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TripoSG

1.5B rectified-flow model for high-fidelity image-to-3D shape synthesis.

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About

TripoSG is VAST-AI-Research's open model for high-fidelity 3D shape synthesis from images, described in the February 2025 arXiv paper and released with weights and inference code in March 2025. It pairs a 1.5B-parameter rectified-flow transformer with an SDF-based VAE trained on 2 million curated image-SDF pairs, using 2048 latent tokens, with hybrid SDF, surface-normal, and eikonal supervision.

The release includes the rectified-flow model, the VAE, inference code, and an interactive demo, with weights on Hugging Face and a minimum requirement of about 8GB VRAM. It targets sharp geometric detail and semantic consistency across photorealistic images, cartoons, and sketches. Note on dating: the March 2025 release date is era-level from the repo's update notes; verify the license on the model card before commercial use.

Specs

Context window

Pricing

Free quota

API access

Weights

Open weights

Released

March 1, 2025

Benchmarks

Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.

Use cases

image-to-3d3d-modelingopen-weightsgame-assetsmesh-generation

Trust score — 7/10

/10 trustMetrics-checked

Scored 7/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 85; Trending score 68/100 from researcher assessment.

Sources