NVIDIA released an open-source AI-powered quantum error correction decoder, the Ising Decoder ColorCode 1 Fast, which the company says reduced logical error rates by up to 347.7 times and accelerated decoding by up to 7.3 times for color code quantum error correction under benchmark conditions. The model uses a small convolutional neural network as a pre-decoder to simplify error syndromes before processing by the open-source Chromobius decoder, improving both decoding accuracy and runtime as quantum code distances increase. NVIDIA also released the model weights, training pipeline, synthetic data generation tools and benchmarking resources as open source, allowing quantum hardware developers to train decoders tailored to the noise characteristics of their own quantum processors. According to NVIDIA’s technical blog, the decoder reduced logical error rates by as much as 347.7 times while running 7.3 times faster than the current state-of-the-art open-source color code decoder, Chromobius, under specific benchmark conditions.