cuda 13.0 release overview

cuda 13.0 was released in august 2025 with significant architectural changes and unified arm platform support.

overview

cuda 13.0 introduces:

• unified arm platform installation
• blackwell gpu support
• architectural deprecations (maxwell, pascal, volta)
• fatbin compression switch from lz4 to zstd
• shared memory register spilling

platform changes

unified arm support

cuda 13.0 consolidates arm support across platforms:

• single installer for all arm architectures
• arm64-sbsa unified support
• grace hopper (gh200) optimizations
• jetson orin excluded from initial release

dropped architectures

removed support for:

• maxwell (gtx 750, gtx 900 series) - compute 5.x
• pascal (gtx 1000 series) - compute 6.x
• volta (titan v, quadro gv100) - compute 7.0

nvidia states these architectures are “feature-complete with no further enhancements planned.”

new features

compiler improvements

• llvm clang 20 support
• gcc 15 support
• compile time advisor (ctadvisor) tool
• 32-bit vector type alignment for blackwell

performance enhancements

• register spilling to shared memory
• zstd fatbin compression (smaller binaries)
• improved cuda graph performance
• enhanced error reporting for cuda apis

api additions

// new host memory support
cuMemCreate()  // with host support
cudaMallocAsync()  // host allocation support

driver requirements

minimum driver: r580 series (580.65.06+)

# verify driver version
nvidia-smi | grep "Driver Version"
# must show 580.xx or higher

distribution support

newly supported

• red hat enterprise linux 10/9.6
• debian 12.10
• fedora 42
• rocky linux 9.6/10.0
• ubuntu 24.04 lts
• ubuntu 22.04 lts (continued)

not supported

• ubuntu 25.04 (non-lts)
• ubuntu 25.10 (non-lts)
• ubuntu 23.10 (non-lts, eol)

note: nvidia typically only supports ubuntu lts releases. debian 12.10 is supported despite being a point release.

dropped

• ubuntu 20.04 lts
• older rhel/centos versions

migration guide

checking gpu compatibility

# list gpu compute capability
nvidia-smi --query-gpu=name,compute_cap --format=csv

# supported architectures (compute 7.5+):
# - turing (rtx 20xx)
# - ampere (rtx 30xx)
# - ada lovelace (rtx 40xx)
# - hopper (h100)
# - blackwell (b100/b200)

code migration

1. vector type alignment

   // old (may cause issues on blackwell)
   struct float4 { float x, y, z, w; };
   
   // cuda 13.0 (32-bit aligned)
   __align__(32) struct float4 { float x, y, z, w; };

2. deprecated apis

   • multi-device launch apis removed
   • legacy vector types deprecated
   • nvprof and nvidia visual profiler removed

pytorch compatibility

pytorch cuda 13.0 support status (august 2025):

• tracking issue: pytorch#159779
• release engineering evaluating build complexity
• potential removal of cuda 12.x builds to accommodate

installation

docker (recommended)

# cuda 13.0 base image (when available)
docker pull nvidia/cuda:13.0-base-ubuntu24.04

# runtime test
docker run --rm --gpus all nvidia/cuda:13.0-base-ubuntu24.04 nvidia-smi

native installation

# download cuda 13.0
wget https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64

# install driver first (if needed)
sudo apt install nvidia-driver-580

# install cuda toolkit
sudo sh cuda_13.0_linux.run --toolkit --silent

jax with cuda 13.0

warning: as of august 2025, the jax-cuda13-plugin package may have version conflicts:

# this currently fails with dependency resolution issues
uv pip install --prerelease=allow "jax[cuda13]>=0.7.0"
# Error: no version of jax-cuda13-plugin[with-cuda]==0.7.0

the cuda13 extras are defined in jax’s setup.py but the corresponding plugin packages may not be published yet. monitor jax releases for updates.

# when available, install with:
uv pip install --prerelease=allow "jax[cuda13]>=0.7.0"

# or for local cuda installation
uv pip install --prerelease=allow "jax[cuda13-local]>=0.7.0"

# verify installation
uv run python -c "import jax; print(jax.devices())"

performance considerations

fatbin compression

cuda 13.0 switches from lz4 to zstd:

• ~20% smaller fatbin files
• slightly slower initial load
• better for distribution/containers

shared memory spilling

new feature allows register spillage to shared memory:

• reduces local memory pressure
• improves kernel occupancy
• automatic optimization

framework support

update: jax has added cuda 13.0 support in recent releases.

current supported cuda versions (august 2025):

• pytorch: cuda 11.8, 12.1, 12.4 (planning 12.6 for v2.6)
• tensorflow: up to cuda 12.8 in nvidia optimized containers
• jax: cuda 12.x (cuda 13.x defined but plugin not yet available)

troubleshooting

common issues

1. unsupported gpu error

   • check compute capability >= 7.5
   • maxwell/pascal/volta no longer supported

2. driver version mismatch

   # requires r580+ driver
   nvidia-smi  # should show 580.xx+

3. framework compatibility

   • continue using cuda 12.x or 11.8 builds
   • monitor framework release notes for cuda 13.0 support
   • pytorch tracking: github #159779

4. vllm dependency chain

   • vllm depends on pytorch and cupy
   • neither pytorch nor cupy support cuda 13.0 yet
   • vllm cuda 13.0 support blocked until dependencies update

future roadmap

risc-v support

nvidia announced cuda coming to risc-v:

• no timeline in cuda 13.0
• part of broader architecture expansion
• following arm unification pattern

potential cuda 14.0

based on deprecation patterns:

• turing (compute 7.5) likely next removal target
• further arm platform integration
• potential risc-v preview

references

• cuda 13.0 release notes
• cuda downloads
• compute capability table
• pytorch cuda 13 tracking
• nvidia r580 driver