AI Image Quality Blind Test: Flux vs SDXL vs Midjourney (2025 Study)

Which AI model produces the best images? Everyone has opinions, but we wanted data. We conducted a blind test with 500 participants evaluating images from Flux, SDXL, and Midjourney across multiple categories.

Quick Answer: Midjourney won overall aesthetic preference (42% first choice), but Flux dominated prompt accuracy (67% highest rated). SDXL with custom models competed closely with both. The "best" model depends entirely on your criteria: beauty, accuracy, or flexibility.

Study Methodology

Participant Demographics

We recruited 500 participants through multiple channels:

Age distribution: 18-65, median 32 Geographic: 60% North America, 25% Europe, 15% Other

Models Tested

Flux Dev:

• 50 steps, CFG 3.5
• Standard settings

SDXL (Juggernaut XL):

• 30 steps, CFG 7
• Community-optimized model

Midjourney v6.1:

• Default settings
• Stylize 100

Test Categories

1. Photorealistic Portraits
2. Landscapes and Nature
3. Product Photography
4. Artistic/Stylized
5. Complex Scenes (multiple elements)
6. Text Rendering

Evaluation Protocol

Each participant viewed 24 image sets (4 per category). Each set contained 3 images (one from each model) generated from identical prompts.

Participants rated:

1. Overall quality (1-10)
2. Prompt accuracy (1-10)
3. Which they preferred (forced choice)
4. Which looked "most AI" (reverse quality indicator)

Images were presented in randomized order without model identification.

Overall Results

First Choice Preference

When asked "Which image do you prefer?":

Midjourney's aesthetic appeal gave it a consistent edge in raw preference.

Quality Ratings (1-10)

Higher standard deviation for SDXL indicates more variable quality, expected given model ecosystem diversity.

Prompt Accuracy (1-10)

Flux significantly outperformed on prompt adherence, particularly for complex prompts with multiple elements.

"Looks Most AI" (Lower is Better)

Percentage of times each model was identified as "most AI-looking":

All models occasionally produce obviously AI images. SDXL's variable quality contributed to higher detection.

Category-by-Category Results

Category 1: Photorealistic Portraits

Prompt example: "Professional headshot of a 35-year-old Asian woman, business attire, neutral background, studio lighting"

Analysis: Midjourney's default aesthetic processing creates immediately appealing portraits. Flux followed prompts better but with less "polish."

Category 2: Landscapes and Nature

Prompt example: "Mountain lake at sunrise, snow-capped peaks reflected in still water, pine forest, golden light"

Analysis: Midjourney dominated landscapes. Its built-in enhancement creates dramatic, shareable scenery.

Category 3: Product Photography

Prompt example: "Minimalist perfume bottle on white surface, soft shadows, commercial photography style"

Analysis: Flux's accuracy advantage shines for product photography where specific details matter.

Category 4: Artistic/Stylized

Prompt example: "Cyberpunk street scene, neon lights reflecting on wet pavement, anime style, vibrant colors"

Analysis: Stylized content favored Midjourney and SDXL. Flux tends toward realism even when prompted for stylization.

Category 5: Complex Scenes

Prompt example: "A red-haired woman in a blue dress holding a yellow umbrella, standing in front of a green door, white cat at her feet"

Analysis: Flux dominated complex prompts. Midjourney and SDXL frequently missed or changed elements for "aesthetic improvement."

Category 6: Text Rendering

Prompt example: "Coffee shop storefront with sign reading 'SUNRISE CAFE', warm lighting, brick exterior"

Analysis: Flux's text rendering is dramatically superior. Other models produced garbled or incorrect text consistently.

Demographic Variations

By Expertise Level

AI Enthusiasts preferred:

1. Flux (38%)
2. Midjourney (34%)
3. SDXL (28%)

General Public preferred:

1. Midjourney (48%)
2. Flux (27%)
3. SDXL (25%)

Professional Artists preferred:

1. Midjourney (45%)
2. SDXL (30%)
3. Flux (25%)

Analysis: AI enthusiasts valued Flux's accuracy. General public and professionals prioritized aesthetic appeal.

By Use Case Intent

Participants who stated they would use images for:

Social Media:

• Midjourney: 52%
• Flux: 28%
• SDXL: 20%

Commercial/Professional:

• Flux: 42%
• Midjourney: 38%
• SDXL: 20%

Personal Projects:

• Midjourney: 40%
• SDXL: 35%
• Flux: 25%

Statistical Significance

We calculated statistical significance for key findings:

Results are statistically significant at α=0.05 level with sufficient sample size.

Limitations and Caveats

Study Limitations

1. Model versions: Results specific to tested versions (Jan 2025)
2. Settings: Different settings could change results
3. SDXL model choice: Different fine-tunes would vary
4. Prompt optimization: Prompts weren't optimized per model
5. Sample size: 500 participants, may not represent all users

What This Study Doesn't Measure

• Generation speed
• Cost per image
• Consistency across generations
• Advanced feature capabilities
• NSFW content quality
• Video generation capability

Implications and Recommendations

For Different Users

Choose Midjourney if:

• Aesthetic appeal is primary goal
• Working with landscapes, portraits
• Want consistent "beautiful" output
• Don't need precise prompt control

Choose Flux if:

• Prompt accuracy is critical
• Need text in images
• Working with complex multi-element scenes
• Technical/commercial applications

Choose SDXL if:

• Need maximum flexibility
• Using LoRAs for specific styles
• Budget-conscious
• Want local generation control

For Specific Tasks

Comparison with Other Studies

Our findings align with and extend previous research:

Aligned findings:

• Midjourney aesthetic preference confirmed
• Flux prompt accuracy advantage confirmed
• SDXL flexibility advantage confirmed

New contributions:

• Quantified preference percentages
• Category-specific analysis
• Demographic variations documented
• Statistical significance established

Frequently Asked Questions

Which model is objectively "best"?

None. "Best" depends on criteria. Midjourney for aesthetics, Flux for accuracy, SDXL for flexibility.

Should I trust this study?

Consider limitations. Use as data point alongside your own testing. Results specific to study conditions.

Will these results change over time?

Yes. Models update frequently. Re-testing recommended annually.

Why didn't SDXL do better?

SDXL's power comes from fine-tuned models and LoRAs. Base/standard models test lower than optimized setups.

How do I reproduce this test?

Contact us for prompts and methodology details. We encourage replication studies.

Did participants know it was AI?

Yes, they knew all images were AI-generated. They didn't know which model produced which image.

What about newer models?

This study covers models available as of January 2025. SD3.5 and future models not included.

Wrapping Up

Our blind test confirms what many suspected: there's no single "best" AI image model.

Key findings:

1. Midjourney leads aesthetic preference (42% overall)
2. Flux dominates prompt accuracy (67% for complex scenes)
3. SDXL offers competitive results with more variance
4. Use case should drive model choice

The "best" model is the one that best serves your specific needs. For beautiful landscapes and portraits, Midjourney excels. For accurate commercial work, Flux leads. For maximum control and customization, SDXL's ecosystem is unmatched.

For model comparisons beyond quality, see our Flux vs SDXL vs Midjourney guide. For hands-on testing, try Apatero.com.

Research Data Availability

Anonymized response data from this study is available for academic and research purposes. Full prompt sets and methodology documentation can be provided upon request.

Study conducted January 2025. Results reflect model versions and settings at time of testing.

Appendix: Sample Prompts Used

Portrait Category:

• "Professional headshot of a 35-year-old Asian woman..."
• "Elderly man with white beard, kind eyes, natural lighting..."
• "Young professional in casual setting, authentic expression..."

Landscape Category:

• "Mountain lake at sunrise, snow-capped peaks..."
• "Dense forest with sunbeams filtering through trees..."
• "Desert landscape at golden hour, dramatic shadows..."

Complex Scene Category:

• "Red-haired woman in blue dress with yellow umbrella..."
• "Coffee shop interior with three people, specific positions..."
• "Street scene with car, bicycle, and pedestrian, specific colors..."

Full prompt list available in supplementary materials.

Additional Analysis: Consistency Across Prompts

Model Reliability

We also measured how consistent each model was across multiple generations of the same prompt:

Midjourney's built-in prompt interpretation creates more consistent outputs, while SDXL's flexibility leads to wider variation.

Generation Failure Rate

Percentage of generations that failed to meet basic quality standards:

Participant Feedback Themes

Common qualitative feedback included:

About Midjourney:

• "Always looks professional"
• "Sometimes ignores what I asked for"
• "Great colors and lighting"

About Flux:

• "Gets the details right"
• "Sometimes feels clinical"
• "Best for specific requirements"

About SDXL:

• "Results vary wildly"
• "When it works, it really works"
• "Needs more iteration"

Study Implications

For Casual Users

The data suggests Midjourney is the safest choice for users who want consistently appealing results without extensive prompt engineering.

For Professionals

Flux's accuracy advantage makes it preferable for commercial work where specifications must be met precisely.

For Enthusiasts

SDXL's ecosystem and flexibility reward those willing to invest time in optimization and LoRA selection.

This research provides a data-driven foundation for model selection decisions, complementing subjective preferences with measurable outcomes.