gsplat-optimizer

Original：🇺🇸 English

Translated

1 scriptsChecked / no sensitive code detected

Optimize 3D Gaussian Splat scenes for real-time rendering on iOS, macOS, and visionOS. Use when working with .ply or .splat files, targeting mobile/Apple GPU performance, or needing LOD, pruning, or compression strategies for 3DGS scenes.

2installs

Sourceckorhonen/claude-skills

Added on2026-02-16

NPX Install

npx skill4agent add ckorhonen/claude-skills gsplat-optimizer

SKILL.md Content

View Translation Comparison →

Gaussian Splat Optimizer

Optimize 3D Gaussian Splatting scenes for real-time rendering on Apple platforms (iOS, macOS, visionOS) using Metal.

When to Use

Optimizing
```
.ply
```
or
```
.splat
```
files for mobile/Apple GPU targets
Reducing gaussian count for performance (pruning strategies)
Implementing Level-of-Detail (LOD) for large scenes
Compressing splat data for bandwidth/storage constraints
Profiling and optimizing Metal rendering performance
Targeting specific FPS goals on Apple hardware

Quick Start

Input: Provide a

.ply

/

.splat

file path, target device class, and FPS target.

bash

# Analyze a splat file
python ~/.claude/skills/gsplat-optimizer/scripts/analyze_splat.py scene.ply --device iphone --fps 60

Output: The skill provides:

Point/gaussian pruning plan (opacity, size, error thresholds)
LOD scheme suggestion (distance bins, gaussian subsets)
Compression recommendation (if bandwidth/storage bound)
Metal profiling checklist with shader/compute tips

Optimization Workflow

Step 1: Analyze the Scene

First, understand your scene characteristics:

Gaussian count: Total number of splats
Opacity distribution: Histogram of opacity values
Size distribution: Gaussian scale statistics
Memory footprint: Estimated GPU memory usage

Step 2: Determine Target Device

Device Class	GPU Budget	Max Gaussians (60fps)	Storage Mode
iPhone (A15+)	4-6GB unified	~2-4M	Shared
iPad Pro (M1+)	8-16GB unified	~6-8M	Shared
Mac (M1-M3)	8-24GB unified	~8-12M	Shared/Managed
Vision Pro	16GB unified	~4-6M (stereo)	Shared
Mac (discrete GPU)	8-24GB VRAM	~10-15M	Private

Step 3: Apply Pruning

If gaussian count exceeds device budget:

Opacity threshold: Remove gaussians with opacity < 0.01-0.05
Size culling: Remove sub-pixel gaussians (< 1px at target resolution)
Importance pruning: Use LODGE algorithm for error-proxy selection
Foveated rendering: For Vision Pro, reduce density in peripheral view

See references/pruning-strategies.md for details.

Step 4: Implement LOD (Large Scenes)

For scenes exceeding single-frame budget:

Distance bins: Near (0-10m), Mid (10-50m), Far (50m+)
Hierarchical structure: Octree or LoD tree for spatial queries
Chunk streaming: Load/unload based on camera position
Smooth transitions: Opacity blending at chunk boundaries

See references/lod-schemes.md for details.

Step 5: Apply Compression (If Needed)

For bandwidth/storage constraints:

Method	Compression	Use Case
SOGS	20x	Web delivery, moderate quality
SOG	24x	Web delivery, better quality
CodecGS	30x+	Maximum compression
C3DGS	31x	Fast rendering priority

See references/compression.md for details.

Step 6: Profile and Optimize Metal

Choose storage mode: Private for static data, Shared for dynamic
Optimize shaders: Function constants, thread occupancy
Profile with Xcode: GPU Frame Capture, Metal System Trace
Iterate: Measure, optimize, repeat

See references/metal-profiling.md for details.

Key Metrics

Metric	Target	How to Measure
Frame time	16.6ms (60fps)	Metal System Trace
GPU memory	< device budget	Xcode Memory Graph
Bandwidth	< 50GB/s	GPU Counters
Shader time	< 10ms	GPU Frame Capture

Reference Implementation

MetalSplatter is the primary reference for Swift/Metal gaussian splatting:

Repository: https://github.com/scier/MetalSplatter
Supports iOS, macOS, visionOS
~8M splat capacity with v1.1 optimizations
Stereo rendering for Vision Pro

Getting Started with MetalSplatter