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RUNLOCALAI · v38
Errors / Driver issues / CUDA driver version is insufficient for CUDA runtime version
Driver issues

CUDA driver version is insufficient for CUDA runtime version

CUDA driver version is insufficient for CUDA runtime version
By Fredoline Eruo · Last verified Jun 12, 2026

Cause

Your installed PyTorch (or other CUDA-using library) was compiled against a newer CUDA toolkit than your NVIDIA driver supports. Each driver version has a maximum CUDA runtime it can use.

Solution

Check your current driver and the maximum CUDA it supports:

nvidia-smi

The "CUDA Version" shown is the maximum your driver supports, NOT the version installed.

Two paths:

1. Update the NVIDIA driver (preferred). Get the latest from nvidia.com/Download or use your distro's package manager. After install, reboot. nvidia-smi should show a higher CUDA version.

2. Downgrade your library to match your driver. For PyTorch:

# Driver supports CUDA 11.8, install matching PyTorch
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu118

On Windows with WSL2: Update your Windows NVIDIA driver, NOT the Linux one. WSL2 inherits the host's driver.

Related errors

  • PyTorch CUDA error: driver version is insufficient for CUDA runtime
  • WSL2: nvidia-smi works but PyTorch sees no CUDA / libcuda.so missing
  • WSL2 GPU not detected — nvidia-smi missing or empty
  • nvidia-smi: command not found
  • Docker container can't see GPU — nvidia-container-toolkit missing

Did this fix it?

If your case was different, email Contact support with what you saw and we'll update the page. If it worked but took different commands on your platform, we want to know that too.