ROCm isn’t really supported on consumer gpus but it does still work on them. At least in my experience with rdna 2 it takes a bit to get it to work, just for some things to not work that well. I think if you where to buy an officially supported gpu the experience would be much better. That’s not to say ROCm is bad I just don’t think it’s friendly or makes much sense for your average at home enthusiast or professional. If you want to just mess around with it very rarely ROCm is probably “fine” but if you actually plan on learning and regularly using Ml/dl an nvidia card with as much vram that you can comfortably afford is your best choice. Answer from Booonishment on reddit.com
Reddit
reddit.com › r/amd › is rocm fine or should i go cuda to learn ai with python?
r/Amd on Reddit: Is ROCm fine or should I go CUDA to learn AI with Python?
February 5, 2023 -
I have an RX580 and planning on buying a mid level RDNA3 GPU or Nvidia equivalent.
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For learning you can just use google colab without even needing a gpu. See how it goes for your needs and uses and go from there.
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ROCm isn’t really supported on consumer gpus but it does still work on them. At least in my experience with rdna 2 it takes a bit to get it to work, just for some things to not work that well. I think if you where to buy an officially supported gpu the experience would be much better. That’s not to say ROCm is bad I just don’t think it’s friendly or makes much sense for your average at home enthusiast or professional. If you want to just mess around with it very rarely ROCm is probably “fine” but if you actually plan on learning and regularly using Ml/dl an nvidia card with as much vram that you can comfortably afford is your best choice.
PyTorch
pytorch.org › blog › pytorch-for-amd-rocm-platform-now-available-as-python-package
PyTorch for AMD ROCm™ Platform now available as Python package – PyTorch
March 24, 2021 - PyTorch on ROCm includes full capability for mixed-precision and large-scale training using AMD’s MIOpen & RCCL libraries. This provides a new option for data scientists, researchers, students, and others in the community to get started with accelerated PyTorch using AMD GPUs.
Videos
15:54
How To Install AMD ROCm, PyTorch, Stable Diffusion & YOLO - 2024 ...
12:03
PyTorch/TensorFlow on AMD: Beginner's Guide to ROCm on Linux - YouTube
08:56
Run ROCm + PyTorch on Windows 11 for LOCAL AI, stable diffusion, ...
15:32
AMD ROCm Pytorch Getting Started Guide - YouTube
r/ROCm on Reddit: AMD ROCm Pytorch Getting Started Guide
r/ROCm on Reddit: AMD ROCm7 + Pytorch 2.10 Huge Performance Gains ...
Mayhemcode
mayhemcode.com › home › ai › rocm vs cuda: which one should you actually use for ai?
ROCm vs CUDA: Which One Should You Actually Use for AI?
May 30, 2026 - But the GPU doesn’t just magically know how to run your Python code. You need a layer of software sitting between your PyTorch or TensorFlow code and the actual GPU hardware. That layer is what CUDA and ROCm are. They’re platforms collections of libraries, compilers, and tools — that let software talk to the GPU. CUDA is NVIDIA’s platform. ROCm is AMD’s.
Medium
medium.com › @guinmoon › building-rocm-7-1-and-pytorch-on-windows-for-unsupported-gpus-my-hands-on-guide-0758d2d2b334
Building ROCm 7.1 and PyTorch on Windows for Unsupported GPUs: My Hands-On Guide | by Artem Savkin | Medium
November 21, 2025 - Ever wanted to squeeze ROCm 7 onto your AMD setup without waiting for official support? Here’s how I did it for my RX 6800 and Radeon 780M — complete with PyTorch and ComfyUI tests.
AMD ROCm
rocm.docs.amd.com › projects › rocm_smi_lib › en › docs-6.2.0 › how-to › use-python.html
Using Python in ROCm SMI — ROCm SMI LIB 7.3.0 Documentation
--setextremum <min/max> <sclk or ... our Python CLI tool (rocm-smi --setextremum max sclk 1500). See example below. $ sudo /opt/rocm/bin/rocm-smi --setextremum max sclk 2100 ============================ ROCm System Management Interface ============================ ******WARNING****** Operating your AMD GPU outside ...
Reddit
reddit.com › r/rocm › rocm feedback for amd
r/ROCm on Reddit: ROCM Feedback for AMD
January 19, 2025 -
Ask: Please share a list of your complaints about ROCM
Give: I will compile a list and send it to AMD to get the bugs fixed / improvements actioned
Context: AMD seems to finally be serious about getting its act together re: ROCM. If you've been following the drama on Twitter the TL;DR is that a research shop called Semi Analysis tore apart ROCM in a widely shared report. This got AMD's CEO Lisa Su to visit Semi Analysis with her top execs. She then tasked one of these execs Anush Elangovan (who was previously founder at nod.ai that got acquired by AMD) to fix ROCM. Drama here:
https://x.com/AnushElangovan/status/1880873827917545824
He seems to be pretty serious about it so now is our chance. I can send him a google doc with all feedback / requests.
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Give more/future comsumer cards ROCm support in Linux. I got two rx 6800 cards to do some extracricular ai study(former CS Student) and figured an 80 class gpu would have compute support. My gpus are ROCm supported in windows(my main OS), but not being able to use WSL cuts me off from Pytorch. IMO ROCm needs to be more dev friendly cause they have alot of catchup to do. Also when I have gotten it to work using workarounds (ZLUDA, compile target technicalities) it just breaks but that could be on my end. Credit where credit is due, they work pretty great for LLM inference in windows on the few supported apps.
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They need to stop releasing updates that drop support for older (RDNA2) GPUs. Also, make WSL2 work on every GPU that has ANY ROCm support. Also, it’s ridiculous that ZLUDA on windows runs inference (stable diffusion) faster than ROCm bare metal on Linux. That just proves the hardware is capable, but it’s being held back by AMD poor software. My experience has been so bad that I’m seriously considering Project Digits and completely forgetting any future AMD GPU purchase.
Reddit
reddit.com › r/rocm › so, should i go nvidia or is amd mature enough at this point for tinkering with ml?
r/ROCm on Reddit: So, should I go Nvidia or is AMD mature enough at this point for tinkering with ML?
December 6, 2025 -
I'm trying to choose between two gpus, either a 5060 ti 16gb or a 9070 xt (which I got a good deal on).
I want to learn and tinker with ML, but everyone is warning me about the state of amd/rocm at the moment, so I thought I should post in this forum to get some actual "war stories".
What are your thoughts on going with amd - was it the right choice or would you chose nvidia if you did it all over?
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It depends what you need. My ollama with openwebui is working out of the box. ComfyUI have like 6commands to run when you have python. I have 7900xtx, i never had nvidia so I can not compare. LM models fine no issue with ollama on windows. LM models on vllm only on linux ComfyUI image generation, no issue on win/linux ComfyUI video generation Linux no big issues, Windows slow as windows use to much gpu VRAM for OS. There are ways to do it but it is not out of the box.
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I developed and trained some reinforcement learning models for Coding Game competitions in 06/2024 with Pytorch on Linux and both Amd (6900xt) and Nvidia (4090) worked equally well out of the box. Same (Python) code executed on both machines, the only difference being in the initial Pytorch installation vevn setup. Edit: I remember now that I was not able to make my amd gpu work with Tensorflow easily (1-2 hours effort), so I switched my project to Pytorch because both gpus worked there out of the box (copy- paste the installation command from the Pytorch homepage and it worked).
GitHub
github.com › ROCm › pyrsmi
GitHub - ROCm/pyrsmi: python package of rocm-smi-lib · GitHub
pyrsmi is a Python package providing system management functionality for AMD GPUs. Version 1.0+ uses the new AMD SMI Library (amdsmi), replacing the deprecated rocm-smi-lib.
Starred by 25 users
Forked by 10 users
Languages Python
AMD ROCm
rocm.docs.amd.com › projects › hip-python › en › latest
HIP Python - ROCm Documentation - AMD
June 23, 2023 - HIP Python provides low-level Cython and Python® bindings for the HIP runtime, HIPRTC, multiple math libraries and the communication library RCCL, and further a CUDA® Python Interoperability layer that aims to simplify the porting of CUDA Python Python and Cython programs. ... This documentation has been generated based on ROCm™ version 5.7.1.
Reddit
reddit.com › r/machinelearning › [d] why is cuda so much faster than rocm?
r/MachineLearning on Reddit: [D] Why is CUDA so much faster than ROCm?
September 6, 2024 -
Usually people respond with "Because NVIDIA had more time and more money". However, why cant AMD catch up? What are the exact things that make optimizing ROCm so hard??
It would be helpful if you could point to some resources or if your answer would be as detailed as possible regarding the implementation of specific kernels and structures and how CUDA calls are exactly made and optimized from Triton or XLA. Thx :)
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Because every machine learning library is written with cuda in mind. This means Nvidia's hardware is usually supported iut of the box. Take a look at flash attention. It was developed to optimize transformers by re-writing tge attention operations to utilize the gpu more efficiently. This means writing gpu kernels that are device-specific. Can you guess which device and kernel language they optimized? The answer is A100 and cuda. Now someone has to rewrite the same algorithm in rocm running on MI250. This may or may not happen depending on a lot of factors.
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Egg vs. chicken problem. "Nobody" uses AMD for ML, so AMD does not put money and manpower to develop good libraries for ML in AMD. Because there are no good libraries for using AMD in ML, nobody uses AMD for ML. It is a bit more nuanced but it boils down to that. But things are to change. Finnish LUMI-G supercomputer (5th in computing power in the world IIRC) is build with AMD hardware and AMD just bought out Finnish AI company Silo AI. I think that now AMD is going to properly seed fund the use of AMD in ML and get drivers situation better.
Hacker News
news.ycombinator.com › item
Taking on CUDA with ROCm: 'One Step After Another' | Hacker News
April 23, 2026 - It has been a bit of a nightmare and had to package like 30+ deps and their heavily customized LLVM, but got the runtime to build this morning finally · Things are looking bright for high security workloads on AMD hardware due to them working fully in the open however much of a mess it may be
GitHub
gist.github.com › damico › 484f7b0a148a0c5f707054cf9c0a0533
Script for testing PyTorch support with AMD GPUs using ROCM · GitHub
You can run PyTorch code inside of: (amd) mruserbox@guru-X99:/media/10TB_HHD/_AMD$ rocm-smi ======================= ROCm System Management Interface ======================= ================================= Concise Info ================================= GPU Temp (DieEdge) AvgPwr SCLK MCLK Fan Perf PwrCap VRAM% GPU% 0 56.0c 13.0W 500Mhz 96Mhz 0% auto 215.0W 0% 0% ================================================================================ ============================= End of ROCm SMI Log ============================== ... I already found the problem brother, i had to add my user to vide and render group, i did the follow · sudo usermod -a -G video mruserbox sudo usermod -a -G render mruserbox ... (amd) mruserbox@guru-X99:/media/10TB_HHD/_AMD$ python test.py Checking ROCM support...
PyTorch Forums
discuss.pytorch.org › t › current-state-of-pytorch-rocm › 223926
Current state of PyTorch + ROCm - PyTorch Forums
November 11, 2025 - With ROCm 7.0 just released (and probably soon supported by PyTorch), and new interesting AMD Radeon AI PRO R9700 AI TOP 32 GB VRAM on the market – which seems like a very tempting proposition – I’m curious how far ROCm has and PyTorch has come for a smooth inference and training.
AMD ROCm
rocm.docs.amd.com › projects › rocm_smi_lib › en › latest › how-to › use-python.html
Using ROCm SMI with Python — ROCm SMI LIB 7.8.0 Documentation
To use ROCm SMI, you must have ROCm SMI library (librocm_smi64) installed and should have at least one AMD GPU with the ROCm driver installed.
Scimus
thescimus.com › rocm vs cuda: a practical comparison for ai developers
ROCm vs CUDA: A Practical Comparison for AI Developers - Scimus
August 12, 2024 - It provides the tools and libraries necessary for running high-performance applications on AMD GPUs. ROCm’s open-source nature allows for greater flexibility and customization, making it a strong contender for those who need more control over their computing environments, despite having less market penetration and facing some challenges in software stability and development resources. Like CUDA, ROCm does not require a new programming language, but works with established ones such as C, C++, and Python.
AMD
amd.com › https://www.amd.com/en.html › products › rocm
AMD ROCm™ Software
1 month ago - AMD partners with Hugging Face, enabling thousands of models. ROCm includes day-zero support on PyTorch 2.0. ROCm enables PyTorch AI at scale, with a 1 trillion parameter model successfully getting trained on the Frontier system.
Linux Containers Forum
discuss.linuxcontainers.org › tutorials
ROCm and PyTorch on AMD APU or GPU (AI) - Tutorials - Linux Containers Forum
April 19, 2024 - AMD ROCm is officially supported only on a few consumer-grade GPUs, mainly Radeon RX 7900 GRE and above. But ROCm consists of many things: compilers, runtime libraries, Ai-related libraries, etc.
Medium
medium.com › digitalocean-ai-digest › how-ai-models-run-on-gpus-cuda-vs-rocm-d67569100953
How AI Models Run on GPUs (CUDA vs. ROCm) | by DigitalOcean | DigitalOcean AI Digest | Medium
February 2, 2026 - Examples include cuBLAS, cuDNN, and cuSOLVER for NVIDIA, as well as rocBLAS, MIOpen, and rocSOLVER for AMD. Layer 5 — Frameworks: This layer abstracts everything and makes it simpler to develop your own AI applications and just work in Python (or other language, depending on your framework).
Medium
medium.com › @damngoodtech › amd-rocm-pytorch-and-ai-on-ubuntu-the-rules-of-the-jungle-24a7ab280b17
AMD, ROCM, PyTorch, and AI on Ubuntu: The Rules of the Jungle | by Jordan Hewitt | Medium
October 17, 2023 - In short, Nvidia uses uses CUDA, and AMD uses ROCM.
AMD ROCm
rocm.docs.amd.com › en › latest › how-to › programming_guide.html
Programming guide - ROCm Documentation - AMD
February 6, 2026 - ROCm supports various programming languages and frameworks to help developers access the power of AMD GPUs. The natively supported programming languages are HIP (Heterogeneous-Compute Interface for Portability) and OpenCL, but HIP bindings are available for Python and Fortran.