Measuring LLM Performance Through Shader Programming
We've collected 5,600+ shaders from 28 different AI models to see how well they handle the complex world of graphics programming. You can explore the top 200 from each model right here—each one a unique test of mathematical reasoning, creative problem-solving, and technical precision.
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Why Shader Programming?
A Multidimensional Benchmark for AI Systems
Writing shaders is hard—really hard. It's not like typical programming where you can debug your way to success. Every shader demands a perfect storm of skills: deep mathematical intuition, spatial reasoning that would make a sculptor jealous, and the ability to think in parallel like a GPU does. Most coding benchmarks miss this entirely.
Mathematical Precision
Vector math, trigonometry, matrix operations, and complex geometric calculations
Spatial Reasoning
3D coordinate systems, ray marching, SDF modeling, and camera projections
Evaluation Methodology
How We Measure LLM Shader Performance
The ShaderBench Dataset
We asked 28 of the world's smartest AI models to write shaders—lots of them. Using shaderlab.ai as our generation platform, the result was 5,600+ complete GLSL fragment shaders, each one rendering real-time visual effects. We've curated the top 200 from each model for you to explore, vote on, and learn from.
Shader Generation
Using shaderlab.ai, we prompt AI models with creative challenges...
Technical Validation
No shader makes it through unless it actually works...
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