How Do I use Pytorch with RTX 5060 Ti

Jeff_H: <p>Hello I’m new here. Can someone help me with this? I can’t find a compatible pytorch for my RTX 5060 Ti. Here’s my system and it’s issues. I’ve tried the nightly version and it still won’t work.</p>
<p>"Python 3.10.11</p>
<p>Checking PyTorch…<br>
PyTorch Version: 2.8.0.dev20250618+cu128</p>
<p>Checking GPU and Driver…<br>
Thu Jun 19 16:38:25 2025<br>
±----------------------------------------------------------------------------------------+<br>
| NVIDIA-SMI 576.80                 Driver Version: 576.80         CUDA Version: 12.9</p>
<p>Checking CUDA Toolkit…<br>
nvcc: NVIDIA (R) Cuda compiler driver<br>
Copyright (c) 2005-2024 NVIDIA Corporation<br>
Built on Fri_Jun_14_16:44:19_Pacific_Daylight_Time_2024<br>
Cuda compilation tools, release 12.6, V12.6.20<br>
Build cuda_12.6.r12.6/compiler.34431801_0</p>
<p>Checking PyTorch CUDA and GPU Compatibility…<br>
CUDA Available: Yes<br>
PyTorch CUDA Version: 12.8<br>
GPU Compute Capability: (12, 0)<br>
GPU Compatibility: Not supported by PyTorch 2.8.0.dev20250618+cu128. Try a nightly build: <a href="https://pytorch.org/get-started/locally/" rel="noopener nofollow ugc">https://pytorch.org/get-started/locally/</a>"</p>

ptrblck: <p>You’ve installed the right binary. Could you explain where this error message comes from as I haven’t seen it before?</p>
<aside class="quote no-group" data-username="Jeff_H" data-post="1" data-topic="220926">
<div class="title">
<div class="quote-controls"></div>
<img alt="" width="24" height="24" src="https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/jeff_h/48/77338_2.png" class="avatar"> Jeff_H:</div>
<blockquote>
<p>GPU Compatibility: Not supported by PyTorch 2.8.0.dev20250618+cu128. Try a nightly build: <a href="https://pytorch.org/get-started/locally/">https://pytorch.org/get-started/locally/</a>"</p>
</blockquote>
</aside>

Jeff_H: <p>I get the error when I install the pytorch nightly build or the stable version. I’m trying to run FramePack with GPU acceleration, and I get this error no matter what pytorch version I use. I have a batch file that checks for compatibility between PyTorch CUDA and GPU. When I run it I get the error. Every time.</p>

ptrblck: <p>I would recommend trying to install the latest stable or nightly PyTorch binary with CUDA 12.8 standalone without any 3rd party libs which seem to raise the error message.<br>
Refer to e.g. <a href="https://discuss.pytorch.org/t/pytorch-support-for-sm120/216099/54">this post</a> for a smoke test.</p>

Jeff_H: <p>Thank you. I will try that and let you know the results.</p>

Jeff_H: <aside class="quote no-group" data-username="ptrblck" data-post="4" data-topic="220926">
<div class="title">
<div class="quote-controls"></div>
<img alt="" width="24" height="24" src="https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/ptrblck/48/1823_2.png" class="avatar"> ptrblck:</div>
<blockquote>
<p>I would recommend trying to install the latest stable or nightly PyTorch binary with CUDA 12.8 standalone without any 3rd party libs which seem to raise the error message.</p>
</blockquote>
</aside>
<p>I switched to:<br>
nvcc: NVIDIA (R) Cuda compiler driver<br>
Copyright (c) 2005-2025 NVIDIA Corporation<br>
Built on Fri_Feb_21_20:42:46_Pacific_Standard_Time_2025<br>
Cuda compilation tools, release 12.8, V12.8.93<br>
Build cuda_12.8.r12.8/compiler.35583870_0</p>
<p>Checking PyTorch CUDA and GPU Compatibility…<br>
CUDA Available: Yes<br>
PyTorch CUDA Version: 12.8<br>
GPU Compute Capability: (12, 0)<br>
GPU Compatibility: Not supported by PyTorch 2.8.0.dev20250618+cu128. Try a nightly build: <a href="https://pytorch.org/get-started/locally/" rel="noopener nofollow ugc">https://pytorch.org/get-started/locally/</a></p>
<p>and I get the same error</p>

ptrblck: <p>Your locally installed CUDA toolkit won’t be used as the binaries ship with their own CUDA runtime dependencies. I would still recommend executing the smoke test I’ve linked before since you are still using 3rd party libs raising unknown error messages.</p>

RobinDong: <p>For RTX 50XX series, I just install CUDA 12.8 and then</p>
<pre><code class="lang-auto">pip install --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/cu128
</code></pre>

Programer_Salar: <p>yaa, its work, there is no issue</p>

Roosri_test: <p>This works for me<br>
MSI RTX 5090 TI</p>

Jack_Baqir: <ol>
<li>Install with CUDA:</li>
</ol>
<p>bash</p>
<p>CopyEdit</p>
<pre><code class="lang-auto">pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121  
</code></pre>
<ol start="2">
<li>Verify GPU:</li>
</ol>
<p>python</p>
<p>CopyEdit</p>
<pre><code class="lang-auto">import torch  
print(torch.cuda.is_available())  
print(torch.cuda.get_device_name(0))  
</code></pre>

ptrblck: <p>This won’t work since you are explicitly installing an old PyTorch binary with CUDA 12.1 while CUDA 12.8+ is required.</p>

mia2: <p>May I ask if you have solved this problem? I am experiencing the same issue as you and still haven’t resolved it. I need help.</p>

ptrblck: <p>Install any of our PyTorch binaries built with CUDA 12.8+ using the install command from our <a href="https://pytorch.org/get-started/locally/">install matrix</a>. E.g. a simple <code>pip install torch</code> will install <code>torch==2.8.0+cu128</code> on Linux x86 systems supporting Blackwell GPUs:</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/f/d/fd9fa952974a2a13571187431cae65603a17c794.png" data-download-href="https://discuss.pytorch.org/uploads/default/fd9fa952974a2a13571187431cae65603a17c794" title="image"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/f/d/fd9fa952974a2a13571187431cae65603a17c794_2_690x285.png" alt="image" data-base62-sha1="AbES7VGCSut4K6TYW3pDBysdZs0" width="690" height="285" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/f/d/fd9fa952974a2a13571187431cae65603a17c794_2_690x285.png, https://discuss.pytorch.org/uploads/default/original/3X/f/d/fd9fa952974a2a13571187431cae65603a17c794.png 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/f/d/fd9fa952974a2a13571187431cae65603a17c794.png 2x" data-dominant-color="F5DFDC"><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">988×409 41.4 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>
<p>EDIT: From your cross-post:</p>
<blockquote>
<p>My Python version is 3.8.10 and CUDA is 12.8. Using the official pip and Nightly commands to download PyTorch 12.8 shows that this version cannot be found</p>
</blockquote>
<p>This is expected as Python &gt;= 3.9 is needed as described on the install page:</p>
<blockquote>
<p><strong>NOTE:</strong> Latest Stable PyTorch requires Python 3.9 or later. Latest Preview (Nightly) PyTorch requires Python 3.10 or later.</p>
</blockquote>
<p>so update your Python version and rerun the install command. <a class="mention" href="/u/mia2">@mia2</a></p>

cfoster1111: <p>This is what worked for me, …</p>
<h1><a name="p-476270-rtx-5060-ti-16gb-setup-1" class="anchor" href="#p-476270-rtx-5060-ti-16gb-setup-1"></a>RTX 5060 Ti 16GB Setup</h1>
<h2><a name="p-476270-hardware-requirements-2" class="anchor" href="#p-476270-hardware-requirements-2"></a>Hardware Requirements</h2>
<ul>
<li><strong>GPU</strong>: NVIDIA GeForce RTX 5060 Ti 16GB</li>
<li><strong>Architecture</strong>: Blackwell (SM 12.0)</li>
<li><strong>Driver</strong>: NVIDIA 580.82.10+</li>
<li><strong>OS</strong>: Windows 11 with WSL2</li>
</ul>
<h2><a name="p-476270-docker-container-stack-3" class="anchor" href="#p-476270-docker-container-stack-3"></a>Docker Container Stack</h2>
<ul>
<li><strong>Base Image</strong>: pytorch-tensorflow-gpu:latest</li>
<li><strong>Ubuntu</strong>: 24.04 LTS</li>
<li><strong>Python</strong>: 3.11.14</li>
<li><strong>CUDA</strong>: 12.8.1</li>
<li><strong>cuDNN</strong>: 9.x</li>
</ul>
<h2><a name="p-476270-pytorch-stack-4" class="anchor" href="#p-476270-pytorch-stack-4"></a>PyTorch Stack</h2>
<ul>
<li><strong>PyTorch</strong>: 2.10.0.dev20251017+cu128 (nightly)</li>
<li><strong>CUDA Support</strong>: Yes (for 1 GPUs)</li>
<li><strong>Compute Capability</strong>: 12.0 (Blackwell)</li>
</ul>
<h2><a name="p-476270-tensorflow-stack-5" class="anchor" href="#p-476270-tensorflow-stack-5"></a>TensorFlow Stack</h2>
<ul>
<li><strong>TensorFlow</strong>: 2.21.0-dev20251017</li>
<li><strong>CUDA Runtime</strong>: 12.8</li>
<li><strong>JIT Compilation</strong>: Enabled for Blackwell</li>
</ul>
<h2><a name="p-476270-aiml-libraries-6" class="anchor" href="#p-476270-aiml-libraries-6"></a>AI/ML Libraries</h2>
<ul>
<li><strong>diffusers</strong>: 0.35.2</li>
<li><strong>transformers</strong>: 4.57.1</li>
<li><strong>accelerate</strong>: Latest</li>
<li><strong>huggingface-hub</strong>: 0.35.3</li>
<li><strong>safetensors</strong>: 0.6.2</li>
</ul>
<h2><a name="p-476270-installation-order-7" class="anchor" href="#p-476270-installation-order-7"></a>Installation Order</h2>
<ol>
<li>Docker Desktop 4.28+ (WSL2 backend)</li>
<li>NVIDIA Container Toolkit</li>
<li>Clone: <a href="https://github.com/dconsorte/pytorch-tensorflow-gpu.git" class="inline-onebox" rel="noopener nofollow ugc">GitHub - dconsorte/pytorch-tensorflow-gpu: RTX 5090 &amp; RTX 5060 Docker container with PyTorch + TensorFlow. First fully-tested Blackwell GPU support for ML/AI. CUDA 12.8, Python 3.11, Ubuntu 24.04. Works with RTX 50-series (5090/5080/5070/5060) and RTX 40-series.</a></li>
<li>Build: <code>./build.sh --no-cache</code></li>
<li>Install: <code>pip install diffusers transformers accelerate</code></li>
</ol>
<h2><a name="p-476270-verification-commands-8" class="anchor" href="#p-476270-verification-commands-8"></a>Verification Commands</h2>
<pre data-code-wrap="bash"><code class="lang-bash">nvidia-smi
python -c "import torch; print(torch.cuda.is_available())"
python -c "from diffusers import StableDiffusionPipeline; print('Ready')"
</code></pre>
<h2><a name="p-476270-container-commands-9" class="anchor" href="#p-476270-container-commands-9"></a>Container Commands</h2>
<pre data-code-wrap="bash"><code class="lang-bash"># Start container
docker run --gpus all -v ~/ai_training_env:/workspace -it rtx5060ti-ready

# Test GPU
python -c "import torch; print('GPU:', torch.cuda.get_device_name(0))"
</code></pre>
<h2><a name="p-476270-performance-specs-10" class="anchor" href="#p-476270-performance-specs-10"></a>Performance Specs</h2>
<ul>
<li><strong>GPU Memory</strong>: 16,311 MiB total</li>
<li><strong>CUDA Cores</strong>: Blackwell architecture</li>
<li><strong>Memory Bandwidth</strong>: Optimized for 16GB VRAM</li>
<li><strong>Mixed Precision</strong>: FP16 support enabled</li>
</ul>
<h2><a name="p-476270-httpsgithubcomdconsortepytorch-tensorflow-gpugit-11" class="anchor" href="#p-476270-httpsgithubcomdconsortepytorch-tensorflow-gpugit-11"></a><a href="https://github.com/dconsorte/pytorch-tensorflow-gpu.git" class="inline-onebox" rel="noopener nofollow ugc">GitHub - dconsorte/pytorch-tensorflow-gpu: RTX 5090 &amp; RTX 5060 Docker container with PyTorch + TensorFlow. First fully-tested Blackwell GPU support for ML/AI. CUDA 12.8, Python 3.11, Ubuntu 24.04. Works with RTX 50-series (5090/5080/5070/5060) and RTX 40-series.</a></h2>
<ul>
<li><strong>Docker Image</strong>: rtx5060ti-ready (41.8GB)</li>
</ul>