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# WebGPU vs. WebGL: Performance Benchmarks for Client-Side Inference

**[SitePoint](https://daily.dev/sources/sitepoint)** · 15 min read · 0 upvotes · 0 comments

## Summary

A detailed performance comparison of WebGPU vs. WebGL for running LLMs and vision models directly in the browser. The core finding is that WebGPU delivers 3–8× faster GEMM (matrix multiplication) execution at large matrix sizes (2048×2048+) due to native compute shaders, storage buffers, and workgroup shared memory — capabilities WebGL entirely lacks. Benchmarks were run across Apple M2, NVIDIA RTX 3060, and Intel UHD 630 hardware. For real-world LLM inference (Phi-3-mini on M2), token latency drops from ~320 ms to ~85 ms when switching from WebGL to WebGPU. The article includes full WGSL and GLSL shader code, a timing harness using GPUQuerySet timestamp queries, and practical guidance for implementing WebGPU-first backends with WebGL fallback. WebGL remains the necessary fallback for older hardware and Safari stable.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.sitepoint.com/webgpu-vs-webgl-inference-benchmarks/>

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---

Tags: [#webdev](https://daily.dev/tags/webdev), [#machine-learning](https://daily.dev/tags/machine-learning), [#webgpu](https://daily.dev/tags/webgpu)

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