Private 3D AI

3D generation models and GPU requirements

Compare local 3D models for shape, texture and asset generation. Many pipelines have separate geometry, multiview and texture stages, so each stage and the complete hand-off need sizing.

Compare 1 models Compare server hardware

Selection approach

Choose for the workload, then size the complete deployment

Judge the exported asset, not only the preview. Topology, texture quality, UV handling and compatibility with the downstream DCC or game-engine workflow determine practical value.

What to compare

Image-to-3D or text-to-3D input
Mesh, Gaussian or other output representation
Texture, UV and material requirements
Downstream DCC and engine compatibility

What changes the hardware

Separate shape and texture model peaks
Multiview image-generation overhead
System RAM for mesh processing
Storage for intermediate assets and revisions

What to test before purchase

Geometry quality and watertightness
Texture alignment and usable resolution
Export into the target production software
End-to-end generation time and failure recovery

Showing 1 models

Tencent

Hunyuan3D 2.1

Tencent's image-to-3D generation pipeline for shape and texture creation, with open model weights and a model-specific community licence.

3D generation

Minimum GPU memory: 24GB single-GPU planning floor
Recommended starting system: Studio 96
Licence: Tencent Hunyuan Community Licence

See specifications and all 11 systems

Model-to-hardware fit

Memory fit is the first gate, not the final recommendation

01Exact model version
Use the precise model version, numerical format and complete software pipeline intended for production.
02Minimum memory
Check whether it can load on one GPU or requires supported multi-GPU loading.
03Working headroom
Allow for context, cache, batch, media encoders and concurrent users.
04Workload test
Measure quality, latency and stability on representative work.

Diagram showing an approved request, a local service, an approved store and a policy-controlled data path — A private deployment starts with the permitted data path, access policy and logging boundary. GPU Servers technical illustration.

GPU server remote management dashboard with system status, access logs and sensor monitoring panels — Supplier screenshot of the platform management interface. The final management features and access policy depend on the ordered system. OEM supplier reference image.

Diagram showing approved documents moving through a searchable index to an answer with a source citation — A retrieval workflow should connect each useful answer to approved source material and defined refusal behaviour. GPU Servers technical illustration.

Diagram of an evidence pack containing an asset schedule, burn-in record, health readings, workload test and admin guide — A complete handover includes the supplied assets, test results, operating instructions and agreed follow-up work. GPU Servers technical illustration.