Oginify vs The New Black
Side-by-side comparison of features, pricing, and ratings
Oginify or The New Black: which should you choose?
| Dimension | Oginify | The New Black |
|---|---|---|
| Goal | Auto-generate branded OG images from any URL | AI fashion design for apparel/accessories |
| Pricing | Free (6/day signed-in, 3 anonymous/IP) + pay-per-card bundles | Free tier; Pro & Business plans |
| Output | 1200×630 PNG with baked-in meta tags | High-res designs + tech pack exports |
| Key Feature | 4 variants per run (1 on-brand + 3 wildcards) | Text-to-design, virtual try-on, custom AI models |
| Best For | Solo devs, marketers, agencies needing quick link previews | Fashion brands, designers, startups |
| Limitation | No API yet; low daily free limit | Strictly fashion; no general graphic design |

Generate Open Graph images from any URL — four 1200×630 AI cards in about 30 seconds, no prompt or template.
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AI fashion design studio: turn product photos, sketches or prompts into on-model shots, video and factory-ready tech packs
Visit WebsiteWho should pick Oginify, and who should pick The New Black?
- Solo founder launching a product pagePick: Oginify
Needs instant branded link previews for social sharing; Oginify's free tier (6/day) and no-signup option make it ideal for quick iterations.
- Fashion startup designing first collectionPick: The New Black
Requires AI-generated apparel concepts with tech pack exports; The New Black is purpose-built for fashion, from ideation to prototype.
- Content marketer managing multiple blogsPick: Oginify
Needs consistent OG images for each article without manual design; Oginify's URL-based generation with brand detection is efficient.
- Independent fashion designer exploring stylesPick: The New Black
Wants rapid text-to-design generation and virtual try-on to visualize ideas; The New Black's Fashion Diffusion AI suits this need.
- Agency producing social previews for clientsPick: Oginify
Can use pay-per-card bundles for occasional high-volume runs; no API needed. Quick turnaround on branded cards.
Frequently Asked Questions
Do I need to sign up for Oginify?
No, you can generate 3 images per day anonymously per IP. Signing in gives 6 daily generations.
What file formats does Oginify output?
1200×630 PNG images with baked-in og:image and twitter:card tags.
Can I use Oginify for batch generation?
Not yet; no API is available. You must generate one URL at a time via the web app.
What is The New Black best used for?
AI fashion design for apparel and accessories, from text prompts to tech packs and virtual try-ons.
Does The New Black require design experience?
No, it's designed for quick ideation; text prompts suffice, though design styles can be customized.
Are both tools free to start?
Yes, Oginify offers free daily generations; The New Black has a free tier with limited features.
Can I self-host Oginify's engine?
Yes, the open-source engine (social-cards-skills) is MIT-licensed, but the latest v0.3.0 uses google/gemini-3.1-flash-image-preview model; check the repo for details.
Does The New Black integrate with design software?
No direct integrations listed; tech packs can be exported separately.
What else are Oginify and The New Black compared with?
These are not competitors — the shortlist decision never happens, so don't shop them against each other. If you make apparel, jewelry, or accessories and want one workspace from design to a factory br
These aren't alternatives — they're different jobs. PerfectPixel is for a game developer who wants to describe a character and get a walk cycle in eight directions as an engine-ready sprite sheet, run
If you run an apparel, jewelry, or accessory brand and need on-model imagery, video, tech packs, and Shopify-ready visuals, The New Black is the clear choice. If you just need free, private background
These aren't competitors — pick based on your job title, not features. If you run a clothing, jewelry or accessory label and need on-model imagery, try-on, lookbooks, video and a factory brief without
Where can you read more about Oginify and The New Black?
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Analysis generated by our model pipeline from live data: