, quality vs. speed trade-offs.

Parameter

Purpose

Typical Values & Effects

num_inference_steps

Number of denoising iterations

Lower (10-20): Faster generation, less detail Higher (30-50): Slower generation, higher quality Typical range: 20-40 steps

guidance / strength

How closely the model follows your prompt

Lower (2-3): More creative interpretation, realistic Higher (6-10): Stricter adherence, stronger effects Typical range: 3-7

seed

Controls randomness and reproducibility

Set to specific number: Reproducible results Leave empty: Random generation each time

num_outputs

Number of images to generate

Typically 1-4 outputs More outputs increase processing time

aspect_ratio

Dimensions of the output image

“1:1”: Square “16:9”: Wide landscape “9:16”: Portrait “4:3”: Traditional photo

output_format

Image file format

“webp”, “png”, “jpeg” PNG: High quality, larger files WebP/JPEG: Compressed, smaller files

output_quality

Compression quality for output

Range: 0-100 Higher values = better quality, larger files Not applicable to PNG format

prompt_strength (img2img)

How much the original image changes

Lower (0.3-0.5): Subtle changes, preserves original Higher (0.7-1.0): Major transformations Default: 0.8

optimization

Some models support runtime optimizations that impact speed and quality

mischallaneous: differs per model and platform

megapixels

Approximate output resolution

“1”: Standard resolution Higher values: Increased detail, slower generation

Tip

Document your parameter choices alongside your prompts. This helps you reproduce successful results and understand which settings work best for different types of images.

Using negative prompts

Not all models support negative prompts. But when they do, they allow you to specify unwanted elements, helping eliminate common issues and refine your output quality.

Common Exclusion Categories:

  • Technical Quality Issues: “blurry”, “low resolution”, “pixelated”, “distorted”

  • Anatomical Problems: “extra digits”, “malformed”, “asymmetrical”

  • Unwanted Elements: “watermarks”, “signatures”, “text overlays”, “brand logos”

  • Style Conflicts: “cartoon style”, “anime aesthetic” (when seeking realism)

"a purple knitted pruna holding a sign that says "pruna endpoints are awesome!" realistic photo on street in Paris on a sunny cheerful day"
https://huggingface.co/datasets/pruna-test/documentation-media/resolve/main/prompt_guide/image_generation/positive.jpeg?download=true

Tweak results with image editing

Once you have a generated image that you’re happy with but you can’t get the exact result you want, you can tweak it with image editing.

Example workflow:

  1. Generate an image

  2. Tweak the image with image editing

See the image editing guide for more information on advanced prompting strategies.

Troubleshooting common issues

Problem

Solution

Check

Try

Image doesn’t match prompt

Simplify the prompt and focus on core elements

Word order and emphasis placement

Using more specific descriptive words

Poor image quality

Add quality enhancement keywords

Technical specifications and lighting

Different quality markers for your style

Unwanted elements appearing

Use negative prompts effectively

Prompt for conflicting elements

More specific positive descriptions

Style inconsistencies

Choose one primary style

For conflicting style keywords

Removing secondary style references

Anatomical issues (extra fingers, etc.)

Add anatomical quality keywords

Negative prompts for common issues

More specific pose descriptions

Next steps