WebGPU vs WebGL: Introduction and technical comparison of the graphics APIs

WebGPU vs WebGL describes two graphics APIs that are currently shaping the future of web graphics.

WebGL (Web Graphics Library) is based on OpenGL ES 2.0, has been in use since 2011 and enables interactive 3D content directly in the browser.

WebGPU is a modern, low-level hardware API inspired by Vulkan, Metal and DirectX 12. It is an official W3C candidate standard and initially available in Chrome 113 (April 2023).

Differences between WebGPU and WebGL

1. state management & pipelines

Global state (WebGL): Settings such as colors, textures or shaders remain active until they are explicitly changed. Developers must always know what is currently set in the system - otherwise errors or unexpected effects will occur. In large projects, settings can also overlap and cause unpredictable behavior.

Pipelines & Command Encoder (WebGPU): Everything that is required for a graphics task - shaders, textures, colors, render settings - is combined in a so-called pipeline. If something needs to be changed, you simply create a new pipeline. This keeps the code clear and different modules do not interfere with each other. This increases maintainability and robustness.

2. shader models & languages

WebGL uses GLSL ES for vertex and fragment shaders - an established but older language.

WebGPU uses WGSL - a modern, typed language, clearly structured and more powerful for current hardware.

3. compute shader

WebGL does not offer real compute shaders and often requires cumbersome workarounds.

WebGPU offers dedicated compute shaders - ideal for simulations, data processing and ray tracing.

4. synchronicity & performance

WebGL works mainly synchronously - every command is executed directly, which can lead to delays and poor performance in complex scenes.

WebGPU works asynchronously with command queues. Commands are scheduled and relieve the CPU-GPU pipeline, which increases efficiency in complex scenes.

Technical depth

With WebGPU, shaders, textures and uniforms are clearly assigned and typified. Buffer layouts are precisely defined. WebGL works with less structured memory access and an untyped model.

Practical example: Performance behavior

Various tests have shown that WebGL works faster in some cases - e.g. with simple particle effects. WebGPU, on the other hand, scores points with complex calculations or simulations. The actual performance depends heavily on the application, complexity and hardware.

When is something worthwhile?

Conclusion: hybrid approach

WebGL is ideal when speed is of the essence and maximum compatibility is required.

WebGPU is particularly suitable for long-term, high-performance projects with high maintainability.

Recommendation for Design4real: Uses WebGL as a basis and integrates WebGPU specifically where performance and modular architecture offer decisive advantages - e.g. for simulations, data-intensive graphics or XR applications.