Leonardo AI Review: Real-World Testing of This AI Image Generator For Affiliate Marketing and Personal Brands

This Leonardo AI review is based on the past four months to build Empire Forged’s visual identity—brand images, lead magnet graphics, and on-brand assets. Here’s what actually works, what falls short, and whether it’s worth your time and money.

No hype. Just what I learned building with it.

The Problem: Most AI Image Tools Are Either Expensive or Limited

If you’ve tried generating images for your business, you’ve hit one of these walls:

Midjourney requires Discord and a $10/month minimum. Great outputs, terrible workflow for batch creation.

DALL-E 3 through ChatGPT Plus costs $20/month but gives you slow generation and limited control over style consistency.

Stable Diffusion is free but demands technical setup, model management, and hours of prompt engineering before you get usable results.

You need something that generates quality images without eating your budget or requiring a computer science degree. That’s where Leonardo AI sits—and why this Leonardo AI review exists in the first place.

What Leonardo AI Actually Does

Leonardo AI is a web-based image generator built on fine-tuned Stable Diffusion models (basically customized versions of the open-source AI that powers most image generators). You write a text prompt (a description of what you want), pick a model style, adjust a few settings, and generate 4-8 images in about 15-30 seconds.

Key features I actually use:

• 50+ AI models (photorealistic, illustration, anime, 3D render, cinematic styles)—think of these as different “art styles” the AI can use
• Flow State mode (rapid-fire image generation that lets you click toward what you want instead of rewriting prompts)
• Image-to-image generation (upload a reference image, AI modifies it based on your prompt)
• Canvas editor for inpainting and outpainting (editing specific parts of an image or extending it beyond its borders)
• Prompt generation tool (helps if you’re stuck on how to describe what you want)
• Elements feature (style presets that apply consistent visual characteristics like lighting, color grading, and composition)
• Fine control over guidance scale (how closely AI follows your prompt), sampling steps (quality vs. speed), schedulers (different algorithms that affect the final look), and seeds (numbers that let you recreate or iterate on specific images)
• API access on paid tiers (lets you automate image generation through code—useful for scaling)

What it’s built for: Marketing visuals, concept art, product mockups, social media graphics, brand assets, and content illustration.

What it’s not: A replacement for professional photography or a complete hands-off solution. You’ll still need basic editing skills and brand judgment to refine outputs.

Real Results: What I Built With Leonardo AI

Test 1: Empire Forged Brand Images

Goal: Generate consistent brand images for Empire Forged’s visual identity across the site.

Process: Used the “Google Nano Banana Pro” model (a photorealistic model that produces clean, modern images) with prompts like “minimalist workspace with laptop and coffee, soft natural lighting, clean desk setup.”

Results:

• Almost all images were usable without edits
• Average generation time: 22 seconds per batch of 4 images
• Cost: 200 tokens (roughly $0.40 worth on the Apprentice plan)

What worked: Consistency across the set. All images had a similar aesthetic, which kept the site looking cohesive. The model understood “minimalist” and “clean” without overcomplicating the scenes.

What didn’t: Outputs were stellar, but some needed minor tweaks for brand color consistency. Getting that specific orange accent (#FF6B35) required post-processing in Canva rather than being baked into the generation.

Test 2: Lead Magnet Graphics

Goal: Create custom lead magnet graphics for ebooks and downloadable resources.

Process: Used the “Leonardo Lightning” model (a faster model optimized for stylized, abstract images) with their Elements feature. Prompts focused on abstract concepts related to affiliate marketing, content creation, and entrepreneurship.

Results:

• 100+ images generated across multiple concepts
• Roughly 50% were usable as-is
• The other half required editing in Canva for custom branded text and minor graphical enhancements

What worked: Abstract visuals are Leonardo’s sweet spot. Incredible outputs, mostly on target for what I had in mind. The Elements feature (think of these as Instagram filters but for AI generation—they apply consistent lighting, color, and composition rules) dramatically improved consistency—once I found the right Element, I could generate variations that all felt cohesive.

What didn’t: Color control. I wanted that specific orange accent (#FF6B35) but couldn’t force it consistently without multiple regenerations. I ran multiple iterations with varied prompts to dial them in, which ate more tokens than expected.

Real talk: Budget 2-3x the tokens you think you’ll need for abstract concept work. The first batch rarely nails it, but iterations get you there.

Flow State saved me here: When I wasn’t sure exactly what style I wanted for a particular lead magnet, I switched to Flow State mode. Instead of generating 4 images, waiting, tweaking my prompt, and repeating, Flow State streamed dozens of variations continuously. I clicked on the ones that felt close, adjusted the vibe and lighting sliders, and let it generate new waves based on those selections. This “I’ll know it when I see it” approach cut my exploration time in half—I found the right aesthetic direction in 10 minutes instead of burning an hour on prompt rewrites.

Test 3: Empire Forged On-Brand Assets

Goal: Generate background images, icons, favicons, and supporting visual assets.

Process: Used the “Lucid Origin” model (specializes in cinematic, high-detail scenes with dramatic lighting) with prompts like “sprawling modern city empire, stunning views at sunset with global lighting and HD details.”

Results:

• 50+ backgrounds and brand assets generated in just minutes
• Combined with text overlays, color overlays, and other edits in Canva
• Used across email headers, social graphics, and site backgrounds

What worked: Speed. I could test 3-4 background concepts in the time it would take to find and license one stock photo. The Lucid Origin model excels at cinematic, high-detail scenes—perfect for hero backgrounds.

What didn’t: Fine details were tricky to dial in initially. Early attempts had inconsistent lighting or odd compositional elements. But Leonardo has had radical, consistent development since I started using it. Features that were clunky four months ago are now smooth. What used to take 20 regenerations now takes 3-5.

Key learning: Leonardo AI improves fast. If you tested it six months ago and dismissed it, revisit it. The platform evolves weekly.

How Leonardo AI Compares to Alternatives

For this Leonardo AI review, I tested Leonardo against three other tools I’ve used in the past six months.

Feature	Leonardo AI	Midjourney	DALL-E 3	Stable Diffusion (Local)
Ease of Use	Full web app with organized dashboards	Discord-based (clunky)	ChatGPT integration (easy)	Requires technical setup
Image Quality	9/10	9/10	7/10	9/10 (with tuning)
Speed	15-30 seconds	30-60 seconds	45-90 seconds	10-20 seconds (local GPU)
Cost (Monthly)	$10 for 8,500 tokens	$10 for ~200 images	$20 (ChatGPT Plus)	Free (hardware cost upfront)
Commercial Rights	Included on paid plans	Included	Included	Included (open source)
Consistency	Excellent with Elements & custom models	Excellent	Moderate	Excellent (with LoRAs)
Fine Control	Extensive (guidance, steps, schedulers, seeds)	Limited (prompt-only)	Minimal	Maximum (requires expertise)
API Access	Yes (paid plans)	No	Yes (OpenAI API)	Yes (local or cloud)
Development Speed	Rapid (weekly updates)	Moderate	Slow	Community-driven (variable)
Model Variety	50+ models across every style	Single engine, style via prompts	Single model	Unlimited (manual management)
Integrated Workflow	Generation → upscale → edit → export in one UI	Generation only	Generation only	Requires multiple tools/plugins
Rapid Ideation	Flow State mode for continuous exploration	None	None	Requires manual batch scripting

Bottom line: Leonardo AI delivers top-tier image quality matching or exceeding Midjourney, with significantly better workflow tools and control. It captures 70-90% of what makes local Stable Diffusion powerful while eliminating 90% of the setup pain. For practical creator and marketing workflows, it’s the strongest all-around platform I’ve used.

Why Leonardo AI Actually Wins for Real Work

1. Image Quality Is Stellar Across Insane Model Variety

Leonardo doesn’t just compete with Midjourney on quality—it matches or beats it depending on the model you choose. I’ve generated hundreds of images across both platforms. Here’s what I found:

Photorealistic outputs: Leonardo’s “Absolute Reality v1.6” and “DreamShaper v7” models (both trained specifically on realistic photos and scenes) produce cleaner, more controllable results than Midjourney’s photorealism attempts. Less uncanny valley, more usable first-generation outputs.

Stylized and concept art: Leonardo’s “Anime Pastel Dream,” “RPG v5,” and “3D Animation Style” models (each trained on specific art styles) give you Midjourney-level aesthetics with better consistency across batches.

Cinematic and hero images: “Lucid Origin” and “Leonardo Vision XL” (models optimized for dramatic lighting and composition) rival Midjourney’s best outputs. I’ve used both for Empire Forged hero backgrounds—Leonardo won on speed and iteration control.

The difference isn’t just quality—it’s choice. Midjourney forces you to describe style in your prompt and hope the algorithm interprets it correctly. Leonardo gives you 50+ models, each trained on specific aesthetics. Pick the model that matches your vision, write a simpler prompt, get better results faster.

2. Flow State Mode Changes How You Find the Right Image

This is the feature I wish I’d discovered in week one instead of month two.

What Flow State does: Instead of generating fixed batches of 4 images and waiting, Flow State streams continuous variations from a single prompt. You click on images that feel close to what you want, adjust high-level controls like vibe, lighting, shot type, and color theme, and Leonardo generates new waves based on your selections.

Why it matters: Most of the time, you don’t know exactly what you want until you see it. Writing the perfect prompt is hard. Flow State lets you click your way toward the image in your head instead of playing prompt roulette.

How I use it:

When I’m exploring a new visual direction (like finding the right style for a lead magnet series), I start in Flow State. I write a basic prompt—”abstract concept representing digital entrepreneurship”—and let it stream variations. I click the 3-4 that feel right, tweak the lighting slider toward “dramatic,” adjust the vibe toward “modern,” and watch new options flow in.

Once I find the direction I want, I switch back to Classic Mode or Canvas for precision work. Flow State gets me 80% of the way there in 10 minutes. Classic Mode gets me the final 20%.

The cost trade-off: Each Flow State image consumes tokens, so you’re trading speed of exploration for higher credit burn if you scroll endlessly. I budget 500-800 tokens for a Flow State exploration session, which usually gives me 2-3 solid directions to pursue.

Best for:

• Fast concepting and mood boards
• “I’ll know it when I see it” scenarios
• Learning what different models and styles can do
• Exploring visual directions before committing to detailed prompts

Not for:

• Exact compositions or layouts (use Classic Mode after you find your direction)
• Typography or text-heavy work (use Nano Banana Pro in Classic Mode)
• Budget-conscious generation (Flow State eats tokens faster than batch generation)

Real example: I needed a hero background for a new email sequence. I had a vague idea—”modern city, aspirational, sunset lighting”—but couldn’t nail the exact composition. Spent 15 minutes in Flow State, clicked through maybe 40 variations, found three I liked, refined one in Classic Mode. Total time: 20 minutes. Total cost: 600 tokens. Without Flow State, I would’ve spent an hour rewriting prompts and burning similar tokens anyway.

3. All-in-One Workflow Beats Tool-Switching Hell

Here’s what a typical image creation workflow looks like across platforms:

Midjourney:

1. Write prompt in Discord
2. Wait for generation
3. Upscale in Discord (increase resolution for final use)
4. Download
5. Open Photoshop/Canva for edits
6. Export final

DALL-E 3:

1. Write prompt in ChatGPT
2. Wait for generation
3. Download
4. Open editing tool for refinements
5. Export final

Local Stable Diffusion:

1. Choose checkpoint (the base AI model file)
2. Load LoRAs (additional training files that modify the model’s style)
3. Configure sampler (the algorithm that generates the image), steps (quality iterations), CFG (how closely it follows your prompt)
4. Generate
5. Switch to img2img (image-to-image mode) for refinements
6. Upscale in separate node (a separate processing step)
7. Export final

Leonardo AI:

1. Pick model (or use Flow State to explore)
2. Write prompt
3. Generate
4. Upscale, inpaint (edit specific areas), or edit in the same interface
5. Export final

Leonardo’s Canvas editor, built-in upscaler (resolution enhancer), and integrated refinement tools mean I stay in one browser tab from concept to final asset. This isn’t a minor convenience—it’s a 30-40% time savings on every image I produce.

4. Fine Control Without the Learning Curve

Leonardo exposes the controls that matter—guidance scale (how strictly the AI follows your prompt), sampling steps (more steps = higher quality but slower), scheduler type (different algorithms that affect the final look), negative prompts (telling the AI what to avoid), seed control (a number that lets you recreate or iterate on specific results)—without requiring you to understand ComfyUI node graphs (complex visual programming interfaces) or A1111 settings panels (Automatic1111, a popular but technical Stable Diffusion interface).

What this means in practice:

• I can lock a seed and iterate on prompt variations to test specific changes
• I can adjust guidance scale to dial in how closely the AI follows my prompt
• I can use negative prompts to exclude specific elements without regenerating from scratch
• I can switch schedulers (DPM++, Euler, DDIM—different mathematical approaches to image generation) to change output style without changing models

Midjourney gives you none of this. DALL-E 3 gives you almost none of this. Local Stable Diffusion gives you all of this plus 500 other settings you don’t need and have to research to understand.

Leonardo sits in the sweet spot: enough control to produce professional work, not so much complexity that you need a PhD to use it.

5. Elements Feature Is Unmatched

Elements are style presets that apply consistent aesthetic characteristics across generations. Think of them as professional photo filters that control lighting, color grading, depth of field, and composition—but applied during AI generation instead of after.

I use the “Cinematic” Element for hero backgrounds. It automatically applies:

• Global illumination (realistic light bouncing and shadows)
• Depth of field (professional camera focus effects)
• Color grading (film-like color treatment)
• Composition rules (professional framing and balance)

Without me having to describe any of that in my prompt.

Result: My prompts are shorter, my outputs are more consistent, and my iteration time is cut in half.

Midjourney has no equivalent. DALL-E 3 has no equivalent. Local Stable Diffusion has LoRAs (additional training files you download and manage manually), but you have to find them, download them, manage versions, and configure trigger words (specific phrases that activate the LoRA’s effects). Leonardo’s Elements just work.

6. Rapid Development Means It Gets Better Weekly

Leonardo ships meaningful updates every week. Features that didn’t exist when I started using it four months ago:

• Alchemy v2 (enhanced quality mode that produces sharper, more detailed images)
• PhotoReal v2 (improved photorealistic portrait generation with better skin texture and lighting)
• Canvas layers (Photoshop-style layer system for complex edits)
• Transparent background generation (creates images with no background, ready for design work)
• Motion generation (early access to turning static images into short video clips)
• Flow State mode (continuous image streaming for rapid exploration)

Midjourney updates every few months. DALL-E 3 barely updates at all. Local Stable Diffusion updates constantly, but you have to manually pull new checkpoints (download new model files), update extensions (plugins), and troubleshoot breaking changes (when updates break your existing setup).

Leonardo’s development pace means the platform improves alongside your needs. What was a 7/10 feature in January is a 9/10 feature by March.

7. Pricing Is Transparent and Competitive

Leonardo AI Apprentice Plan: $10/month for 8,500 tokens

• Roughly 200-300 final images after iterations and upscaling
• Commercial rights included (you can use images in your business)
• API access included (automate generation through code)
• No hidden fees, no surprise overages

Midjourney Basic Plan: $10/month for ~200 images

• No API
• Discord-only workflow
• Limited control over outputs

DALL-E 3 via ChatGPT Plus: $20/month

• Slower generation
• No fine control
• Limited to ChatGPT interface

Local Stable Diffusion: Free after hardware investment

• Requires 800-1,500 GPU (graphics card powerful enough to run AI models locally)
• Requires technical knowledge (command line, model management, troubleshooting)
• Requires time for setup, maintenance, troubleshooting

For anyone building a business, Leonardo’s pricing is better. You get more control than Midjourney, better workflow than DALL-E 3, and none of the technical overhead of local Stable Diffusion.

8. API and Automation Support

Leonardo’s API (Application Programming Interface—a way to control the tool through code instead of clicking buttons) lets you automate image generation for:

• Batch processing lead magnet covers
• Dynamic social media graphics
• Programmatic product mockups
• Custom integrations with your existing tools

I haven’t fully explored this yet, but the fact that it exists—and that Midjourney still doesn’t offer a public API—matters if you’re scaling.

Leonardo AI Pricing: What You Actually Get

Leonardo AI uses a token system instead of simple monthly limits. Tokens are credits you spend on different actions—1 token for a standard generation, 5 tokens for upscaling, etc.

Free Plan

• 150 tokens per day
• 1 token = 1 standard image generation (4 images)
• Access to all models except premium fine-tunes
• No API access
• No commercial use rights

Real talk: The free plan is usable for testing but not sustainable for business use. 150 tokens = about 150 images per day, but only if you’re generating standard resolution. Upscaling and advanced features eat tokens fast.

Apprentice Plan – $10/month

• 8,500 tokens per month
• Commercial rights included
• Priority generation queue (faster processing)
• API access (25 calls/month)

My take: This is the plan I use. 8,500 tokens covers roughly 200-300 final images per month depending on how much you regenerate and upscale. For brand graphics, lead magnets, and site visuals, it’s enough.

Artisan Plan – $24/month

• 25,000 tokens per month
• Faster generation
• API access (100 calls/month)
• Early access to new models

Who needs this: If you’re generating images daily for multiple projects or clients, this makes sense. For a solo builder running one or two brands, it’s overkill unless you’re also selling the images.

Maestro Plan – $48/month

• 60,000 tokens per month
• Highest priority queue
• Unlimited API calls
• Private image generation (not added to public gallery)

Skip it unless: You’re running an agency or selling AI-generated assets at scale.

What Leonardo AI Gets Right

1. Model Variety Without Complexity

You’re not managing checkpoints (large AI model files), LoRAs (style modification files), or embeddings (additional training data). Pick a model from the dropdown, generate, done. With 50+ models covering every aesthetic from photorealistic to anime to 3D renders, you find what works for your brand and stick with it.

2. Batch Generation Speed

Need 20 variations of a concept? Generate 4 at a time, pick the best, iterate. This workflow is faster than Midjourney’s single-image-per-prompt approach and more efficient than DALL-E’s slow processing.

3. Transparent Token System

You know exactly what each action costs. No surprise overages, no “fair use” ambiguity. 1 standard generation = 1 token. Upscaling = 5 tokens. Elements usage = clearly marked. Simple.

4. Canvas Editor for Refinement

The inpainting tool (lets you select and regenerate specific parts of an image) lets you fix problems without starting over. I’ve used this to fix backgrounds, remove objects, and adjust compositions without burning tokens on full regenerations.

5. Integrated Workflow Saves Hours

Generation, upscaling, editing, and export all happen in one interface. No switching between Discord, Photoshop, and file managers. This alone saves 30-40% of my image production time.

What Leonardo AI Actually Gets Right (and Where It Still Falls Short)

1. Text Generation Is No Longer “Completely Broken”

Older AI image models turned any on-image text into gibberish, but that’s not the current state of Leonardo. With Google’s Nano Banana and Nano Banana Pro models integrated, Leonardo can now render clean, readable text on signs, labels, book covers, thumbnails, and infographics with high accuracy—often in a single pass.

How it really works now:

For text-heavy images, you switch to Nano Banana or Nano Banana Pro inside Leonardo. These models are specifically optimized for legible, structurally correct text across 100+ languages.

In practice, you can get 90-95%+ accurate text on the first try for headlines, short phrases, thumbnails, covers, and UI labels. You only clean up edge cases in Canva or Photoshop instead of rebuilding everything from scratch.

My testing:

• Generated 20+ lead magnet covers with titles and subtitles
• 18 out of 20 had perfectly readable text on the first generation
• The 2 that didn’t required minor letter corrections in Canva

The catch: You have to use the right model. If you generate with older or generic models and then complain about text, that’s user error, not a 2025 technical limitation. Nano Banana Pro is the model for text-heavy work—use it.

2. Exact Color Control: Still Not Hex-Perfect, But Manageable

Leonardo still doesn’t natively support “strict hex input” in the prompt the way a design tool does—so you can’t just type #FF6B35 and expect a Pantone-level match across every pixel. However, saying you “can’t control color” is misleading.

The reality now:

You can drive color very close to a brand palette using structured prompts, reference images, and style presets. For example: “Empire Forged brand orange, similar to hex #FF6B35, high saturation, high contrast.”

For mission-critical brand work (logos, UI elements, print materials), the professional workflow is: generate layout and lighting in Leonardo → sample and lock exact hex in Figma or Photoshop afterward. That’s not a Leonardo failure; that’s just how serious brand production works today.

My workflow:

• Generate the image with color descriptions close to brand guidelines
• Export to Canva
• Apply a color overlay or adjustment layer to lock in #FF6B35 exactly
• Total extra time: 30-60 seconds per image

Bottom line: Ultra-precise color matching still needs a design tool in the final 10%, but you can absolutely get close enough for web creative inside Leonardo without “30 regenerations.”

3. Batch Editing: Limited Natively, Great via Automation

Native Leonardo still doesn’t feel like Lightroom for bulk edits—you can’t open a grid of 50 images and apply the same manual crop and color tweak with one in-app click. That part of the criticism is fair.

What has changed:

You can batch-generate and batch-upscale sets of images in one go using Leonardo’s workflows and upscaler, which cuts a lot of friction when building asset packs.

For real batch editing (tens or hundreds of images with the same prompt or transformation), creators now hook Leonardo into automation platforms like Make, Zapier, or custom scripts to feed prompts from Google Sheets and process at scale.

My setup:

• I generate 10-20 variations of a concept in one batch
• Upscale the best 5-10 in a single action
• Export and do final color/crop adjustments in Canva using batch templates

So:

• “No native batch editing UI like Lightroom” → still basically true
• “No way to batch process with Leonardo” → false; serious users wire it into automation tools and let the API handle the bulk work

4. Token Costs: Real, But Manageable with the Right Models & Workflow

Tokens absolutely still matter—and if you spam abstract prompts, keep switching models, and redo every generation at max quality, you will chew through a plan fast. That part of the criticism still stands.

However, the economics have shifted:

Modern plans plus optimized models (Phoenix for general work, Nano Banana Pro for text-heavy work) let you create more final-quality images per credit because you need fewer retries to fix text, layout, and logic.

Automation and batch workflows reduce “human-driven” wasted iterations—you define a prompt once, push a sheet of variations, and filter outputs, instead of manually burning tokens on each experiment.

A more accurate framing for 2025:

If you prompt sloppily and chase micro-tweaks at max quality, you will burn tokens. If you pair Phoenix or Nano Banana with structured prompts, batch workflows, and light post-processing, Leonardo gives you production-ready assets at a cost that’s competitive with or better than Midjourney and DALL-E 3 for real marketing work.

My actual token usage over 4 months:

• Month 1: Burned 12,000 tokens learning the platform (lots of wasted iterations)
• Month 2-4: Averaged 7,500 tokens per month with better prompting and model selection
• Final output: 200-250 usable images per month on the Apprentice plan

The key: Learn which models work for which use cases, write better prompts, and accept that 80-90% perfect is good enough for most marketing visuals.

Common Mistakes People Make With Leonardo AI

Mistake 1: Using It for Every Image Need

Leonardo AI is a tool, not a replacement for all visual content. Stock photos, custom illustrations, and professional photography still have their place. Use Leonardo for concepts, backgrounds, and supplementary visuals—not hero images where brand identity is critical.

Mistake 2: Ignoring the Elements Feature

I generated images for a month before discovering Elements. Once I started using them, my usable output rate jumped from 60% to 85%. Elements apply consistent style characteristics (lighting, color grading, composition) without bloating your prompts. Test 3-4 Elements with the same base prompt before committing to a style.

Mistake 3: Not Using Flow State for Exploration

If you’re stuck rewriting prompts trying to find the right visual direction, you’re doing it wrong. Switch to Flow State, let it stream variations, click what feels right, and narrow down from there. It’s faster than prompt iteration and often surfaces ideas you wouldn’t have thought to describe.

Mistake 4: Not Budgeting for Iterations

Your first batch of 4 images will rarely be perfect. Budget 2-3x the tokens you think you’ll need, especially for abstract concepts or brand-specific work. I learned this the hard way when I burned through 3,000 tokens on lead magnet graphics I thought would take 1,000.

Mistake 5: Skipping the Negative Prompt Field

Negative prompts tell the AI what to avoid. I add “blurry, distorted, low quality, watermark, text, cluttered” to every generation. This simple step improved output quality noticeably and reduced unusable results by roughly 20%.

Mistake 6: Not Testing Models Before Committing

Each model has a different style and strength. “Leonardo Lightning” is fast and great for abstract concepts. “Lucid Origin” excels at cinematic, detailed scenes. “Google Nano Banana Pro” handles realistic, clean compositions and readable text. Test 2-3 models with the same prompt before generating in bulk.

Mistake 7: Picking the Wrong Tool for the Job

Leonardo excels at marketing visuals, concept art, and brand assets. It’s not the right choice for pixel-perfect product photography, images requiring exact Pantone color matching without any post-processing, or projects where you need zero human review.

Mistake 8: Using the Wrong Model for Text

If you need readable text in your images, use Nano Banana or Nano Banana Pro. Using older models and complaining about gibberish text is like using a hammer to cut wood—you’re using the wrong tool for the job.

The Real Comparison: Leonardo AI vs. Everyone Else

Leonardo AI vs. Midjourney

Quality: Tied at 9/10. Both produce professional-grade outputs.

Workflow: Leonardo wins decisively. Web app with integrated tools vs. Discord command-line interface.

Control: Leonardo wins decisively. Fine-tuning guidance scale (prompt adherence), steps (quality iterations), schedulers (generation algorithms), and seeds (result recreation) vs. prompt-only control.

Model variety: Leonardo wins. 50+ specialized models vs. one engine with style variations.

Exploration tools: Leonardo wins. Flow State mode for rapid ideation vs. manual prompt iteration.

Text generation: Leonardo wins. Nano Banana Pro produces readable text; Midjourney still struggles.

Cost: Tied at $10/month entry point.

API access: Leonardo has it. Midjourney doesn’t.

Verdict: Leonardo is better for anyone who values time, iteration speed, and control over their outputs.

Leonardo AI vs. DALL-E 3

Quality: Leonardo wins (9/10 vs. 7/10). DALL-E 3 produces decent images but lacks the polish and variety of Leonardo’s best models.

Workflow: Leonardo wins. Integrated tools vs. ChatGPT-only interface.

Control: Leonardo wins decisively. Extensive fine-tuning vs. minimal control.

Exploration tools: Leonardo wins. Flow State mode vs. one-at-a-time generation.

Text generation: Leonardo wins. Nano Banana Pro produces cleaner, more accurate text than DALL-E 3.

Cost: Leonardo wins (10 vs. 20 for ChatGPT Plus).

Speed: Leonardo wins (15-30 seconds vs. 45-90 seconds).

Verdict: Leonardo is better for professional work. DALL-E 3 is fine for casual use.

Leonardo AI vs. Local Stable Diffusion

Quality: Tied at 9/10 when Stable Diffusion is properly configured.

Workflow: Leonardo wins. Web app vs. tool juggling across A1111 (Automatic1111, a technical interface), ComfyUI (node-based programming interface), and file managers.

Control: Stable Diffusion wins on absolute control. Leonardo wins on practical control—enough power without the complexity.

Exploration tools: Leonardo wins. Flow State mode vs. manual batch scripting.

Cost: Stable Diffusion wins on marginal cost (free after GPU purchase). Leonardo wins on time cost (no setup, no maintenance).

Ease of use: Leonardo wins decisively. No technical knowledge required.

Verdict: Leonardo is better unless you’re a technical user who enjoys tinkering with models, LoRAs (style files), and node graphs (visual programming). For builders who want results, not hobbies, Leonardo wins.

Is Leonardo AI Worth It?

Yes, if:

• You need brand visuals regularly (site images, lead magnets, social graphics)
• You want faster iteration than stock photo hunting
• You’re comfortable with 80-90% success rate and minor post-editing
• You value workflow efficiency and integrated tools
• You want top-tier quality without technical complexity
• You’re building a business and time matters more than tinkering
• You need readable text in your images (use Nano Banana Pro)
• You want to explore visual directions quickly (use Flow State)

No, if:

• You need pixel-perfect brand consistency with zero post-processing
• Your visuals require exact Pantone color matching without any edits
• You already have a Stable Diffusion workflow that works and you enjoy managing it
• You’re generating fewer than 20 images per month (free tools are enough)
• You’re a technical user who wants maximum control and doesn’t mind complexity

My Setup: How I Actually Use Leonardo AI

Here’s my current workflow for Empire Forged brand assets:

1. Define the visual need first. I generate images after I know exactly what the asset is for—lead magnet cover, email header, site background, etc.
   
2. Choose the right mode:
   
   • Flow State when I’m exploring and don’t have a clear vision yet
   • Classic Mode when I know exactly what I want and need precision
   • Canvas when I need to refine or edit specific parts of an existing image
3. Pick the model based on use case:
   
   • For brand images: “Google Nano Banana Pro” (clean, realistic)
   • For text-heavy work (covers, thumbnails): “Nano Banana Pro” (readable text)
   • For abstract concepts: “Leonardo Lightning” with Elements
   • For cinematic backgrounds: “Lucid Origin”
4. Write a specific prompt. Example: “modern minimalist workspace with laptop, notebook, and coffee mug, natural window light, clean desk, soft focus background.”
   
5. Add negative prompt. “blurry, distorted, low quality, watermark, cluttered, oversaturated.”
   
6. Select an Element if applicable. For lead magnets, I use the “Concept Art” Element. For backgrounds, “Cinematic” or “HDR” (High Dynamic Range—enhanced lighting and detail).
   
7. Generate 4 images (or stream in Flow State). Pick the best one or regenerate if none work. Budget 2-3 iterations for abstract concepts, 1-2 for text-heavy work with Nano Banana Pro.
   
8. Upscale if needed. For hero images or lead magnet covers, I upscale to 2048px width (increases resolution for crisp, professional quality—costs 5 tokens).
   
9. Edit in Canva. Crop to final dimensions, add brand color overlays (#FF6B35 orange) if needed, adjust contrast, add additional text elements.
   

Time per final image: 5-8 minutes including edits and iterations (10-15 minutes if starting with Flow State exploration).Cost per final image: Roughly $0.10-0.20 depending on regenerations and upscaling.

Conclusion: Is Leonardo AI Worth Your Time and Money?

After months of daily use building Empire Forged’s visual identity, here’s what I actually think.

Leonardo AI is the best all-around image generation platform for people building real businesses in 2025 and beyond. Not because it’s perfect—it’s not. But because it delivers professional-quality outputs without forcing you to become an AI engineer or burn hours managing technical complexity.

What makes it worth the money:

The image quality matches Midjourney. The workflow beats everything else. You get 50+ models that cover every aesthetic from photorealistic to abstract, readable text generation through Nano Banana Pro, and Flow State mode that cuts exploration time in half when you’re not sure exactly what you want.

The integrated workflow—generate, upscale, edit, export in one browser tab—saves 30-40% of my production time compared to the Discord-Photoshop-file manager dance I was doing with Midjourney. The Canvas editor lets me fix specific problems without regenerating entire images. Elements apply consistent style characteristics without me writing novel-length prompts.

And the platform improves every week. Features that were clunky in January are polished by March. That development pace matters when you’re building a business—your tools should evolve alongside your needs, not stagnate.

What it’s not good at:

Exact color matching. You can get close to brand colors with structured prompts, but if you need pixel-perfect Pantone consistency, you’re finishing in Canva or Figma. That’s not a dealbreaker—it’s just reality.

Native batch editing. You can batch-generate and batch-upscale, but applying the same crop or color adjustment to 50 images means doing it manually or wiring Leonardo into automation tools. For solo creators, that’s manageable. For agencies processing hundreds of images, it’s friction.

Token costs add up if you’re sloppy. Flow State is powerful but burns credits fast if you scroll endlessly. Abstract concepts need multiple iterations. If you don’t learn which models work for which use cases and write better prompts, you’ll chew through your plan.

Who should use Leonardo AI:

You’re building a business and need brand visuals regularly—site images, lead magnets, email headers, social graphics, thumbnails. You value time over tinkering. You want professional quality without learning ComfyUI or managing local Stable Diffusion setups. You need readable text in your images and fast visual exploration when you’re not sure exactly what you want.

If that’s you, Leonardo AI is worth every dollar of the $10/month Apprentice plan.

Who should skip it:

You need pixel-perfect brand consistency with zero post-processing. Your visuals require exact Pantone matching without any edits. You already have an optimized Stable Diffusion workflow and enjoy the technical side. You’re generating fewer than 20 images per month—free tools are enough at that volume.

My actual recommendation:

Start with the free plan. Generate 20-30 images across different use cases. Test Flow State for exploration—write a vague prompt, click what feels right, see if it surfaces ideas faster than rewriting prompts. Test Nano Banana Pro for text-heavy work like lead magnet covers or thumbnails. Test Elements to see if style presets improve your consistency.

Track your success rate. If 70-80%+ of outputs are usable with minor edits, upgrade to Apprentice. If you’re still hunting for the “perfect” image after 10 regenerations and burning tokens on endless iterations, Leonardo AI isn’t the right tool for that specific project—but it might work for others.

The bottom line:

Leonardo AI delivers top-tier image quality matching or exceeding Midjourney, with significantly better workflow tools, fine control, model variety, readable text generation, and rapid exploration through Flow State. It captures 70-90% of what makes local Stable Diffusion powerful while eliminating 90% of the setup and maintenance pain.

For practical creator and marketing workflows in 2025, it’s the strongest all-around platform available. If you’re building a business and need reliable, high-quality visuals without becoming a full-time AI engineer, Leonardo AI is the best tool on the market right now.

That’s not hype. That’s what I learned after generating hundreds of images, building an entire brand’s visual identity, and comparing it to every alternative I’ve tested. Your mileage may vary, but mine has been worth every token.

Next Steps

If you’re testing Leonardo AI, here’s what to do:

1. Sign up for the free plan at leonardo.ai
2. Test Flow State with a vague concept prompt and click your way toward what you want
3. Test the Elements feature with 3-4 different Elements on the same prompt
4. Generate 10 test images using models that match your visual needs:
   • Nano Banana Pro for text-heavy work
   • Lucid Origin for cinematic backgrounds
   • Leonardo Lightning for abstract concepts
5. Track your success rate—how many are usable with minor edits?
6. Compare to your current method—is this faster or cheaper than stock photos, other AI tools, or hiring designers?

If it works for your workflow, upgrade to Apprentice. If not, you’ve spent zero dollars finding out.

Frequently Asked Questions

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