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FASHN VTON v1.5

open-source virtual try-on model

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We’re open-sourcing FASHN VTON v1.5, a production-grade virtual try-on model.Given an image of a person and an image of a garment, the model generates a photorealistic try-on result.Model specs: - It operates directly in pixel space (no VAE) - Supports maskless inference by default, and was trained from scratch. - ~972M parameters, runs on consumer GPUs - Can run in ~5 seconds on H100We built this as a focused alternative to large generalist models, with the goal of making a production-grade, specialized virtual try-on model.We’re releasing the weights, inference code, and architecture details under an Apache-2.0 license.Would love to hear your thoughts!

HN · launched Jan 28, 2026 · 6 upvotes (top 75%) · 0 views

Niche: virtual try-on software · 94 launches, 9 in the last 7 days ▼ -31% · Explore this niche →

Category and tags

  • Retail & commerce
  • Model & infra
  • Developer
  • AI-native
  • Commercial product

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Could you build this?

No FASHN VTON v1.5 is a state-of-the-art generative computer vision model operating in pixel space for photorealistic virtual try-on, requiring massive datasets and cluster training that AI assistance cannot synthesize.

What it would actually take: Developing this requires training a deep diffusion model on hundreds of thousands of paired high-resolution garment and human model images across diverse poses. Architecture involves specialized cross-attention conditioning, deformation warping networks, and extensive GPU cluster compute (dozens of H100s/A100s for weeks). Requires world-class generative computer vision researchers and substantial ML infrastructure funding.

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Competitors

Other products that read as similar to this one : 146 launches clear the similarity bar, closest 8 shown.

Attention rank: #132 of 147 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 83 days after the earliest competitor.

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