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JohannesGaessler
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Fixes issue described in #16528 (comment) .

The problem as far as I can tell are numerical issues for the rescaling of the VKQ accumulators with the inverse of the KQ sum at the end of the kernel. The input values in test-backend-ops and the models I tested did not provoke this issue so I did not detect it in #16492 . The fix is to simply use FP32 arithmetic, the impact on performance is negligible since it's only done once per CUDA block.

@github-actions github-actions bot added Nvidia GPU Issues specific to Nvidia GPUs ggml changes relating to the ggml tensor library for machine learning labels Oct 12, 2025
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ggml changes relating to the ggml tensor library for machine learning Nvidia GPU Issues specific to Nvidia GPUs

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