Gaussian Splatting processing time depends on the tool, input size, and available hardware. Here is a breakdown by platform:
Professional Processing (DJI Terra V5.0+)
- Speed: ~500 images per hour for GS reconstruction
- City block: 30–40 minutes from a DJI Matrice 4E capture
- Large site (10,000+ images): Several hours
- Maximum capacity: 30,000 images per task on 32GB+ RAM systems
- Comparison: Approximately 2× faster than traditional mesh-based photogrammetry
Consumer / Cloud Processing
| Tool | Processing Time | Notes |
|---|---|---|
| Luma AI | Under 1 minute | Cloud-based, video upload |
| Polycam | 2–10 minutes | Cloud via AWS, LiDAR or photo input |
| PostShot | 10–60 minutes | Local desktop processing |
| Nerfstudio | 15 minutes–2 hours | Local, depends on dataset size |
| Xgrids LCC Studio | ~5 hours per model | Cloud processing, high quality |
Hardware Requirements
For local GS processing, GPU power determines speed:
- Minimum: 8GB VRAM (e.g., RTX 3060) — handles small scenes
- Recommended: 16–24GB VRAM (e.g., RTX 4080/4090) — handles large scenes efficiently
- System RAM: 32GB minimum for large datasets, 128GB for city-scale reconstructions
- Storage: SSD recommended — GS generates large intermediate files
Training vs Rendering
It is important to distinguish:
- Training time (creating the GS model): Minutes to hours — this is the computationally expensive step
- Rendering time (viewing the result): Real-time at 60+ FPS on any modern GPU — this is GS's key advantage over NeRF
Comparison to Other Methods
| Method | Typical Processing Time | Real-Time Viewing? |
|---|---|---|
| Gaussian Splatting | Minutes to hours | Yes (60+ FPS) |
| NeRF | Hours to days | No (seconds per frame) |
| Mesh Photogrammetry | Hours to days | Limited (requires simplification) |
For a professional Gaussian Splatting project, THE FUTURE 3D handles all processing — you receive finished deliverables without needing GPU hardware. Get a quote →