Question about setting up cuDNN BI 5.9.9.83 CPAI 2.9.5 + NVIDIA GeForce RTX 4060 Ti #347
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stevendennisha
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Hello everyone. I am having a little trouble knowing the correct way to install cuDNN. Right now I show this
C:\Users\Administrator>nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2023 NVIDIA Corporation
Built on Tue_Jun_13_19:42:34_Pacific_Daylight_Time_2023
Cuda compilation tools, release 12.2, V12.2.91
Build cuda_12.2.r12.2/compiler.32965470_0
BI Info
Version: Release 5.9.9.83 x64 (9/23/2025)
OS: Windows 11 Pro
CPU,GPU: Intel(R) Core(TM) i7-14700K [6%,12%]
RAM: 4.01GB/127.7GB
CPAI info
Server version: 2.9.5
System: Windows
Operating System: Windows (Windows 11 24H2)
CPUs: Intel(R) Core(TM) i7-14700K (Intel)
1 CPU x 20 cores. 28 logical processors (x64)
GPU (Primary): NVIDIA GeForce RTX 4060 Ti (8 GiB) (NVIDIA)
Driver: 581.29, CUDA: 12.2.91 (up to: 13.0), Compute: 8.9, cuDNN:
System RAM: 128 GiB
Platform: Windows
BuildConfig: Release
Execution Env: Native
Runtime Env: Production
Runtimes installed:
.NET runtime: 9.0.9
.NET SDK: 9.0.305
Default Python: Not found
Go: Not found
NodeJS: Not found
Rust: Not found
Video adapter info:
Microsoft Remote Display Adapter:
Driver Version 10.0.26100.5074
Video Processor
NVIDIA GeForce RTX 4060 Ti:
Driver Version 32.0.15.8129
Video Processor NVIDIA GeForce RTX 4060 Ti
System GPU info:
GPU 3D Usage 2%
GPU RAM Usage 1.2 GiB
Global Environment variables:
CPAI_APPROOTPATH =
CPAI_PORT = 32168
When I try to install the ALRP module I see this in the logs
2025-09-24 17:26:21: CUDA Present...Yes (CUDA 12.2, No cuDNN found, CUDA Toolkit: true)
I was concerned the bat file here might install the older version not compatible with CUDA 12.2
https://www.digitalocean.com/community/tutorials/install-cuda-cudnn-for-gpu
There are instructions that note
Step 4: Download and Install cuDNN on Windows
Register as an NVIDIA Developer: To gain access, you need to set up an account on the NVIDIA Developer website to access cuDNN downloads.
Check Compatibility: It’s important to ensure the cuDNN version aligns with your installed CUDA version. If you have, for example, CUDA 11.8, search specifically for cuDNN 8 builds that indicate they support CUDA 11.8.
QUESTIONS
Thanks so much for any help you can provide me
Steve
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