Pytorch Support for Apple Silicon: User Experiences
Published:Dec 27, 2025 10:18
•1 min read
•r/deeplearning
Analysis
This Reddit post highlights a common dilemma for deep learning practitioners: balancing personal preference for macOS with the performance needs of deep learning tasks. The user is specifically asking about the real-world performance of PyTorch on Apple Silicon (M-series) GPUs using the MPS backend. This is a relevant question, as the performance can vary significantly depending on the model, dataset, and optimization techniques used. The responses to this post would likely provide valuable anecdotal evidence and benchmarks, helping the user make an informed decision about their hardware purchase. The post underscores the growing importance of Apple Silicon in the deep learning ecosystem, even though it's still considered a relatively new platform compared to NVIDIA GPUs.
Key Takeaways
- •Apple Silicon (M-series) GPUs are gaining traction in deep learning.
- •PyTorch support for MPS is available, but performance varies.
- •User experiences and benchmarks are crucial for informed hardware decisions.
Reference
“I've heard that pytorch has support for M-Series GPUs via mps but was curious what the performance is like for people have experience with this?”