What Makes Firefly Different

Adobe Firefly launched in 2023 with a clear differentiator: while Midjourney and DALL-E were trained on internet-scale data (with ongoing copyright debates), Firefly was trained exclusively on Adobe Stock images, openly licensed content, and public domain material. This matters for commercial use — Adobe provides enterprise indemnification, meaning they’ll stand behind the legal safety of Firefly-generated images.

This training data decision is Firefly’s defining characteristic. Images generated with Firefly are commercially safer than any competitor — a crucial consideration for agencies, enterprises, and anyone creating images for commercial products. The tradeoff: the training dataset is smaller and more curated, which means Firefly’s creative range is narrower than Midjourney’s or DALL-E’s.

Firefly is not a standalone tool competing for the “best AI image” title. It’s the AI layer inside Adobe’s creative ecosystem — designed to be used within Photoshop, Illustrator, Express, and the Firefly web app by people who already live in Adobe’s tools.

Firefly Scorecard 📊

4 Real-World Tests 🔬

Test 1: Generative Fill — Firefly’s Killer Feature

Task: Take a product photo on a plain white background. Select the background area and replace it with “a modern office desk setting, warm lighting, shallow depth of field.”

Firefly (Generative Fill in Photoshop): Selected the background → typed the prompt → Firefly generated the new background in ~5 seconds, offering 3 variations. The result: seamless integration. The product’s lighting matched the new background’s light source direction. The depth of field on the office setting was consistent with the product’s focus plane. Shadows fell correctly. This feature alone justifies Firefly’s existence — it’s a genuinely magical editing capability that no competitor offers within a professional editing tool.

Midjourney/DALL-E: No equivalent. You can generate a new background separately and composite manually — but the lighting consistency, perspective matching, and edge blending that Generative Fill handles automatically would require significant manual Photoshop work.

Test 2: Commercial Product Photography

Prompt: “A luxury wristwatch on a marble surface, soft studio lighting, product photography quality, clean sharp details on the watch face, shallow depth of field.”

Firefly: Generated a highly realistic product shot. The watch details were sharp, the marble texture was natural (not repeating), the metal reflections were physically accurate, and the lighting was studio-quality. The image could plausibly appear on an e-commerce product page. The commercial indemnification means it legally can.

Midjourney: More dramatic lighting, more “luxury magazine” aesthetic. Slightly more beautiful — but trained on copyrighted imagery, with less certain commercial safety for product use.

Test 3: Style Reference Consistency

Task: Generate 10 images of different products (shoes, bags, watches, etc.) in a consistent catalog style — same lighting, same background treatment, same photographic approach.

Firefly: Using the Style Reference feature (upload a reference image, Firefly matches the style), the 10 images maintained consistent lighting direction, color temperature, background style, and overall photographic approach. The output looked like a cohesive product catalog. Brand consistency at scale is one of Firefly’s strongest production features.

DALL-E 3: Generated beautiful individual product shots but style consistency across 10 images was lower — some had warmer tones, different background treatments, varied lighting setups.

Test 4: Photoshop Integration for Professional Workflow

Task: Edit a portrait photo — smooth skin, enhance eyes, adjust lighting on the face, extend the background to make room for text overlay.

Firefly (in Photoshop): Used Generative Fill to extend the background canvas. Used Neural Filters for skin smoothing and eye enhancement. Used the Camera Raw filter for lighting adjustments. All AI features were accessible within Photoshop’s existing interface — no switching tools, no exporting and re-importing. The workflow was “Photoshop with AI superpowers” rather than “AI tool that you export from.”

Midjourney/DALL-E: Can generate elements to composite in — but require external generation, download, import into Photoshop, compositing. More tool-switching, less integrated.

The Commercial Safety Advantage

The single most important thing to understand about Firefly: it’s the only major AI image generator that provides enterprise indemnification for generated images. Here’s what that means in practice:

• Training data: Firefly was trained on Adobe Stock (~300M images Adobe has rights to), openly licensed content, and public domain material
• Indemnification: For enterprise customers, Adobe will defend against copyright claims on Firefly-generated images
• Content Credentials: Every Firefly image includes C2PA metadata labeling it as AI-generated and tracking its provenance

For agencies creating images for Nike, for enterprises building product catalogs, for publishers creating book covers — the commercial safety question isn’t theoretical. Midjourney and DALL-E are trained on copyrighted internet imagery with ongoing legal uncertainty. Firefly’s answer to “can I legally use this image commercially?” is a clear yes.

Pricing

At $5/month, Firefly Standard is the cheapest entry point for commercially safe AI images — cheaper than Midjourney Basic ($10/month). At $20/month (Photography plan), you get Photoshop + Lightroom + Firefly — the best value for photographers and designers. At $60/month (All Apps), you get every Adobe tool plus Firefly — priced for professional designers who already pay for Creative Cloud.

Pros & Cons

Final Recommendation

Last updated: July 2, 2026. Adobe Firefly features and pricing verified against official sources.

What Makes Leonardo Different

Leonardo AI was founded in 2022 with a specific thesis: general-purpose AI image generators (Midjourney, DALL-E) serve broad audiences well, but creative professionals — game developers, concept artists, illustrators — need tools built for production workflows, not one-off image generation.

This thesis shaped every feature decision:

• Fine-tuned models instead of one general model. Leonardo offers platform-specific models (Leonardo Diffusion XL for photorealism, Leonardo Anime for animation-style art, Leonardo RPG for character designs, Leonardo Isometric for game tiles). Each model is optimized for a specific creative domain.
• AI Canvas instead of text-to-image-only. The Canvas is a real-time editing environment where you can select areas to regenerate (inpainting), extend images beyond their borders (outpainting), sketch rough layouts and have AI refine them, and compose scenes from multiple generated elements.
• Production workflow instead of one-shot generation. You can generate variations, iterate on specific regions, upscale final outputs, remove backgrounds, and export in game-ready formats — all within one tool.

Leonardo AI Scorecard 📊

4 Real-World Production Tests 🔬

Test 1: RPG Character Design

Task: “Generate a dark elf rogue character — hooded cloak, dual-wielding daggers, standing in a moonlit alley. Fantasy art style, character concept sheet quality.”

Leonardo (RPG model): Generated a striking character design with the dark elf’s distinctive features clearly rendered, appropriate costume detail, and atmospheric moonlight. The RPG model understood character design conventions — full-body framing, clear silhouette, costume details. Generated 4 variations, 2 of which were directly usable as concept art references.

Midjourney: Generated a more aesthetically beautiful image — better lighting, more dramatic composition. But the character felt more like an illustration and less like a concept sheet. Fewer generation controls. Beautiful output; less production-focused.

Test 2: Isometric Game Tiles

Task: “Generate isometric game tiles for a fantasy village — a blacksmith building, a tavern, a marketplace stall, and a small bridge. Consistent art style, suitable for a 2.5D game.”

Leonardo (Isometric model): Generated all four building tiles with consistent isometric perspective, lighting direction, and art style. The tiles could be placed adjacent to each other in a game engine with minimal adjustment. The special-purpose model’s understanding of isometric projection was accurate — no perspective drift.

DALL-E 3: Generated visually appealing individual buildings but perspective was inconsistent across the four tiles (one was near-isometric, one more top-down, two in 3/4 perspective). Required significant manual adjustment to work as game tiles.

Test 3: AI Canvas Iteration

Task: Take a generated landscape image. Replace the sky with a sunset, add a castle in the distance on a hill, and extend the canvas to widescreen format for a game splash screen.

Leonardo (AI Canvas): Selected the sky area, prompted “golden hour sunset with orange and purple clouds” — sky replaced seamlessly. Selected a distant hill area, prompted “medieval castle silhouette with towers” — castle appeared, lighting consistent with the new sunset. Used outpainting to extend the canvas on both sides, filling in landscape that matched the original style. Total time: ~8 minutes. Final output: widescreen splash screen, no external editing tool needed.

Firefly (Generative Fill in Photoshop): Could handle the sky and castle inpainting well (arguably better on the sky, which had more realistic light). Outpainting to widescreen required switching tools. End result similar quality, took ~12 minutes and required Photoshop.

Test 4: Free Tier Viability

Task: A week of casual game asset prototyping using only the free tier (250 tokens/day).

Leonardo free tier: 250 daily tokens translates to roughly 50-125 images depending on resolution (fast mode ~2 tokens/image, quality mode ~5 tokens). For a solo indie dev prototyping character concepts and environment art: this is sufficient for meaningful work. You won’t generate every asset you need, but you’ll get through concepting and early prototyping without paying.

Compare to Midjourney (no free tier after trial, $10/month minimum) and DALL-E (limited free generations in ChatGPT). Leonardo’s free tier is the most generous in the specialized AI image category.

Key Features Deep Dive

Fine-Tuned Model Library

Leonardo’s core differentiator is its collection of fine-tuned models, each optimized for specific creative domains:

The model selection is not a gimmick — switching between them produces meaningfully different outputs for the same prompt. For teams that need consistent art direction across many assets, the ability to lock into a specific model is more valuable than a single model that does everything adequately.

AI Canvas

The AI Canvas is Leonardo’s answer to the “generate → download → edit in another tool → re-upload” workflow that plagues most AI image tools. Key capabilities:

• Inpainting — select an area, describe the change, AI regenerates just that area
• Outpainting — extend the canvas in any direction, AI fills the new area to match
• Sketch-to-Image — rough layout drawing → AI refines into polished output
• Real-time generation — see results update as you type prompt changes

How Leonardo Compares

See Best AI Image Tools 2026 for the full ranking, and Leonardo vs Midjourney for the head-to-head.

Pricing

Token usage: fast generation ~2 tokens/image, quality generation ~5 tokens, upscaling ~5-10 tokens, AI Canvas edits ~2-5 tokens per operation. At $12/month (Apprentice), a solo developer can generate ~1,700-4,200 images per month — more than enough for active game prototyping.

Pros & Cons

Final Recommendation

Last updated: June 28, 2026. Leonardo AI features and pricing verified against official sources.