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Even the best AI models lose about half their performance when charts get complicated, new benchmark finds

THE DECODER / 4/19/2026

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Key Points

  • The RealChart2Code benchmark evaluates 14 leading AI models using complex visualizations generated from real-world datasets to test code generation quality.
  • Results show that even top proprietary models lose nearly half their performance when the input charts become more complicated.
  • The findings suggest that current model capabilities are more reliable on simpler chart-to-code tasks than on diagram-, graph-, and visualization-heavy inputs.
  • The benchmark highlights the need for better robustness in AI systems that translate visual analytics into executable code under challenging conditions.

Collage of diagram windows, color schemes and cables as a symbol for the complexity of converting visualizations into code.

The RealChart2Code benchmark puts 14 leading AI models to the test on complex visualizations built from real-world datasets. Even the top proprietary models lose nearly half their performance compared to simpler tests.

The article Even the best AI models lose about half their performance when charts get complicated, new benchmark finds appeared first on The Decoder.

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