What are the input requirements?

You need 1 to 4 images. A front view is mandatory; left, right, and back views are optional. Accepted formats are JPG and PNG. Recommended resolution is 512×512 or higher. Backgrounds should be neutral or lightly cluttered (segmentation is supported).

What 3D output formats are supported?

The API outputs 3D meshes in OBJ, GLB, and FBX formats. Textures are UV-mapped and PBR-ready. The coordinate system is right-handed with normalized scale, and the mesh topology is triangulated for downstream optimization.

How much does the API cost?

The cost is $0.525 per generation.

What benchmarks indicate its performance?

It scores 0.21 on LPIPS (Learned Perceptual Image Patch Similarity) and achieves a Chamfer Distance of 0.85, indicating high perceptual similarity and accurate geometry. In a user study, 78% preferred its outputs over other single-image methods.

What are the key features of Magic Image-to-3D?

Key features include generating a full 360-degree model from a single photo, producing high-resolution textures for unseen areas, offering a user-friendly workflow requiring no 3D expertise, and delivering production-ready, optimized models for engines, AR/VR, and 3D printing.

What are the limitations and ethical considerations?

Output quality depends on input image quality. Highly complex geometry may be approximated. Users must only generate models from images they own or have rights to, and should avoid replicating copyrighted designs. The model may reflect biases present in its training data.

What are the primary use cases?

Primary use cases include e-commerce for product visualization, game development for asset prototyping, digital archiving of artifacts, 3D printing of personal items, and AR/VR content creation for populating virtual environments.

How does the Magic Pipeline work?

The process involves four steps: 1) User uploads 1-4 images. 2) The core neural network predicts 3D geometry and synthesizes novel views. 3) A diffusion model generates high-fidelity textures and unwraps them onto a UV map. 4) The final textured mesh is compiled, optimized, and exported in standard formats.

What are the input requirements?

You need 1 to 4 images. A front view is mandatory; left, right, and back views are optional. Accepted formats are JPG and PNG. Recommended resolution is 512×512 or higher. Backgrounds should be neutral or lightly cluttered (segmentation is supported).

What 3D output formats are supported?

The API outputs 3D meshes in OBJ, GLB, and FBX formats. Textures are UV-mapped and PBR-ready. The coordinate system is right-handed with normalized scale, and the mesh topology is triangulated for downstream optimization.

How much does the API cost?

The cost is $0.525 per generation.

What benchmarks indicate its performance?

It scores 0.21 on LPIPS (Learned Perceptual Image Patch Similarity) and achieves a Chamfer Distance of 0.85, indicating high perceptual similarity and accurate geometry. In a user study, 78% preferred its outputs over other single-image methods.

What are the key features of Magic Image-to-3D?

Key features include generating a full 360-degree model from a single photo, producing high-resolution textures for unseen areas, offering a user-friendly workflow requiring no 3D expertise, and delivering production-ready, optimized models for engines, AR/VR, and 3D printing.

What are the limitations and ethical considerations?

Output quality depends on input image quality. Highly complex geometry may be approximated. Users must only generate models from images they own or have rights to, and should avoid replicating copyrighted designs. The model may reflect biases present in its training data.

What are the primary use cases?

Primary use cases include e-commerce for product visualization, game development for asset prototyping, digital archiving of artifacts, 3D printing of personal items, and AR/VR content creation for populating virtual environments.

How does the Magic Pipeline work?

The process involves four steps: 1) User uploads 1-4 images. 2) The core neural network predicts 3D geometry and synthesizes novel views. 3) A diffusion model generates high-fidelity textures and unwraps them onto a UV map. 4) The final textured mesh is compiled, optimized, and exported in standard formats.

Magic Image-to-3D API — One API 400+ AI Models

Q: What is Magic API?

Magic API is a system that converts sparse 2D photos into usable 3D models. It learns to maintain multi-angle coherence, reconstructing surfaces and textures into a single, consistent asset from minimal input, drastically reducing manual modeling labor.

Magic Image-to-3D

Magic Image-to-3D is a generative AI model designed to reconstruct high-quality 3D objects from 1 to 4 input images taken from different viewpoints.

Magic API seamlessly converts sparse 2D photos into usable 3D models. The system learns to maintain multi-angle coherence, reconstructing surfaces and textures into a single, consistent asset from minimal input.

The model is built to:

Drastically cut down on manual modeling labor.
Perform reliably with incomplete or imperfect image sets.
Deliver a practical balance of fast turnaround, high-quality visuals, and structurally sound geometry.

Input Requirements

Number of images: 1–4
Mandatory view: Front
Optional views: Left, Right, Back
Accepted formats: JPG, PNG
Recommended resolution: 512×512 or higher
Background: Neutral or lightly cluttered (segmentation supported)

Output Formats

3D mesh: OBJ / GLB / FBX
Textures: UV-mapped, PBR-ready
Coordinate system: Right-handed, normalized scale
Topology: Triangulated mesh suitable for downstream optimization

API Pricing

$0.65 per generation

Performance Benchmarks

Magic Image-to-3D was evaluated against standard metrics for 3D reconstruction quality:

LPIPS (Learned Perceptual Image Patch Similarity): Scores 0.21 on the challenging Google Scanned Objects dataset, indicating high perceptual similarity to ground truth models.
Chamfer Distance: Achieves a distance of 0.85 (lower is better), demonstrating accurate geometric reconstruction from sparse views.
User Preference Study: In a blind A/B test with creators, 78% preferred the topology and texture coherence of Magic Image-to-3D outputs compared to other single-image methods.

Key Features & Capabilities

Minimal Input, Maximum Output: Generate a full 360-degree 3D model from just a single front-facing photo. Additional views dramatically improve quality.
High-Resolution Texturing: Automatically generates detailed, plausible textures for all sides of the object, including unseen areas.
User-Friendly Workflow: No 3D modeling expertise required. The process is as simple as uploading photos and downloading the model.
Production-Ready Outputs: Models are optimized, watertight, and come with PBR-ready materials suitable for game engines, AR/VR, and 3D printing preparation.

Limitations & Ethical Considerations

Input Sensitivity: Output quality is directly tied to input image quality (lighting, clarity, background).
Geometric Complexity: Highly complex geometry (e.g., dense foliage, intricate chainmail) may be approximated rather than perfectly reconstructed.
Intellectual Property: Only generate 3D models from images you own or have explicit rights to. Do not replicate copyrighted designs or artworks.
Bias: As with all AI models, outputs may reflect biases present in the training data.

Use Cases

E-commerce & Retail: Rapid 3D model creation for product visualization, interactive catalogs, and AR try-on experiences.
Game Development: Fast prototyping of assets, creating variants of props, or generating background objects.
Digital Archiving & Museums: Creating accessible 3D records of artifacts or items from limited photographic references.
3D Printing & Maker Community: Turning a photo of a cherished item, pet, or custom design into a printable 3D model.
AR/VR Content Creation: Quickly populating virtual environments with custom 3D objects.

How It Works: The Magic Pipeline

Image Upload: User provides 1-4 images.
View Synthesis & Geometry Estimation: The model's core neural network predicts the complete 3D geometry and generates consistent, coherent novel views of the object.
Texture Diffusion & Unwrapping: A diffusion model inpaints and generates high-fidelity textures for the entire model, which are then intelligently unwrapped onto a UV map.
Asset Export: The final textured mesh is compiled, optimized, and delivered in standard 3D formats.

Example H2

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