GPT Image 1.5: How to Get Clean Text

Getting text to render cleanly in AI image generators remains one of the most persistent challenges for creators. When you need readable typography in your images—whether for social media graphics, presentation slides, or marketing materials—the frustration of seeing blurred letters, distorted fonts, or completely illegible text can derail your entire workflow. GPT Image 1.5, available on PicassoIA, offers advanced text-to-image capabilities, but still requires specific techniques to produce clean, readable text.

The problem isn't that AI can't generate text—it's that default settings prioritize aesthetic composition over text legibility. This article provides exact, actionable solutions for getting clean text from GPT Image 1.5, covering every aspect from prompt engineering to final output verification.

Above: The precise interface of digital typography generation requires specific prompt engineering to achieve clean text results.

Why Text Rendering Fails in AI Images

AI image generators approach text differently than human designers. These models learn patterns from millions of images where text often appears as visual texture rather than readable content. The training data includes everything from street signs with partially obscured letters to artistic typography where legibility takes second place to aesthetics.

Three primary factors cause text rendering failures:

1. Pattern Recognition Bias: Models recognize text shapes but prioritize visual harmony over character clarity
2. Context Override: Background elements and composition often overpower text visibility
3. Resolution Limitations: Text requires pixel-perfect precision that current models struggle to maintain at smaller sizes

When you prompt for "text" without specifying exact requirements, the model defaults to its most common training examples—where text serves as decorative element rather than communication tool.

Above: Direct comparison shows the dramatic difference between poorly-rendered and clean text in AI image generation.

Prompt Engineering for Text Clarity

Your prompt determines 90% of text quality in GPT Image 1.5 outputs. General descriptions like "add text" or "include words" produce unreliable results. Specific, detailed prompt engineering solves this.

Exact Prompt Syntax That Works

Use this structured prompt format for clean text:

"Professional typography showing the words "[YOUR TEXT HERE]" in crisp, perfectly kerned [FONT NAME] font with 95% contrast against [BACKGROUND DESCRIPTION]. Text positioned at [POSITION] following rule of thirds composition. Each character exhibits pixel-perfect anti-aliasing and optical alignment at [SIZE] point size."

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Key Components:

• Quoted Text: Always enclose your actual text in quotes "text here"
• Font Specification: Name specific fonts (Helvetica Neue, Times New Roman, Arial)
• Contrast Percentage: Specify exact contrast ratio (95%, 90%, 85%)
• Position Reference: Use compositional terms (lower right golden ratio, center aligned)
• Technical Terms: Include "pixel-perfect anti-aliasing", "optical alignment", "crisp edges"

Example Working Prompt:

"Modern graphic design showing the quote \"AI Innovation\" in crisp, perfectly kerned Helvetica Neue Bold with 95% contrast against minimalist white background. Text positioned at lower right golden ratio intersection with perfect optical alignment at 48 point size. Each character exhibits pixel-perfect anti-aliasing and clean edge definition."

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Above: The transition from handwritten prompt notes to digital text generation requires precise language engineering.

Font Specification Techniques

Different fonts render with varying clarity in AI models. Sans-serif fonts generally produce cleaner results than serif fonts at smaller sizes. Here's the hierarchy of font clarity:

Font Recommendations for GPT Image 1.5:

• Helvetica Neue: Most reliable for clean rendering
• Arial: Good alternative with similar characteristics
• Times New Roman: Best serif option for readability
• Roboto: Modern alternative with excellent clarity

Avoid These Fonts for Small Text:

• Comic Sans (poor edge definition)
• Papyrus (texture interference)
• Brush Script (stroke inconsistency)
• Any handwritten or calligraphy fonts below 48pt

Contrast Optimization Strategies

Text visibility depends entirely on contrast against its background. GPT Image 1.5 needs explicit contrast instructions to prioritize readability over aesthetic blending.

Ideal Contrast Ratios for Readability

These ratios ensure text remains readable across different backgrounds:

Prompt Examples for Contrast:

"Black text with 95% contrast against pure white background"
"White text with 90% contrast against dark charcoal background"
"Yellow text with 85% contrast against deep blue gradient"

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Above: Contrast optimization shows the dramatic difference between properly contrasted text and poorly contrasted alternatives.

Background Separation Methods

When text must appear against complex backgrounds, use these separation techniques:

Depth of Field Control:

"Text in sharp focus at f/2.8 aperture with background completely blurred to bokeh"

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Lighting Separation:

"Text illuminated with rim lighting that creates separation from background elements"

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Color Isolation:

"Text appears in complementary color that visually separates from background palette"

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Position Strategy:

"Text positioned in front of simplest background area within the composition"

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Typography Hierarchy Principles

Clean text requires proper hierarchy—larger elements should guide attention to smaller readable elements.

Font Size Relationships

Follow these size ratios for hierarchical clarity:

Prompt Example for Hierarchy:

"Typographic hierarchy showing 'GPT Image 1.5' at 48pt as primary headline, 'Clean Text Solutions' at 36pt as secondary, and descriptive paragraph at 24pt as body text. Each size maintains perfect optical adjustments for its respective scale."

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Above: Proper typography hierarchy creates readable text relationships that guide viewer attention effectively.

Weight and Style Combinations

Font weight affects readability at different sizes:

Style Combinations That Work:

• Headline: Bold (48pt)
• Subhead: Medium (36pt)
• Body: Regular (24pt)
• Caption: Light (16pt)

Positioning and Composition

Where text appears in the frame significantly impacts its readability and perceived importance.

Rule of Thirds for Text Placement

Text positioned at rule of thirds intersections reads more clearly than center-placed text:

Prompt Examples for Positioning:

"Text positioned at lower right rule of thirds intersection"
"Headline aligned to upper left golden ratio point"
"Body text placed along center horizontal third line"

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Above: Strategic text placement according to compositional principles maximizes readability and visual impact.

Negative Space Management

Adequate negative space around text prevents visual crowding:

Negative Space Prompt:

"Text surrounded by generous negative space equal to 2x character width on all sides"

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Using GPT Image 1.5 on PicassoIA

GPT Image 1.5 on PicassoIA offers specific parameters that affect text quality. Understanding these settings improves results.

Model Parameters for Text

These GPT Image 1.5 parameters directly impact text rendering:

Parameter Prompt Integration:

"Generate at maximum quality with high style fidelity to preserve font characteristics"

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Output Quality Settings

Match output resolution to your text size needs:

Resolution Prompt:

"Generate at 2048×2048 resolution to maintain clarity for 24pt text"

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Common Mistakes to Avoid

These errors consistently produce poor text results in GPT Image 1.5.

Text That Disappears

Text blending into background occurs when:

• Contrast below 70%
• Color values too similar
• Background patterns overpower text
• Insufficient size for the distance

Solution Prompt:

"Ensure text maintains 90% minimum contrast against background with distinct color separation"

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Blurred or Distorted Letters

Character distortion happens when:

• Text size too small for resolution
• Complex fonts at small sizes
• Excessive style applications
• Poor edge definition parameters

Solution Prompt:

"Generate text at minimum 24pt size with pixel-perfect anti-aliasing and clean edge definition"

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Above: Font clarity comparison at macro level reveals the detailed differences that affect text readability in final outputs.

Testing Your Text Results

Always verify text quality before finalizing your image.

Quick Verification Methods

1. Zoom Test: View text at 100% zoom—characters should remain crisp
2. Contrast Check: Text should maintain clear separation from background
3. Readability Assessment: Text should be immediately legible at intended viewing distance
4. Edge Examination: Character edges should show clean definition without feathering

Iterative Improvement Process

Follow this workflow for perfect text:

1. Initial Generation: Use basic text prompt
2. Problem Identification: Note specific issues (blur, contrast, positioning)
3. Parameter Adjustment: Modify one variable at a time
4. Re-generation: Test improved prompt
5. Validation: Apply verification methods
6. Final Output: Generate at highest quality

Above: Background separation techniques ensure text remains readable against complex visual environments.

Putting It All Together

Clean text generation in GPT Image 1.5 requires intentional, specific prompting combined with understanding of how the model processes typography. The difference between blurry, unreadable text and crisp, professional typography comes down to exact prompt engineering and parameter control.

Complete Working Example Prompt:

"Professional graphic design showing the phrase \"Digital Innovation\" in crisp, perfectly kerned Helvetica Neue Bold at 36pt size with 95% contrast against minimalist white background. Text positioned at lower right golden ratio intersection with generous negative space equal to 2x character width. Each character exhibits pixel-perfect anti-aliasing, clean edge definition, and optical alignment. Generate at maximum quality with high style fidelity to preserve font characteristics at 2048×2048 resolution."

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This prompt incorporates all successful techniques:

• Specific font specification
• Exact contrast percentage
• Strategic positioning
• Technical quality terms
• Appropriate resolution
• Style preservation parameters

Above: Final showcase of perfect text rendering achieved through systematic application of all optimization techniques.

The most effective approach combines GPT Image 1.5 with other PicassoIA models when needed. For example, use Flux Pro for different text styles or SDXL for alternative rendering approaches. Each model has slightly different text handling characteristics.

What to Do Next:

1. Start with the exact prompt template provided
2. Adjust one variable at a time based on your specific text needs
3. Test different fonts to find which renders most cleanly in your use case
4. Experiment with contrast levels for your particular background
5. Use the verification methods to confirm text quality

The techniques outlined here work because they address how GPT Image 1.5 actually processes text—not how we wish it would process text. By speaking the model's language through specific technical terms, exact measurements, and clear compositional instructions, you transform frustrating text rendering into reliable, clean typography generation.