# AMP autocast not faster than FP32

**URL:** <https://discuss.pytorch.org/t/amp-autocast-not-faster-than-fp32/111757>\
**Category:** mixed-precision\
**Created:** [February 13, 2021, 12:07am UTC](https://discuss.pytorch.org/t/amp-autocast-not-faster-than-fp32/111757 "2021-02-13T00:07:39Z")\
**Posts on this page:** 1\
**Showing post:** 13

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**Author:** ![ptrblck](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/ptrblck/32/1823_2.png) [@ptrblck](https://discuss.pytorch.org/u/ptrblck)\
**Post date:** [August 27, 2021, 10:15pm UTC](https://discuss.pytorch.org/t/amp-autocast-not-faster-than-fp32/111757/13 "2021-08-27T22:15:47Z")

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Your A6000 would use TF32 by default and would thus already speedup your wokload using TensorCores. [This post](https://github.com/pytorch/pytorch/issues/57806) has additional information, but skip the “channels-last” part since you are working on a language model.  
Additionally, [this post](https://discuss.pytorch.org/t/torch-cuda-amp-cannot-speed-up-on-a100/120525/2) discusses a similar issue and provides a profile of the workload.

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