Fashn Vton vs QOVES

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-10-18
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At a glance

DimensionFashn VtonQOVES
PricingFreemium (free tier + paid plans)Paid (no free tier)
Primary UseVirtual try-on for fashion imageryFacial analysis for non-surgical improvement
Core TechnologyMaskless pixel-space diffusion model (MMDiT)Statistical facial beauty markers + research-backed protocols
Data PrivacyOpen-source Apache 2.0, API usage may send imagesPrivate, paid analysis
Target AudienceBusinesses, devs, fashion brands, creatorsIndividuals seeking science-based beauty advice
Latest Feature (June 2026)Fast mode for Try-On, more realistic Model Creation, coding agent skillSmoother checkout, refreshed homepage, faster page loads

Choose QOVES if you want a data-driven, non-surgical facial transformation plan based on 160+ beauty markers and scientific research. Choose Fashn Vton if you need photorealistic virtual try-on for fashion e-commerce or content creation, especially if you require fast, open-source technology. They serve completely different needs: personal beauty analysis vs. commercial fashion imagery.

Fashn Vton
Fashn Vton

FASHN VTON v1.5 is an open-source maskless virtual try-on model that swaps garments directly in pixel space — no segmentation masks, Apache 2.0 code and

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QOVES
QOVES

AI facial analysis scoring 160+ beauty markers into a personalized, non-surgical glow-up protocol backed by named research.

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Pricing
Freemium
Paid
Plans
$0
$19/mo
$49/mo
$99/mo
$149 one-time
Popularity
31 views
6.5k views
Skill Level
Advanced
Beginner-friendly
API Available
Platforms
WebAPI
Web
Categories
🎨 Image Generation
👁️ Computer Vision🌤️ Everyday Life
Features
Maskless virtual try-on generating results without segmentation masks
Pixel-space diffusion operating directly on RGB pixels with no VAE encoding
972M parameter MMDiT with 8 double-stream and 16 single-stream blocks
4 patch-mixer blocks allowing up to 75% of tokens to be dropped during training
Pose keypoint conditioning supplied as single-channel grayscale images
Category embeddings for tops, bottoms, and one-pieces added to timestep conditioning
Roughly 5 second inference on H100 GPUs
Open-source release under Apache 2.0 with code and model weights
Preserves tattoos, body identity, and cultural garments like hijabs during swaps
Handles volume changes from slim outfits to puffer jackets and floor-length gowns
Selective layered-outfit replacement that keeps an outer jacket intact
Unified credit system shared between web, iOS, and Android apps
AI video generation at 720p on Basic and 1080p on Pro and Agency
Videos with generated audio via the FASHN Agent, at double the credit cost of silent video
Transparent backgrounds including semi-transparent tulle, lace, and mesh, up to 4K upscale
Scores 160+ beauty markers across your face
Facial harmony assessment showing how features interact
Feature-level scores including eyebrow fullness and lip smoothness on a 0–100 scale
Eye melanin concentration and eye color readout
Facial thirds ratio compared against both ideal and average
Visual projection of your best-looking self
Personalized non-surgical glow-up protocol
Recommendations weighted by ethnic background and personal preferences
Lifestyle inputs: diet, climate, stress, sleep and habits
Natural aging pattern adjustment for skin, bone and fat distribution
Cultural and regional beauty standard adaptation
Research-backed protocol citing named academic studies
Skin scored region by region: wrinkles, pores, smoothness, oiliness, redness, sun damage, pigmentation
Analysis limitations page stating which parts of your analysis your photos could not support
Consent controls for how photos and results are used, changeable at any time

Who should pick which

  • Solo founder
    Pick: Fashn Vton

    Because Fashn Vton is open-source and freemium, so a low-budget startup can integrate virtual try-on without heavy upfront cost.

  • Self-improvement enthusiast
    Pick: QOVES

    Because QOVES provides a research-backed, non-surgical glow-up plan with ethnic and lifestyle adjustments.

  • E-commerce brand manager
    Pick: Fashn Vton

    Because Fashn Vton generates photorealistic on-model imagery quickly, ideal for product listings and marketing.

  • Plastic surgery researcher
    Pick: QOVES

    Because QOVES offers detailed facial biometrics and scientific citations that can inform studies.

  • AI developer building a fashion app
    Pick: Fashn Vton

    Because Fashn Vton is open-source with API access and a coding skill for assistants, making integration straightforward.

Frequently Asked Questions

Fashn Vton vs QOVES: which should you choose?

Choose QOVES if you want a data-driven, non-surgical facial transformation plan based on 160+ beauty markers and scientific research. Choose Fashn Vton if you need photorealistic virtual try-on for fashion e-commerce or content creation, especially if you require fast, open-source technology. They serve completely different needs: personal beauty analysis vs. commercial fashion imagery.

Are these two tools direct competitors?

No. QOVES is for personal facial beauty analysis; Fashn Vton is for virtual try-on of clothing. They serve completely different markets.

Can I use QOVES for free?

No. QOVES is a paid service with no free tier or trial mentioned in the data.

Is Fashn Vton free?

The model is open-source under Apache 2.0 for research and commercial use. The FASHN platform offers a free tier, but advanced features require a paid subscription.

Which one is better for surgery planning?

Neither. QOVES explicitly avoids surgical recommendations. Fashn Vton is for fashion try-on only.

Can I integrate Fashn Vton into my app?

Yes, via the FASHN API and the open-source model. The latest news mentions a coding skill for agent assistants.

Does QOVES analyze aging patterns?

Yes, it adjusts for natural aging patterns in its glow-up protocol.

Does Fashn Vton work for any garment type?

It supports tops, bottoms, and one-pieces via category embeddings. It is not designed for accessories.

What is the latest improvement in QOVES?

As of June 2026, smoother checkout, refreshed homepage, and faster page loads.

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Last reviewed: July 3, 2026