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stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2\">\u003Cpath d=\"M11.017 2.814a1 1 0 0 1 1.966 0l1.051 5.558a2 2 0 0 0 1.594 1.594l5.558 1.051a1 1 0 0 1 0 1.966l-5.558 1.051a2 2 0 0 0-1.594 1.594l-1.051 5.558a1 1 0 0 1-1.966 0l-1.051-5.558a2 2 0 0 0-1.594-1.594l-5.558-1.051a1 1 0 0 1 0-1.966l5.558-1.051a2 2 0 0 0 1.594-1.594zM20 2v4m2-2h-4\"\u002F>\u003Ccircle cx=\"4\" cy=\"20\" r=\"2\"\u002F>\u003C\u002Fg>",{"left":4,"top":4,"width":5,"height":5,"rotate":4,"vFlip":6,"hFlip":6,"body":44},"\u003Cg fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2\">\u003Cpath d=\"M21.42 10.922a1 1 0 0 0-.019-1.838L12.83 5.18a2 2 0 0 0-1.66 0L2.6 9.08a1 1 0 0 0 0 1.832l8.57 3.908a2 2 0 0 0 1.66 0zM22 10v6\"\u002F>\u003Cpath d=\"M6 12.5V16a6 3 0 0 0 12 0v-3.5\"\u002F>\u003C\u002Fg>","\u003Cblockquote>\n\u003Cp>Smooth in Blender viewport, ten-second load and stutter on the web. The browser isn't "weak"—Web has different budgets than desktop: network download and lowest-common-denominator GPUs. Optimization cuts overhead that barely affects appearance across mesh, vertices, and textures.\u003C\u002Fp>\n\u003C\u002Fblockquote>\n\u003Cp>\u003Cimg src=\"\u002Fblog\u002Foptimize-3d-model-for-web\u002Fcover.webp\" alt=\"Web 3D optimization: decimation, vertex merge, texture compression\">\u003C\u002Fp>\n\u003Ch2>Why Is Web 3D More Constrained Than Desktop?\u003C\u002Fh2>\n\u003Cp>Web adds two hard constraints vs. desktop modeling: \u003Cstrong>download bandwidth\u003C\u002Fstrong> and \u003Cstrong>device GPU floor\u003C\u002Fstrong>. Desktop has local files and usually strong GPUs; the web must transfer the model over the network, then render in real time on possibly low-end phone GPUs.\u003C\u002Fp>\n\u003Cp>Two bottleneck classes: \u003Cstrong>loading\u003C\u002Fstrong>—larger files, longer time to first frame; \u003Cstrong>runtime\u003C\u002Fstrong>—triangles, draw calls, texture sampling drive frame rate. Optimization targets both—three levers on the model: triangle count, vertex data, texture volume.\u003C\u002Fp>\n\u003Ch2>Reducing Triangles: What Decimation Does\u003C\u002Fh2>\n\u003Cp>Decimation (mesh simplification) \u003Cstrong>approximates the original silhouette with fewer triangles\u003C\u002Fstrong>. Mainstream approach: \u003Cstrong>QEM (Quadric Error Metrics)\u003C\u002Fstrong>—estimate surface deviation if each edge collapses, repeatedly collapse lowest-error edges until target count.\u003C\u002Fp>\n\u003Cp>Why moderate decimation is invisible: flat regions lose tiny triangles with near-zero silhouette impact; high-curvature corners are preserved. Clear limits:\u003C\u002Fp>\n\u003Cul>\n\u003Cli>\u003Cstrong>Over-decimation collapses silhouette\u003C\u002Fstrong>: beyond a ratio, surfaces turn blocky, detail vanishes—threshold depends on original geometry.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>UV seams and normals suffer\u003C\u002Fstrong>: decimation can break UV boundaries → texture misalignment—algorithms must protect seams.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Hard surface vs. organic\u003C\u002Fstrong>: mechanical parts more sensitive; characters\u002Fterrain tolerate more.\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2>Merging Duplicate Vertices: Optimization Without Fewer Faces\u003C\u002Fh2>\n\u003Cp>Many models \u003Cstrong>store the same logical point multiple times\u003C\u002Fstrong>—export splits vertices per face, so vertex count far exceeds geometric need. Welding\u002Fmerge-by-distance shrinks data and improves cache hits without changing face count.\u003C\u002Fp>\n\u003Cp>Often missed: \u003Cstrong>merge only when attributes match\u003C\u002Fstrong>. Same position but different normal or UV → don't merge blindly—hard edges and textures break. Merge is "same position + compatible attributes," not naive dedup. Same face count, very different render cost—vertex reuse and index cache efficiency differ.\u003C\u002Fp>\n\u003Ch2>Textures: Often the Biggest Volume\u003C\u002Fh2>\n\u003Cp>Many optimize face count and ignore \u003Cstrong>textures often dominate file size\u003C\u002Fstrong>. Uncompressed 4K ≈ 4096×4096×4 ≈ 64 MB per map—multiple maps exceed mesh data. Two different optimization paths—don't conflate:\u003C\u002Fp>\n\u003Ctable>\n\u003Cthead>\n\u003Ctr>\n\u003Cth>Technique\u003C\u002Fth>\n\u003Cth>What it compresses\u003C\u002Fth>\n\u003Cth>Nature\u003C\u002Fth>\n\u003Cth>Notes\u003C\u002Fth>\n\u003C\u002Ftr>\n\u003C\u002Fthead>\n\u003Ctbody>\n\u003Ctr>\n\u003Ctd>Lower resolution\u003C\u002Ftd>\n\u003Ctd>Pixel count\u003C\u002Ftd>\n\u003Ctd>One-time, irreversible\u003C\u002Ftd>\n\u003Ctd>Match display size—distant maps don't need 4K\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd>JPEG\u002FPNG\u002FWebP encode\u003C\u002Ftd>\n\u003Ctd>Transfer size\u003C\u002Ftd>\n\u003Ctd>Decodes to full VRAM\u003C\u002Ftd>\n\u003Ctd>Smaller download, same runtime memory\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd>GPU textures (KTX2\u002FBasis)\u003C\u002Ftd>\n\u003Ctd>VRAM\u003C\u002Ftd>\n\u003Ctd>GPU samples directly\u003C\u002Ftd>\n\u003Ctd>Saves download and VRAM; block-compression artifacts\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003C\u002Ftbody>\n\u003C\u002Ftable>\n\u003Cp>Key distinction: \u003Cstrong>regular image compression only saves download—decoded VRAM is full size\u003C\u002Fstrong>; GPU-compressed textures (Basis Universal \u002F KTX2) let GPU sample compressed data—both download and VRAM, at block-compression quality cost.\u003C\u002Fp>\n\u003Ch2>Geometry Compression: What Draco Compresses\u003C\u002Fh2>\n\u003Cp>Mesh download size can shrink further with \u003Cstrong>geometry compression\u003C\u002Fstrong>—Draco quantizes vertex attributes (float coordinates to limited precision) + entropy coding, often reducing mesh to a fraction of original.\u003C\u002Fp>\n\u003Cp>Tradeoffs: \u003Cstrong>quantization is lossy\u003C\u002Fstrong>—coordinate precision loss may cause subtle jitter on high-precision models; \u003Cstrong>decode has runtime cost\u003C\u002Fstrong>—client decoder adds overhead on very weak devices. Draco fits "network is bottleneck, device is OK"—not always-on.\u003C\u002Fp>\n\u003Ch2>How Much Optimization Is Enough?\u003C\u002Fh2>\n\u003Cp>No universal answer—depends on \u003Cstrong>workload\u003C\u002Fstrong>:\u003C\u002Fp>\n\u003Cul>\n\u003Cli>\u003Cstrong>Product viewer \u002F configurator\u003C\u002Fstrong>: prioritize load—decimate to sufficient silhouette, textures sized to display, geometry compression on.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>High-end viz (medical, industrial inspection)\u003C\u002Fstrong>: precision first—careful decimation\u002Fquantization; accept slower load.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Mobile \u002F weak network\u003C\u002Fstrong>: tight VRAM and bandwidth—GPU textures and aggressive decimation pay most.\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>Fit depends on \u003Cstrong>target device, acceptable precision loss, bottleneck is download or frame rate\u003C\u002Fstrong>: download-bound → textures and geometry first; frame-rate-bound → face count and draw calls; precision-sensitive → dial back all lossy steps.\u003C\u002Fp>\n\u003Ch2>Summary\u003C\u002Fh2>\n\u003Cp>Web 3D lag adds download bandwidth and GPU floor vs. desktop. Three dimensions: decimation (QEM collapses low-error edges first—overdo and silhouette collapses), merge duplicate vertices (position + compatible attributes only), textures and geometry compression (distinguish download-only vs. VRAM savings—Draco\u002FKTX2 each have lossy tradeoffs). 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