What HY-3D-3.1 is
HY-3D-3.1 is Tencent's specialized 3D asset generation model in the Hunyuan 3D family. Its purpose is to create three-dimensional objects from visual or textual guidance. Instead of returning a text completion, it produces downloadable 3D model files that can be inspected, edited, or imported into other production tools.
Tencent positions the 3.1 release as an improvement over HY-3D-3.0 in geometric precision and texture detail. The available research supports that positioning as a provider claim; independent benchmark measurements are not supplied here, so the size of the improvement cannot be quantified.
The model is available through Tencent Cloud's HY-3D professional API and TokenHub. Both are intended for production-oriented generation workflows, with requests processed as asynchronous tasks rather than immediate conversational responses.
Supported inputs and outputs
HY-3D-3.1 accepts several kinds of conditioning input:
- Text: Chinese prompts can describe the object or scene to generate.
- Single images: Uploaded images or image URLs can guide image-to-3D generation.
- Sketches: Supported workflows can use sketches or line art as visual guidance.
- Multi-view images: Up to eight directional images can be used for reconstruction when one view does not adequately describe hidden surfaces.
The output is a 3D asset rather than text, audio, an image, or a video. Depending on the selected workflow and parameters, the result can be a textured model or a geometry-only white model. Documented export formats include OBJ, GLB, STL, USDZ, and FBX, although format availability can depend on the interface and request parameters. OBJ and GLB are described as default result formats in the TokenHub workflow.
In practical terms, a product team might provide a product photograph to generate a starting 3D asset, while a game artist might provide a text description or several views of a character prop. Multi-view input is especially useful when the front view alone would leave the model's rear or side geometry ambiguous.
Capabilities and production role
The model's main strength is focused 3D asset creation. It covers several stages that would otherwise require separate modeling or reconstruction work:
- Text-to-3D generation from Chinese descriptions.
- Single-image-to-3D reconstruction.
- Multi-view reconstruction from as many as eight supported views.
- Sketch-conditioned asset generation.
- Textured asset generation for visual presentation.
- Geometry-only generation for workflows that need a base mesh or white model.
- Export to common 3D formats for downstream use.
This makes HY-3D-3.1 more comparable to a specialized 3D generation service than to a general-purpose AI assistant. It can help create a first-pass asset quickly, but the supplied information does not establish that every generated object is ready for final production without human review. Cleanup, topology corrections, UV work, rigging, material adjustments, and engine-specific optimization may still be necessary.
API workflow and documented limits
TokenHub uses a submit-and-query workflow. A client submits a request containing the hy-3d-3.1 model identifier and the relevant prompt, image, or multi-view inputs. The service returns a task identifier. A later query checks the task status and retrieves links to the generated files when processing is complete.
This asynchronous design is important when evaluating the model. It is suitable for asset pipelines that can wait for a generation task to finish, but it is not designed for token-by-token streaming or immediate conversational interaction. The documented task identifier remains valid for 24 hours, and the default concurrency allocation is three tasks.
Text prompts can contain up to 1,024 UTF-8 characters. Supported image formats include JPG, PNG, JPEG, and WebP, subject to Tencent's documented resolution and file-size requirements. The supplied research does not provide the exact resolution and file-size values, so they should be checked in the active API documentation before implementation.
The TokenHub interface does not support the low_poly parameter for HY-3D-3.1. Some legacy API workflows also restrict particular sketch or low-poly parameters when version 3.1 is selected. This matters for teams that specifically need a low-polygon result: the model may still be useful as a source asset, but the documented TokenHub configuration does not provide that direct control.
No context-window size or maximum output-token limit is documented because this is not a text-generation model. The output is delivered as 3D files through an asynchronous task rather than as a token stream.
HY-3D-3.1 pricing
TokenHub charges HY-3D-3.1 per generation task rather than using separate language-model input and output token prices. The published consumption range is 15 to 60 credits per task, and one credit is priced at CNY 0.12. That produces an approximate reference range of CNY 1.80 to CNY 7.20 per generation.
| Item | Documented information |
|---|---|
| Billing method | Per-generation task credits |
| Consumption range | 15–60 credits per task |
| Credit price | CNY 0.12 per credit |
| Approximate task range | CNY 1.80–CNY 7.20 |
The final charge depends on the selected generation configuration and the billing record. The range should therefore be treated as a reference rather than a guaranteed single price for every request. Text and image inputs are included in the task-based charge instead of being priced as separate tokens.
Reasoning, coding, and tool support
HY-3D-3.1 is not a general reasoning or coding model. It does not provide a conversational answer channel for solving programming problems, writing software, or performing extended textual reasoning. Any planning involved in turning a prompt or image into a 3D asset is part of the model's generation process, not a separately documented reasoning mode.
It also has no documented tool or function-calling capability. The API workflow itself provides submission and status-query operations, but these should not be confused with model tool use. The model does not independently browse the web, call business functions, or operate external software according to the supplied specifications.
For the same reason, HY-3D-3.1 should not be selected when the primary requirement is chat, code generation, embeddings, speech, real-time interaction, or structured text output. A general-purpose model or a purpose-built coding, speech, or embedding service would be more appropriate for those tasks.
Strengths and trade-offs
HY-3D-3.1's principal advantage is specialization. Compared with a general-purpose text or image model, it directly targets 3D asset creation and provides 3D file outputs. Its support for textured and geometry-only results also lets a team choose between a presentation-oriented asset and a simpler base form. Multi-view reconstruction is another practical advantage when several reference angles are available.
Its trade-offs follow from that specialization. The model does not offer the breadth of a conversational AI system, and its asynchronous processing is less convenient for interactive applications. The available research does not provide generation latency benchmarks, so no precise speed ranking should be assumed. Editorially, its cost profile can be attractive for batch asset creation because the listed task range is explicit and relatively easy to estimate, but the actual value depends on how much manual correction each generated asset requires.
The lack of a TokenHub low-poly parameter may also be significant for mobile games, stylized real-time scenes, or pipelines with strict polygon budgets. Teams in those workflows may need a separate simplification or optimization stage after generation.
When to choose HY-3D-3.1
HY-3D-3.1 is a sensible choice when the main goal is to create a 3D starting point from text, a product image, a sketch, or multiple reference views. It is particularly relevant for:
- Game studios building early asset libraries or prototypes.
- Designers who need a quick 3D concept from a sketch or description.
- E-commerce teams creating product visualization assets from reference images.
- Digital-human and virtual-environment workflows that need generated objects.
- 3D printing projects that need a generated mesh as a starting point.
- Batch pipelines that can submit jobs and retrieve results asynchronously.
Choose another type of option when you need instant conversational responses, text reasoning, code generation, speech, embeddings, or tightly controlled low-poly output directly from the generation request. A conventional 3D modeling workflow may also be preferable when exact dimensions, topology, manufacturability, or production-ready rigging are more important than rapid asset creation.
Bottom line
HY-3D-3.1 is best understood as a production-oriented 3D asset generator rather than an all-purpose AI model. Its defining capabilities are text-to-3D, image-to-3D, sketch support, multi-view reconstruction, textured output, and geometry-only output through Tencent Cloud services. The 15–60-credit task pricing, support for up to eight views, 1,024-character prompt limit, asynchronous API design, and lack of a TokenHub low-poly parameter are the most important practical details for evaluation. It is a strong fit for rapid asset creation and prototyping, provided the team allows time for inspection and downstream 3D cleanup.