Flux Kontext Prompt Library - Expert Prompts & Templates
Access our curated collection of Flux Kontext prompts and templates. Master image editing with proven prompts from ImageGPT experts.
All
Object Editing
People Removal
Style Transfer
Background Replace
Character Consistency
Text Editing
Change Haircut
Headshot


Auto
Pearl Earring Headscarf Color Change
portrait
classic
+3


Auto
Hair Color Transformation
portrait
hair
+3


Auto
Sketch to Photorealistic Portrait
sketch
realistic
+3


Auto
Facial Expression Modification
portrait
expression
+3


Auto
Indoor to Garden Background Replace
background
environment
+3


Auto
Casual to Business Attire
clothing
fashion
+3


Auto
Age Progression with Feature Consistency
age
progression
+3


Auto
Van Gogh Style Transformation
art
style
+3


Auto
Long to Short Bob Haircut
haircut
bob
+3


Auto
Curly to Straight Hair Transformation
haircut
straight
+3


Auto
Pixie Cut Transformation
haircut
pixie
+3


Auto
Professional LinkedIn Headshot
professional
linkedin
+3


Auto
Social Media Profile Picture
social-media
profile
+3


Auto
Corporate Executive Headshot
corporate
executive
+3


Auto
Store Sign Text Replacement
sign
store
+3


Auto
Remove Person from Any Scene
removal
building
+4


Auto
Remove Person from Any Scene
removal
building
+5
Flux Kontext Expert Guide & FAQ
Essential questions and answers about Flux Kontext capabilities, best practices, and optimization techniques
What is Flux Kontext and how does it revolutionize image editing?
Flux Kontext is a revolutionary family of AI models by Black Forest Labs that transforms image editing using natural language instructions. Unlike traditional tools that regenerate entire images, Flux Kontext makes targeted edits with surgical precision while preserving the rest of the image intact.
How do the different Flux Kontext model versions compare?
Flux Kontext offers three versions:
- [Pro] - Provides state-of-the-art performance with high-quality outputs and great prompt following
- [Max] - The premium model with maximum performance and improved typography generation
- [Dev] - The upcoming open-weight version for developers and research
What are the key features that make Flux Kontext superior to competitors?
Key advantages of Flux Kontext:
- 10x faster and cheaper than competitors like OpenAI's GPT-4o
- 6-12 second generation times
- Superior accuracy in preserving original details
- Avoids color tinting issues
- Excels at maintaining character consistency across edits
How do I write effective prompts for basic image edits with Flux Kontext?
Best practices for basic prompts:
- Use specific verbs like 'change', 'add', 'remove', 'replace'
- Be precise: 'change the wall color to blue' instead of 'make it blue'
- For text changes, use quotation marks: 'Replace "SALE" with "SOLD"'
- Start simple and build complexity iteratively
What prompting techniques ensure character consistency across different scenes?
Character consistency techniques:
- Include preservation phrases like 'while keeping the same facial features' or 'maintaining the original character appearance'
- Use direct naming: 'the woman with short black hair' instead of pronouns
- Example: 'Change background to beach while keeping person in exact same position'
How do I write prompts for complex style transfers and artistic effects?
Style transfer best practices:
- Name styles explicitly: 'convert to 90s cartoon style' or 'transform into watercolor painting'
- Always specify what to preserve: 'maintain original composition while converting to pencil sketch'
- Break complex transformations into step-by-step prompts
What are the best practices for text editing prompts in Flux Kontext?
Text editing guidelines:
- Always use quotation marks for exact text replacements
- Example: 'Change the text in sunglasses to "FLUX" and "Kontext"'
- Be specific about text location: 'Replace the sign text with "Welcome"'
- This ensures Flux Kontext targets correct text while preserving styling
How should I structure prompts for product visualization and brand assets?
Product visualization strategies:
- Be specific about product context: 'Show the sneakers on a wooden floor with natural lighting'
- For brand modifications: 'Change logo color to corporate blue while maintaining design proportions'
- Include environment details for better visualization results
What prompting strategies work best for background changes and object removal?
Background and object modification:
- Use precise location descriptions: 'Replace background with mountain landscape while keeping same perspective'
- For removal: 'Remove the person on the left while maintaining natural composition'
- Always specify what should remain unchanged to avoid unwanted alterations
How do I write iterative prompts for complex image transformations?
Iterative prompting approach:
1. Start with simple edits: 'Remove background'
2. Then add complexity: 'Add forest setting'
3. Finally refine: 'Adjust lighting to match environment'
- Build complexity gradually rather than attempting everything in one prompt
- Each step should reference previous successful changes
What common prompting mistakes should I avoid with Flux Kontext?
Common mistakes to avoid:
- Vague instructions like 'make it better'
- Using pronouns instead of descriptive phrases
- Overloading prompts with multiple changes
- Ambiguous commands that could cause context-slip where the model misinterprets your intent
How do I optimize prompts for speed and quality in Flux Kontext?
Optimization strategies:
- Use high-quality, well-lit source images for best results
- Make one change per prompt to ensure accuracy
- Include control phrases like 'maintain original composition' to prevent unwanted changes
- Clear, specific language yields faster, more accurate results
What types of images and use cases work best with Flux Kontext prompting?
Optimal use cases:
- Image types: Photos, drawings, paintings, and digital art
- Best applications:
- Quick color/style changes
- Character consistency for storytelling
- Product visualization
- Brand asset adaptation
- Iterative design workflows
Note: Clear, well-lit images yield optimal results