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2 Comments
Source: Blender benchmarks, specifically [https://opendata.blender.org/benchmarks/query/?compute_type=OPTIX&compute_type=CUDA&compute_type=HIP&compute_type=METAL&compute_type=ONEAPI&group_by=device_name&blender_version=4.0.0](https://opendata.blender.org/benchmarks/query/?compute_type=OPTIX&compute_type=CUDA&compute_type=HIP&compute_type=METAL&compute_type=ONEAPI&group_by=device_name&blender_version=4.0.0)
Filtered by “NVIDIA Geforce RTX” cards only, exported to CSV, and rendered using Python and Seaborn. I manually added the family column to the CSV data to get it grouped by family.
This is for Nvidia’s consumer cards only, color-coded by family / series (green for 40 series, orange for 30 series, red for 20 series).
The code to generate this was almost 100% written in ChatGPT 🙂 I just prompted ChatGPT to write the Python code to generate the bar charts grouped by family, and had to make a few tweaks and further prompts to get what I wanted.
That unlabeled score axis hurts my soul