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Rohan Paul· @rohanpaul_ai · X· · Original publication time AI score54

Hi3D releases code and weights for its image-to-3D model v1.0Machine translation

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Hi3D v1.0’s code and weights are available for commercial use within the stated limits. It refines a 3D shape from an image and a coarse mesh. The model produces no colors or textures and requires an NVIDIA GPU; professionals chose it in 83.5% of 562 side-by-side ratings.

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@rohanpaul_ai

🧵3/n Hi3D v1.0 is the open base, while Hi3D’s own closed model is already at v3.0, refining at 2048 cubes per side.

The new Hi3D Agent puts generating, editing and processing 3D models in one flow, and a Model Context Protocol (MCP) server lets other AI agents call Hi3D directly.

Hi3D says it has cut users’ credit costs by over 50%.

People who work on 3D algorithms prefer its geometry. Thirteen people with professional 3D-algorithm experience compared Hi3D v1.0 side by side against eight other image-to-3D models across 562 judgments. They picked Hi3D v1.0 83.5% of the time.

ReplyRohan Paul@rohanpaul_ai
🧵2/n Most image-to-3D tests only grade the view shown in the input image, so the team also checked the back and bottom of every result. On a winged armored figure for example, TRELLIS.2 collapsed into a flat panel, while Hi3D v1.0 kept the wings and limbs as connected parts. The hidden sides are still the model’s best guess, since 1 photo can’t show them.
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Related contextRohan Paul@rohanpaul_ai
This is so good for open 3D generation. last year’s cutting-edge technology, open-sourced this year @Hi3D_AI has open-sourced Hi3D v1.0 (formerly Sparc3D), an image-to-3D model that holds together from every angle and already ran in Hi3D’s live product before release. > Anyone can run it privately on their own servers, connect it to their internal systems, and build tools and apps for their industry on top of it. > Code and weights are on GitHub and Hugging Face, free to use including commercially, Most image-to-3D models get judged by how the front looks, so the back, the bottom and thin parts like wings, horns and handles often come out blobby, broken or missing. Hi3D v1.0 takes the image plus a rough draft shape (a “coarse mesh” from another model) and sharpens it in 3 passes, at 512, 1024 and 1536 resolution. Resolution here means the space around the object is cut into tiny cubes called voxels, basically 3D pixels, and 1536 means 1536 cubes along each side. That full grid would hold over 3.6B cubes, so the model works sparse, only touching cubes near the surface and skipping empty air and the solid inside. In each pass, a “self-pruning” decoder rebuilds the surface at 8x finer scale and drops cubes that turn out empty. Training data grew from 500K to about 2M curated 3D assets. Against 8 other image-to-3D models, including TRELLIS.2 and Hunyuan3D-2.1, it scored best on multi-view fidelity (0.75), which checks the shape stays consistent and unbroken from 6 camera angles, and detail richness (0.841), which grades fine surface relief and small parts. It also kept a 90% slicing success rate, the share of models a 3D printer’s software could cut into print layers, versus 7% for Pixal3D, the only other model at 1536, and 17% for TRELLIS.2. In 562 side-by-side ratings by 13 people with professional 3D experience, Hi3D v1.0 was picked 83.5% of the time. It outputs shape only (no colors or textures), needs an NVIDIA GPU, and the code and weights are free for commercial use up to 200K monthly users or $1M monthly revenue. And Hi3D 1.0 Is Now Open Source https://t.co/AaRHAfa3Bu
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Source: Rohan Paul · x.com

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