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threejs-perf

Three.js performance optimization patterns for draw calls, scene traversal, and instancing. Use when optimizing 3D scenes with 100+ repeated objects, thousands of moving entities, or draw calls above

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About

Imported from playableintelligence/game-creator (skills/threejs-perf/SKILL.md) via skills.sh. Install upstream with npx skills add playableintelligence/game-creator --skill threejs-perf. Copyright stays with the author (MIT).

Three.js Performance Optimization

Performance patterns for Three.js games, backed by measured before/after numbers on Three.js r183 (headless Chromium via Playwright, Apple M1 Pro, software WebGL).

Reference Files

  • instancing-static.md — InstancedMesh for large static repeated objects (19,600 → 1 draw call)
  • instancing-moving.md — Flat state buffer + batched InstancedMesh writes for moving entities (8,000 entities)
  • templates/ — Baseline vs optimized reference implementations for each pattern

When to Use This Skill

  • Scene has 100+ repeated objects sharing geometry/material
  • Draw calls exceed 500 and frame time is unstable
  • Thousands of moving entities need per-frame transform updates
  • Profile shows scene-graph traversal as a bottleneck

When NOT to Use

  • Object count is low (<50 unique meshes) — simpler code wins
  • Every object needs unique materials/shaders that defeat batching
  • Geometry differs enough that instancing provides no batching benefit

Pattern 1: Instancing Large Static Object Sets

Problem: Forests, debris, decorations as individual Meshes = unnecessary draw calls.

Solution: One InstancedMesh per shared geometry+material combo.

Evidence: ~19,365 → 2 draw calls. Render CPU p95: 28.5ms → 0.5ms (~57× faster). Build: 39.4ms → 3.9ms. See instancing-static.md.

// Anti-pattern: one Mesh per prop
for (let i = 0; i < 19600; i++) {
  const mesh = new THREE.Mesh(geometry, material);
  mesh.position.set(x, 0, z);
  scene.add(mesh); // 19,600 draw calls
}

// Correct: one InstancedMesh
const im = new THREE.InstancedMesh(geometry, material, 19600);
const mat = new THREE.Matrix4();
for (let i = 0; i < 19600; i++) {
  mat.makeTranslation(x, 0, z);
  im.setMatrixAt(i, mat);
}
im.instanceMatrix.needsUpdate = true;
scene.add(im); // 1 draw call

Pattern 2: Moving Entity Update Loops

Problem: Thousands of moving actors as individual Meshes = scene-graph churn + transform propagation.

Solution: Flat entity state buffer + batched InstancedMesh.setMatrixAt() writes.

Evidence: 8,000 → 1 draw calls. Render CPU p95: 9.9ms → 0.5ms (~20× faster). Update loop p95: 1.4ms → 0.3ms. See instancing-moving.md.

// Anti-pattern: per-entity Mesh position writes
meshes.forEach((mesh, i) => {
  mesh.position.x = computeX(i, tick);
  mesh.position.y = computeY(i, tick);
});

// Correct: batched instance matrix writes
const mat = new THREE.Matrix4();
for (let i = 0; i < count; i++) {
  mat.makeTranslation(computeX(i, tick), computeY(i, tick), computeZ(i, tick));
  instancedMesh.setMatrixAt(i, mat);
}
instancedMesh.instanceMatrix.needsUpdate = true;

Decision Tree

Is the object repeated 50+ times with same geometry+material?
├── YES → Is it static (no per-frame movement)?
│   ├── YES → Pattern 1: Static InstancedMesh (instancing-static.md)
│   └── NO  → Pattern 2: Moving InstancedMesh with batched writes (instancing-moving.md)
└── NO  → Standard Mesh is fine. Focus on material/geometry reuse.

Measured Results

Headless Chromium 147 via Playwright, Three.js r183, Apple M1 Pro, 30 warmup + 180 sample frames, median of 3 runs.

Scenario Metric Baseline Optimized Improvement
Static World (19.6k cubes) Draw calls ~19,365 2 ~9,682×
Static World (19.6k cubes) Render CPU p95 28.5ms 0.5ms ~57×
Static World (19.6k cubes) Build 39.4ms 3.9ms ~10×
Moving Entities (8k wave-field) Draw calls 8,000 1 8,000×
Moving Entities (8k wave-field) Render CPU p95 9.9ms 0.5ms ~20×
Moving Entities (8k wave-field) Update loop p95 1.4ms 0.3ms ~4.7×

Methodology notes

  • CPU-side metrics are the trustworthy signal. Draw calls, render CPU p95, update loop, and build time reliably show the 1–2 order-of-magnitude win.
  • FPS and frame-time p95 are unreliable in headless Chromium. Playwright's bundled Chromium uses SwiftShader (software WebGL), which bottlenecks on fragment shading of ~90 MB of visible geometry regardless of draw-call count. On real hardware WebGL, the FPS gap would be substantially larger — baseline would drop to single-digit FPS under real fill, and optimized would hit vsync cleanly.
  • A benchmark passes if draw calls decreased and render CPU p95 did not regress.

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

yaml
targets:
  - https://api.opensmartroute.ai/api/v1/registry/playableintelligence-game-creator-threejs-perf/manifest   # or paste the manifest below

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

playableintelligence-game-creator-threejs-perf.ocm.jsonjson
{
  "ocm": "1",
  "id": "playableintelligence-game-creator-threejs-perf",
  "kind": "skill",
  "name": "threejs-perf",
  "description": "Three.js performance optimization patterns for draw calls, scene traversal, and instancing. Use when optimizing 3D scenes with 100+ repeated objects, thousands of moving entities, or draw calls above 500. Loaded by threejs-game, viral-game, and make-game for performance guidance.",
  "publisher": "playableintelligence",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "math"
    ],
    "tags": [
      "skill-md",
      "threejs",
      "performance",
      "instancing",
      "draw-calls",
      "optimization",
      "skills-sh"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "Three.js performance optimization patterns for draw calls, scene traversal, and instancing. Use when optimizing 3D scenes with 100+ repeated objects, thousands of moving entities, or draw calls above 500. Loaded by threejs-game, viral-game, and make-game for performance guidance."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "skills.sh",
      "repository": "https://github.com/playableintelligence/game-creator",
      "path": "skills/threejs-perf/SKILL.md",
      "ref": "HEAD",
      "url": "https://www.skills.sh/playableintelligence/game-creator/threejs-perf",
      "key": "playableintelligence/game-creator/skills/threejs-perf/SKILL.md"
    },
    "license": "MIT"
  },
  "instructions": "# Three.js Performance Optimization\n\nPerformance patterns for Three.js games, backed by measured before/after numbers on Three.js r183 (headless Chromium via Playwright, Apple M1 Pro, software WebGL).\n\n## Reference Files\n\n- `instancing-static.md` — InstancedMesh for large static repeated objects (19,600 → 1 draw call)\n- `instancing-moving.md` — Flat state buffer + batched InstancedMesh writes for moving entities (8,000 entities)\n- `templates/` — Baseline vs optimized reference implementations for each pattern\n\n## When to Use This Skill\n\n- Scene has 100+ repeated objects sharing geometry/materi",
  "cost": {
    "context_tokens": 1091
  }
}

Fetch it by URL: GET /api/v1/registry/playableintelligence-game-creator-threejs-perf/manifest?version=1.0.0

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