NVIDIA GeForce RTX 5090

username: nafe_alhmdan
cooked: <p>C:\Users\USER\Desktop\RVC1006Nvidia&gt;runtime\python.exe infer-web.py --pycmd runtime\python.exe --port 7897<br>
C:\Users\USER\Desktop\RVC1006Nvidia\runtime\lib\site-packages\torch\cuda_<em>init</em>_.py:173: UserWarning:<br>
NVIDIA GeForce RTX 5090 with CUDA capability sm_120 is not compatible with the current PyTorch installation.<br>
The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_61 sm_70 sm_75 sm_80 sm_86 sm_90 compute_37.<br>
If you want to use the NVIDIA GeForce RTX 5090 GPU with PyTorch, please check the instructions at <a href="https://pytorch.org/get-started/locally/" class="inline-onebox" rel="noopener nofollow ugc">Start Locally | PyTorch</a></p>
<p>warnings.warn(incompatible_device_warn.format(device_name, capability, " ".join(arch_list), device_name))<br>
2025-04-10 18:55:22 | INFO | configs.config | Found GPU NVIDIA GeForce RTX 5090<br>
is_half:True, device:cuda:0</p>

username: ptrblck
cooked: <p>Install the latest nightly binaries with CUDA 12.8 and it will work as the Blackwell support requires CUDA &gt;= 12.8.</p>

username: nafe_alhmdan
cooked: <p>Python 3.12.8 (tags/v3.12.8:2dc476b, Dec  3 2024, 19:30:04) [MSC v.1942 64 bit (AMD64)] on win32<br>
Type “help”, “copyright”, “credits” or “license” for more information.</p>
<blockquote>
<blockquote>
<blockquote>
<p>import torch<br>
print(torch.<strong>version</strong>)<br>
2.8.0.dev20250408+cu128</p>
</blockquote>
</blockquote>
</blockquote>

username: nafe_alhmdan
cooked: <p>It doesn’t work<br>
Same error</p>

username: ptrblck
cooked: <p>The nightly binary itself works as confirmed e.g. <a href="https://discuss.pytorch.org/t/pytorch-support-for-sm120/216099/41">here</a> so I don’t know what the issue in your setup is.<br>
The user in the linked post also claimed to have installed the right binary and later claimed:</p>
<blockquote>
<p>Upgrading to the latest nightly (with <code>sm_120</code> support) resolved that</p>
</blockquote>
<p>so I also don’t fully understand what happened before.</p>

username: nafe_alhmdan
cooked: <p>C:\Users\USER\Desktop\RVC1006Nvidia&gt;runtime\python.exe infer-web.py --pycmd runtime\python.exe --port 7897<br>
C:\Users\USER\Desktop\RVC1006Nvidia\runtime\lib\site-packages\torch\cuda_<em>init</em>_.py:173: UserWarning:<br>
NVIDIA GeForce RTX 5090 with CUDA capability sm_120 is not compatible with the current PyTorch installation.<br>
The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_61 sm_70 sm_75 sm_80 sm_86 sm_90 compute_37.<br>
If you want to use the NVIDIA GeForce RTX 5090 GPU with PyTorch, please check the instructions at <a href="https://pytorch.org/get-started/locally/" class="inline-onebox" rel="noopener nofollow ugc">Start Locally | PyTorch</a></p>
<p>warnings.warn(incompatible_device_warn.format(device_name, capability, " ".join(arch_list), device_name))<br>
2025-04-10 20:05:22 | INFO | configs.config | Found GPU NVIDIA GeForce RTX 5090<br>
is_half:True, device:cuda:0<br>
2025-04-10 20:05:24 | INFO | <strong>main</strong> | Use Language: en_US<br>
Running on local URL:  <a href="http://0.0.0.0:7897" rel="noopener nofollow ugc">http://0.0.0.0:7897</a><br>
2025-04-10 20:05:33 | INFO | infer.modules.vc.modules | Get sid: kikiV1.pth<br>
2025-04-10 20:05:33 | INFO | infer.modules.vc.modules | Loading: assets/weights/kikiV1.pth<br>
2025-04-10 20:05:34 | INFO | infer.modules.vc.modules | Select index: logs\kikiV1.index<br>
2025-04-10 20:05:44 | INFO | infer.modules.vc.pipeline | Loading rmvpe model,assets/rmvpe/rmvpe.pt</p>
<p>C:\Users\USER\Desktop\RVC1006Nvidia&gt;pause<br>
Press any key to continue . . .<br>
The problem could be with the software or the 5090 card.<br>
Because when I change the card to a 4090, it works.<br>
Is there a solution? I’ve tried everything.</p>

username: ptrblck
cooked: <aside class="quote no-group" data-username="nafe_alhmdan" data-post="6" data-topic="218954">
<div class="title">
<div class="quote-controls"></div>
<img alt="" width="24" height="24" src="https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/nafe_alhmdan/48/75984_2.png" class="avatar"> nafe_alhmdan:</div>
<blockquote>
<p>The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_61 sm_70 sm_75 sm_80 sm_86 sm_90 compute_37.</p>
</blockquote>
</aside>
<p>You are still using older PyTorch builds so make sure a single binary built with CUDA 12.8 is installed.</p>

username: OkYes_Anap
cooked: <p>Same issue<br>
UserWarning:<br>
NVIDIA GeForce RTX 5090 Laptop GPU with CUDA capability sm_120 is not compatible with the current PyTorch installation.<br>
The current PyTorch install supports CUDA capabilities sm_50 sm_60 sm_61 sm_70 sm_75 sm_80 sm_86 sm_90.<br>
If you want to use the NVIDIA GeForce RTX 5090 Laptop GPU GPU with PyTorch, please check the instructions at <a href="https://pytorch.org/get-started/locally/" rel="noopener nofollow ugc">https://pytorch.org/get-started/locally/</a></p>
<p>pip3 list<br>
Package           Version</p>
<hr>
<p>einops            0.8.1<br>
filelock          3.18.0<br>
flash_attn        2.7.4.post1<br>
fsspec            2025.5.1<br>
Jinja2            3.1.6<br>
MarkupSafe        3.0.2<br>
mpmath            1.3.0<br>
networkx          3.5<br>
numpy             2.1.2<br>
pillow            11.0.0<br>
pip               25.0.1<br>
setuptools        80.9.0<br>
sympy             1.14.0<br>
torch             2.7.1+cu128<br>
torchaudio        2.7.1+cu128<br>
torchvision       0.22.1+cu128<br>
typing_extensions 4.14.0</p>
<p>python --version<br>
Python 3.12.10</p>

username: ptrblck
cooked: <p>Dame as before: make sure a single and the correct PyTorch binary is used: <a href="https://discuss.pytorch.org/t/nvidia-geforce-rtx-5090/218954/7" class="inline-onebox">NVIDIA GeForce RTX 5090 - #7 by ptrblck</a></p>

username: OkYes_Anap
cooked: <p>How to do this? I already showed you that I have Python and Torch installed. Well, okay, I will attach a screenshot.<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/2/4/2480413f08600f712a95807f86a3a21075104122.png" data-download-href="https://discuss.pytorch.org/uploads/default/2480413f08600f712a95807f86a3a21075104122" title="image"><img src="https://discuss.pytorch.org/uploads/default/original/3X/2/4/2480413f08600f712a95807f86a3a21075104122.png" alt="image" data-base62-sha1="5cTYmZCcmdj6Iadn6Cdu6Pg7koq" width="450" height="500" data-dominant-color="191515"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">image</span><span class="informations">515×571 9.1 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p>

username: ptrblck
cooked: <p>Yes, <code>pip list</code> shows the right version but does not account for other binaries found in e.g. the base env.</p>