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pdmd

PDMD: Projected Distribution Matching Distillation for Video Diffusion Models

This is 1 of 167 launches in ai video creation and editing tools — see how it stacks up on momentum and crowding →

772 other launches read as similar to this one →

Details

External ID
1391208881
Source
GITHUB
Company
—
Product
pdmd
Website domain
github.io
Launched
Sept. 27, 2026
Cohort
—
Upvotes
18
Upvotes percentile
0.5631477464449265
Tags
audio-generation, diffusers, diffusion-models, distillation, distribution-matching-distillation, few-step-generation, minimax-h3, pytorch, text-to-video, video-generation
Fetched at
Oct. 1, 2026, 5:02 p.m.
Updated at
Oct. 1, 2026, 5:02 p.m.

Enrichment

Theme
ai video creation and editing tools
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
video diffusion distillation algorithm for ai researchers
Manually corrected
False

Could you build this?

No PDMD is cutting-edge AI research on step distillation for video diffusion models produced by ByteDance and UCSD researchers, requiring deep mathematical generative AI expertise and massive GPU clusters.

What it would actually take: The project implements projected distribution matching distillation to compress video diffusion models (like Wan2.1 and MiniMax) down to 2-4 network evaluations without quality degradation. Developing this requires specialized PhD-level knowledge in diffusion theory, optimal transport, and score distillation, alongside a multi-node GPU cluster (e.g., H100s) with distributed training frameworks (DeepSpeed, Megatron-LM) to train and benchmark multi-billion parameter video models.

Competitors

Other products that read as similar to this one — 772 launches clear the similarity bar, closest 8 shown.

Attention rank: #328 of 773 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 331 days after the earliest competitor.

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