Producing 3D Gaussian Splatting (3DGS) models is fundamentally GPU-bound, with VRAM and system RAM acting as secondary constraints. Hardware requirements scale with scene size (small interiors vs large aerial sites). Below is a clear, commercially grounded specification guide, with CPU brands explicitly defined.
Absolute Minimum (Small Scenes Only)
Suitable for 200–400 images.
GPU (Critical)
- NVIDIA RTX 3060 (12GB VRAM)
- NVIDIA RTX 2070 / 2080 (8GB minimum, restrictive)
CUDA support is mandatory. AMD GPUs are generally unsuitable due to CUDA-based training pipelines.
CPU
Minimum 6 cores from either:
- AMD Ryzen 5 3600
- Intel Core i5-10400
CPU performance mainly impacts COLMAP processing, feature extraction, and dataset preparation.
RAM
- 32GB minimum
(16GB will bottleneck on reconstruction.)
Storage
Practical Minimum (Commercial Work)
For wedding venues, property marketing, and moderate aerial sites (500–1500 images):
GPU
- NVIDIA RTX 3060 (12GB) – entry professional
- NVIDIA RTX 3080
- NVIDIA RTX 4070 (12GB preferred)
CPU (8–12 cores)
From either brand:
- AMD Ryzen 7 3700X / 5800X
- Intel Core i7-10700K / i7-12700K
Higher core counts significantly improve COLMAP reconstruction and dense processing times.
RAM
Storage
- 1TB NVMe (active projects)
- 2–4TB SSD (archive storage)
Recommended Production Spec (Future-Proof)
For large drone datasets and high-resolution Gaussian splats:
GPU
- NVIDIA RTX 4080 (16GB VRAM)
- NVIDIA RTX 4090 (24GB VRAM ideal)
24GB VRAM substantially improves stability and reduces crashes on large aerial scenes.
CPU (12–16 cores)
From either platform:
- AMD Ryzen 9 5900X / 7900X
- Intel Core i9-12900K / i9-13900K
These processors dramatically accelerate feature matching and dense reconstruction.
RAM
- 64GB minimum
- 128GB is ideal for large drone datasets
Storage
Why the GPU Dominates
3DGS training involves:
- Millions of Gaussian parameters
- Real-time GPU rasterisation
- Gradient-based optimisation
- Continuous splat rendering during training
VRAM determines:
- Number of splats
- Image resolution
- Batch size
- Stability
Exceeding VRAM capacity results in immediate crashes.
Typical Dataset Sizes
- Small interior (300–500 images): 20–50GB
- Wedding venue (800–1500 images): 80–200GB
- Large aerial site (2000+ images): 200GB–1TB
Plan storage accordingly.
Laptop vs Desktop
High-end laptops equipped with NVIDIA RTX 4070 or 4080 GPUs and 32–64GB RAM can run 3DGS workflows. However:
- Sustained loads cause thermal throttling.
- Laptop GPUs often have reduced VRAM.
- Training times are longer.
For commercial production, desktop systems are significantly more efficient and stable.
Bottom Line
Minimum to run:
NVIDIA RTX 3060 (12GB) + 32GB RAM + Ryzen 5 / Core i5
Minimum for professional reliability:
NVIDIA RTX 4080 + 64GB RAM + Ryzen 9 / Core i9
