Pixal3d.ai
Summary
Most image-to-3D tools return a mesh that roughly resembles your input — fine for shape blocking, useless when surface detail and texture fidelity are what justify skipping manual modeling. Pixal3d.ai is built around pixel-aligned back-projection, a technique from TencentARC research that anchors generated geometry to the actual pixel content of your source image rather than inferring geometry from learned priors alone.
The tool accepts a single image and returns a GLB file — no multi-view capture, no turntable shoot. It runs two parallel generation lanes: the Pixal3D back-projection path and a Trellis 2 alternative, so you can compare both outputs before committing cleanup time to either. Quality presets control texture resolution (up to 2048) and vertex budget (up to 200,000 targets), which means the output ceiling is high enough for final review, not just shape prototyping. Every generation consumes credits; there is no free tier visible in the interface — you authenticate, spend credits, and download. The research weights are available on GitHub under TencentARC, so teams with the infrastructure to run inference locally are not locked to the hosted service.
Bottom line: Reach for Pixal3d.ai when pixel-faithful surface reconstruction from a clean product photo or character concept is the deliverable — abandon it when your source images have heavy occlusion, complex backgrounds, or you need batch automation, because the single-image one-shot flow and credit-per-generation model make volume pipelines expensive and slow.
Pricing Plans
Usage-BasedPixal3D Image-to-GLB
Per-generation credit cost for Pixal3D model
- 180-390 credits per generation (varies by quality preset)
- GLB export
- PBR textures
- Up to 2048 texture resolution
- Up to 200,000 target vertices
Trellis 2 Alternative Path
Per-generation credit cost for Trellis 2 comparison/fallback
- 160-310 credits per generation
- Alternate image-to-3D model for comparison
- GLB export
Hunyuan Motion Text-to-FBX
Per-generation credit cost for motion synthesis
- 60 credits per generation
- FBX and motion JSON export
- Text prompt-driven character animation
View full pricing on pixal3d.ai →
Pricing may have changed since last verified. Check the official site for current plans.
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Pros
Sign in to edit- Pixel-aligned back-projection keeps surface detail tied to the actual source image pixels, so texture markings and material boundaries land where you drew them rather than where a diffusion prior guessed they should be — which means less manual UV correction after export.
- Dual-lane comparison between the Pixal3D path and Trellis 2 runs before you commit cleanup time, so you pick the better mesh before spending hours in your DCC tool.
- Three quality presets with explicit vertex and texture targets — up to 200,000 vertices and 2048 textures on the Detail setting — so you can run a cheap shape check first and reserve credit spend for final-review passes.
- TencentARC research weights and inference code are available on GitHub, so studios with GPU infrastructure can bypass the hosted credit model entirely and run generation inside their own pipeline.
- Hunyuan Motion integration generates FBX character animation from text in the same interface, so character teams avoid context-switching between services when they need a posed or animated reference alongside the static mesh.
Cons
Sign in to edit- The input checklist is strict — full subject in frame, clear silhouette, low occlusion, simple background, high resolution, neutral lighting. Any photograph that violates more than one of these conditions produces degraded geometry, which means product shots with props, styled lighting, or partial occlusion go through the same manual rebuild the tool was supposed to shortcut.
- Every generation consumes credits with no visible free tier; teams running iterative prompt-and-inspect workflows across dozens of assets accumulate costs that make per-asset pricing competitive only when generation quality is high enough to reduce cleanup time — at scale, teams with consistent high-volume needs switch to self-hosted inference or a batch-capable competitor with flat-rate pricing.
- No API is exposed on the hosted service, so any attempt to wire generation into a build pipeline, content management system, or automated asset processor requires setting up the GitHub inference stack and maintaining GPU infrastructure — at which point the hosted service adds no value and teams are running TencentARC's weights directly.
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About
- Platforms
- Web (browser)
- API Available
- No
- Self-Hosted
- Yes
- Last Updated
- 2026-05-16T00:41:50.101Z
Best For
Who it's for
- Game developers and 3D artists seeking high-fidelity single-image 3D generation
- E-commerce and product visualization workflows
- Concept artists and designers prototyping 3D assets
- Studios requiring pixel-faithful 3D reconstruction from 2D references
- Teams prioritizing detail and topological accuracy over speed
What it does well
- Game asset generation from concept art or product photos
- E-commerce product 3D model creation from photographs
- Character and creature reference model generation
- Quick 3D prototyping and asset ideation before manual cleanup
- VR/AR asset production with high visual fidelity
Integrations
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Frequently Asked Questions
- Is Pixal3d.ai free?
- Pixal3d.ai is a paid tool. No permanent free tier is offered.
- Is Pixal3d.ai open source?
- No — Pixal3d.ai is a closed-source tool. Source code is not publicly available.
- Can I self-host Pixal3d.ai?
- Yes. Pixal3d.ai supports self-hosting on your own infrastructure.
- When was Pixal3d.ai released?
- Pixal3d.ai was first released in 2026.
- What platforms does Pixal3d.ai support?
- Pixal3d.ai is available on: Web (browser).
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Pixal3d.ai converts a single source image into a downloadable GLB 3D model using pixel-aligned back-projection developed by TencentARC. The workflow is one-shot: upload an image or paste a URL, select a quality preset (Fast Preview, Balanced, or Detail), configure seed and remesh options, and the service returns a textured GLB. A second generation lane running Trellis 2 runs in parallel, letting you compare outputs from two different reconstruction approaches before deciding which to take into cleanup. The platform also exposes a Hunyuan Motion path that generates FBX character animation from text, keeping motion production in the same credit ecosystem.
The differentiating claim is pixel alignment — the vendor states that geometry and texture are anchored to the input pixel content via back-projection rather than purely hallucinated from diffusion priors. In practice this means surface markings, panel lines, and material boundaries on well-photographed inputs are more likely to appear where you expect them, which reduces the number of passes needed in downstream tools. The Detail preset targets 200,000 vertices and 2048-resolution textures, which the docs describe as sufficient for final review rather than just ideation.
The tool fits cleanly into a pre-cleanup ideation pass for game asset artists, e-commerce product teams shooting clean product photography, and concept artists who need a 3D reference from a 2D illustration. It starts breaking when source images violate the documented input checklist: full subject in frame, clear silhouette, low occlusion, simple background, high resolution, and neutral lighting. Complex scenes or partially obscured subjects produce degraded geometry — the page explicitly lists these as conditions that degrade output. There is no API, so automation or pipeline integration requires the GitHub inference code and self-hosted weights, adding infrastructure overhead that the hosted service does not carry.
For teams unwilling or unable to self-host, the pixal3d.ai service requires authentication and credit consumption for every generation. The platform includes browser-based utility tools — a GLB inspector, format converter, texture checker, and model scale calculator — that work locally without credit cost, which reduces the friction of verifying outputs before handoff.