CUDA Toolkit 10.2
eol- Released
- 2019 (exact month unverified — sources disagree on whether this refers to the original GA or a later 10.2.89 update)
- Minimum driver — Linux
- 440.33
- Minimum driver — Windows
- 441.22
- Supported GPU architectures
- Compute capability (sm_XX)
- Commercial GPU names
- Compatible cuDNN
WSL2 & Docker
WSL2: CUDA-on-WSL2 GPU support didn't exist yet when CUDA 10.2 shipped -- NVIDIA introduced it circa 2020, requiring a Windows driver from the R495 branch or later (docs.nvidia.com/cuda/wsl-user-guide). Using CUDA under WSL2 today means installing a current CUDA Toolkit release, not this one. Docker: independent of WSL2 -- a host with a driver >= the Linux minimum above and the NVIDIA Container Toolkit installed can still run this CUDA version inside a container; the CUDA Toolkit itself only needs to be present in the container image, not on the host.
Architecture support corrected 2026-09 against NVIDIA's archived release notes (10.2, 11.0, 12.0, 13.0): Kepler sm_30/sm_32 were dropped in CUDA 11.0 (deprecated since 10.2), Kepler sm_35/sm_37 were removed in 12.0, and Maxwell/Pascal/Volta were removed in 13.0 (still supported, as deprecated, throughout 12.x). Verified 2026-08 against NVIDIA's CUDA Toolkit release notes (Table 3) for driver minimums. Predates Ampere (added in CUDA 11.0). Added to fix a dead cross-link: PyTorch 1.13.0's page listed this version as a supported CUDA build before this entry existed. computeCapabilities added 2026-08, cross-referenced against developer.nvidia.com/cuda-gpus and the CUDA C++ Programming Guide's compute-capabilities appendix; minor SKU-specific steppings (e.g. 8.7 for Jetson Orin, 12.1 for specific Blackwell SKUs) are folded into the primary value shown, matching this site's existing cuDNN '9.x'-style bucketing rather than listing every sub-variant.