Prompt Weighting Syntax: Complete Guide 2025

Prompt weighting gives you precise control over AI image generation. Instead of hoping the AI emphasizes what matters, you can explicitly boost or reduce attention to specific concepts.

Quick Answer: Use (word:1.3) to increase emphasis (1.3x attention) or (word:0.7) to decrease it. BREAK separates prompt sections, AND blends concepts. Syntax varies slightly between platforms.

Basic Weighting Syntax

Parentheses Notation

The standard format for SD 1.5, SDXL, and ComfyUI:

(word:weight)

Examples:

• (red hair:1.3) — 30% more attention to red hair
• (background:0.7) — 30% less attention to background
• (detailed eyes:1.5) — 50% more attention to eye detail

Weight Ranges

Safe Range: 0.5 to 1.5. Beyond this, expect quality issues.

Multiple Parentheses Notation

Alternative syntax using stacked parentheses:

(word) = 1.1x
((word)) = 1.21x (1.1 × 1.1)
(((word))) = 1.33x

Equivalent:

• (red hair) ≈ (red hair:1.1)
• ((red hair)) ≈ (red hair:1.21)

This notation is less precise but faster to type.

The BREAK Keyword

BREAK separates prompt sections, preventing concept bleeding:

beautiful woman in red dress BREAK
forest background with sunlight BREAK
cinematic lighting, film grain

How It Works:

• Each section is processed somewhat independently
• Reduces unintended associations between concepts
• Particularly useful for separating subject from background

Use Cases:

• Subject vs environment separation
• Style vs content separation
• Multiple distinct elements

The AND Syntax

AND blends concepts with controllable weights:

portrait of a woman AND watercolor painting style::0.5

This creates a blend: full portrait concept + half-strength watercolor style.

Syntax:

concept1 AND concept2::weight

Examples:

cat AND dog::0.5        # Cat with subtle dog features
photo AND painting::0.7  # Photo with painterly quality

Platform-Specific Syntax

AUTOMATIC1111 / ComfyUI

(word:1.3)           # Weight syntax
BREAK                # Section separator
[word]               # Decrease by 1.1x (legacy)
{word}               # NOT SUPPORTED (use weight:0.x)

Midjourney

word::2              # Double weight
concept1::2 concept2::1  # Relative weighting
--no word            # Negative (avoid this)

Flux

Flux has limited weighting support:

• Natural language prompts work best
• Explicit weights have minimal effect
• Focus on prompt clarity instead

SD 3.5

Similar limitations to Flux:

• Designed for natural language
• Weighting less effective
• Write descriptive prompts

Practical Examples

Portrait Enhancement

portrait of a woman with (piercing blue eyes:1.3),
(flowing red hair:1.2), (soft skin:1.1),
(background:0.7), studio lighting

Landscape Control

mountain landscape BREAK
(snow-capped peaks:1.3), pine forest,
(dramatic clouds:1.2) BREAK
golden hour lighting, (mist in valley:1.1)

Style Mixing

portrait in the style of (oil painting:1.2)
AND (art nouveau:0.8), detailed brushwork

Concept Balance

(cyberpunk city:1.0) AND (nature reclaiming:0.6),
overgrown buildings, vines, (neon signs:0.8)

Advanced Techniques

Scheduled Weighting

In ComfyUI, weights can change during generation:

[word:alternate:0.5]  # Switch at 50% of steps

Early steps: "word" Later steps: "alternate"

Regional Prompting

Combine with regional prompter for spatial control:

• Different weights in different image regions
• Subject boosted in center, background reduced at edges

Dynamic Weights

Some workflows support weight interpolation:

• Start with high weight, reduce over steps
• Gradual concept introduction

Troubleshooting Weights

Issue: Weights have no effect

• Check syntax for your platform
• Ensure weight is different from 1.0
• Some models respond less to weights

Issue: Artifacts at high weights

• Reduce weight below 1.5
• Split into multiple lower-weighted terms
• Use BREAK to isolate concepts

Issue: Prompt too complex

• Simplify by removing low-priority weights
• Focus weights on 2-3 key elements
• Let the model handle details naturally

Issue: Unexpected results

• Check for conflicting weights
• Ensure BREAK is uppercase
• Verify parentheses are balanced

Best Practices

1. Weight sparingly: Only boost what matters most
2. Stay in safe range: 0.5-1.5 for reliability
3. Use BREAK: Separate subject from background
4. Test incrementally: Adjust weights one at a time
5. Know your platform: Syntax varies significantly
6. Natural language first: Good prompts need less weighting

Frequently Asked Questions

Do weights work in negative prompts?

Yes, but use carefully. Boosting a negative concept can have unexpected effects.

Can I weight phrases, not just words?

Yes: (beautiful sunset over mountains:1.3) weights the entire phrase.

Why doesn't my weight work in Flux?

Flux uses a different architecture where explicit weights have minimal impact. Focus on prompt quality.

What's the maximum effective weight?

Around 1.5-2.0. Higher values cause artifacts without additional emphasis.

Should I weight everything?

No. Weight only 2-4 key elements. Over-weighting makes prompts less effective.

Conclusion

Prompt weighting transforms vague prompts into precise instructions. Master the syntax for your platform, use weights strategically on key elements, and combine with BREAK for clean concept separation.

Remember: well-written prompts need less weighting. Use these tools to fine-tune, not to force poorly structured prompts to work.