Seed3D 2.0 - ByteDance's next-generation 3D large-scale model generation technology.

What is Seed3D 2.0?

Seed3D 2.0 is a new generation of large-scale 3D generation model launched by ByteDance. It features a systematic architectural upgrade focusing on geometric accuracy and texture quality, propelling 3D generation from "usable" to "production-ready." The model employs a MoE architecture and a two-stage Coarse-to-Fine generation strategy, achieving industry-leading performance in both geometric generation and PBR texture generation. Users only need to input a single image to generate structurally accurate and realistically textured 3D assets. It supports component-level segmentation, articulated asset generation, and multimodal scene combination. The output seamlessly integrates with mainstream physics simulation engines such as Isaac Sim, and is widely used in games, embodied intelligence, industrial simulation, and digital content production.

Main features of Seed3D 2.0

• High-precision geometry generationThe Coarse-to-Fine two-stage generation strategy is adopted to decouple and optimize the overall structure and local details, accurately restore sharp edges, thin-walled structures, complex topologies and hollow details, and effectively avoid noise, bad surfaces and bevel blur problems in traditional 3D generation.
• Realistic PBR material generationUnified PBR generation model jointly models complete PBR textures (including parameters such as metallicity and roughness), supports multi-level and multi-type complex material combinations such as metal, plastic, ceramic, and fabric, and maintains physically consistent visual performance under different lighting conditions.
• High-definition reproduction of text and symbolsSignificantly improves the clarity of text on product nameplates, packaging, logos, labels, and other scenarios, reducing blurriness, distortion, and garbled text, and meeting the needs of commercial-grade displays.
• Component-level segmentation and articulated asset generationIt supports splitting complete 3D assets into independent components according to function and automatically adding joint information to adapt to multi-degree-of-freedom physical movements such as hinge rotation, drawer push and pull, and robot joints.
• Multimodal scene combination generationIt supports the generation of 3D scenes based on single images, video sequences, or text descriptions, flexibly expanding the creative input methods.
• Physics simulation engine compatibilityThe generated 3D assets, after processing, are directly compatible with mainstream physics simulation engines such as Isaac Sim, and can be used for simulation training tasks such as robot grasping and dynamic interaction.
• MoE Architecture for High-Efficiency InferenceBased on the Mixture of Experts architecture, it controls the amount of inference computation while increasing the number of model parameters and resolution, achieving a balance between high-resolution material details and accurate boundaries.
• VLM a priori enhancement material decompositionIntroducing prior knowledge from the Visual Language Model (VLM) enhances the stability and accuracy of material decomposition under unknown lighting conditions, thereby improving the quality of material reproduction in complex scenes.

How to use Seed3D 2.0

• Access Volcano Engine PlatformGo to the Volcano Engine website (Volcano Ark) and register or log in to your personal/corporate account.
• Location model entryIn the console, select "Visual Model" → "3D Generation" → "Doubao" → "Seed3D 2.0" to enter the model experience page.
• Select input modeChoose the input method according to your creative needs. It supports single images, video sequences or text descriptions as generation conditions.
• Upload materials or enter a descriptionUpload reference images/videos, or enter detailed text prompts to describe the geometric structure and material characteristics of the target 3D asset.
• Configure generation parameters(Optional): Adjust the generation settings as needed, such as advanced options like component-level segmentation, hinge joint definition, and material complexity.
• Initiate generation taskAfter submission, wait for the model to complete the two-stage Coarse-to-Fine generation to obtain a 3D geometric model with complete PBR textures.
• Preview and download assetsPreview the generated 3D model online, confirm the geometric accuracy and material representation, and then download the standard format 3D file and texture resources.
• Connect to production pipelineImport the exported 3D assets into DCC tools such as Blender and Maya, or directly connect them to physical simulation engines such as Isaac Sim for subsequent editing and dynamic interactive training.

Seed3D 2.0Official website address

• Project official websitehttps://seed.bytedance.com/zh/seed3d_2_0

Technical Principles of Seed3D 2.0

• MoE Sparse Expert Routing ArchitectureIt adopts the Mixture of Experts architecture, which effectively controls the computational overhead of the inference stage while increasing the number of model parameters and the generation resolution through the sparse activation mechanism, thus achieving a balance between high-resolution material details and accurate geometric boundaries.
• Coarse-to-Fine two-stage generation strategyThe overall structural modeling and local geometric detail optimization are decoupled. First, coarse-grained overall structure generation is performed, and then fine-grained geometric detail optimization is performed to accurately restore sharp edges, thin-walled structures and complex topologies, avoiding noise and bad surfaces.
• Unified PBR material co-modeling: Construct an end-to-end PBR generation model, jointly model complete physically rendered textures (including parameters such as metallicity, roughness, and normals), support multi-level and multi-type complex material combinations, and ensure physical consistency under different lighting conditions.
• VLM a priori-enhanced material decompositionIntroducing prior knowledge from a visual language model enhances the stability and accuracy of material decomposition under unknown lighting and complex environmental conditions, and improves the ability to distinguish the physical properties of metals, plastics, ceramics, fabrics, etc.
• Component-level semantic segmentation and joint bindingBased on functional semantics, it automatically breaks down complete 3D assets into independent parts and automatically infers and adds joint information, supporting the definition of multi-degree-of-freedom physical motion such as hinge rotation, drawer push and pull, and robot joints.

Key information and usage requirements of Seed3D 2.0

• Product NameSeed3D 2.0.
• Developer: ByteDance Seed Team.
• Release timeApril 23, 2026.
• Technical ReportIt has been made public.
• API ServiceThe Volcano Engine (Volcano Ark) is now available online. After logging in, select "Visual Model → 3D Generation → Doubao → Seed3D 2.0" to experience it.
• Input methodSupports multimodal input including images, videos, and text.
• Output formatComplete 3D geometric model + PBR material texture, supporting part splitting and joint binding.
• Applicable ScenariosApplications include: game asset creation, embodied intelligence training, simulation environment construction, industrial digital twins, and e-commerce 3D display.

Seed3D 2.0's core advantages

• Dual SOTA test resultsIn both core tasks of geometry generation and end-to-end materialized asset generation, it achieved state-of-the-art (SOTA) results in the industry.
• Leading professional blind reviewSixty human evaluators with 3D modeling experience participated in a blind Pairwise Comparison test, and the geometry generation preference rate was significantly better than all comparison models; the texture 3D content generation preference rate reached [percentage missing]. More than 69%.
• MoE Architecture for High-Efficiency InferenceBy using sparse expert routing, the amount of inference computation can be controlled while increasing the number of model parameters and resolution, thus achieving a balance between high-resolution material details and accurate boundaries.
• VLM a priori enhancement material decompositionIntroducing a Visual Language Model (VLM) prior enhances the stability and accuracy of material decomposition under unknown lighting conditions.
• Production-level availabilityOutputs complete PBR textures, ensuring that assets maintain physically consistent visual appearance under different lighting conditions, and can be directly integrated into standard rendering pipelines and production workflows.

Seed3D 2.0Comparison with similar competing products

Application Scenarios of Seed3D 2.0

• Game and film productionIt can quickly generate high-precision characters, props, and scene assets, shortening the 3D modeling cycle.
• Embodied Intelligence and Robot TrainingGenerates articulated assets with physical properties for robot grasping and interaction training in simulation environments such as Isaac Sim.
• Industrial Design and Digital TwinBased on schematic diagrams, we can infer complete three-dimensional structures and reconstruct complex mechanical structures such as industrial equipment and conveyor belts.
• E-commerce and MarketingGenerates 3D product models with high-definition text and logos, supporting realistic display of multiple materials.
• Virtual Reality and the Metaverse: Build physically consistent, interactive 3D scenes and assets.