@Bink Thank you for the patch. I have verified the install and I believe it have resolved the installation issue.
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Package Details: llama.cpp-cuda-git b9050.r5.8e52631d55-1
Package Actions
| Git Clone URL: | https://aur.archlinux.org/llama.cpp-cuda-git.git (read-only, click to copy) |
|---|---|
| Package Base: | llama.cpp-cuda-git |
| Description: | Port of Facebook's LLaMA model in C/C++ (with NVIDIA CUDA optimizations) |
| Upstream URL: | https://github.com/ggml-org/llama.cpp |
| Licenses: | MIT |
| Conflicts: | ggml, libggml, llama.cpp |
| Provides: | ggml, libggml, libggml-cuda-git, libggml.so, llama.cpp |
| Submitter: | Bink |
| Maintainer: | Bink |
| Last Packager: | Bink |
| Votes: | 3 |
| Popularity: | 1.21 |
| First Submitted: | 2026-01-08 09:17 (UTC) |
| Last Updated: | 2026-05-08 12:41 (UTC) |
Dependencies (19)
- cuda (cuda11.1AUR, cuda-12.2AUR, cuda12.0AUR, cuda11.4AUR, cuda-12.5AUR, cuda-12.9AUR, cuda-12.8AUR, cuda-pascalAUR)
- curl (curl-gitAUR, curl-c-aresAUR)
- gcc-libs (gcc-libs-gitAUR, gccrs-libs-gitAUR, gcc-libs-snapshotAUR)
- glibc (glibc-gitAUR, glibc-eacAUR, glibc-git-native-pgoAUR)
- nvidia-utils (nvidia-410xx-utilsAUR, nvidia-440xx-utilsAUR, nvidia-430xx-utilsAUR, nvidia-340xx-utilsAUR, nvidia-510xx-utilsAUR, nvidia-utils-teslaAUR, nvidia-525xx-utilsAUR, nvidia-575xx-utilsAUR, nvidia-340xx-utils-macbookAUR, nvidia-535xx-utilsAUR, nvidia-utils-betaAUR, nvidia-470xx-utilsAUR, nvidia-390xx-utilsAUR, nvidia-550xx-utilsAUR, nvidia-580xx-utilsAUR, nvidia-vulkan-utilsAUR)
- openssl (openssl-gitAUR, openssl-staticAUR, openssl-aegisAUR)
- cmake (cmake3AUR, cmake-gitAUR) (make)
- cudnn (cudnn9.10-cuda12.9AUR, cudnn-pascalAUR) (make)
- gcc15 (make)
- git (git-gitAUR, git-glAUR, git-wd40AUR) (make)
- ninja (ninja-gitAUR, ninja-memAUR, ninja-noemacs-gitAUR, ninja-kitwareAUR, ninja-fuchsia-gitAUR, n2-ninja-symlinkAUR) (make)
- ccache (ccache-gitAUR) (optional) – greatly reduce package re-build time
- nccl (nccl-cuda12.9AUR, nccl-gitAUR) (optional) – needed for multi-GPU parallelism
- python-numpy (python-numpy-gitAUR, python-numpy-mkl-binAUR, python-numpy1AUR, python-numpy-mkl-tbbAUR, python-numpy-mklAUR) (optional) – needed for convert_hf_to_gguf.py
- python-pytorch (python-pytorch-cuda12.9AUR, python-pytorch-opt-cuda12.9AUR, python-pytorch-cuda, python-pytorch-opt, python-pytorch-opt-cuda, python-pytorch-opt-rocm, python-pytorch-rocm) (optional) – needed for convert_hf_to_gguf.py
- python-safetensors (optional) – needed for convert_hf_to_gguf.py
- python-sentencepieceAUR (python-sentencepiece-gitAUR, python-sentencepiece-binAUR) (optional) – needed for convert_hf_to_gguf.py
- python-transformersAUR (python-transformers-gitAUR) (optional) – needed for convert_hf_to_gguf.py
- rdma-core (rdma-core-gitAUR) (optional) – RDMA transport for RPC backend
Required by (7)
- llama.cpp-cublas-git (requires libggml-cuda-git)
- llamaman-bin (requires llama.cpp) (optional)
- scmd-bin (requires llama.cpp)
- voxd (requires llama.cpp) (optional)
- voxd-bin (requires llama.cpp) (optional)
- voxd-git (requires llama.cpp) (optional)
- whisper.cpp-cuda (requires libggml-cuda-git)
Sources (3)
Latest Comments
« First ‹ Previous 1 2
TeddyHuang-00 commented on 2026-04-23 17:32 (UTC)
Bink commented on 2026-04-23 10:08 (UTC)
Thanks for sharing these details! I don't have fish shell, but I've pushed an update that hopefully handles this better anyway. Let me know if that resolves it.
tixwho commented on 2026-04-23 03:30 (UTC)
Hi,
I have a single Nvidia GPU on the device. I can build the package without issue until version b8892.r0.0d0764dfd2-1, but now the package failed to build for llama-server. The error log is as follows:
[546/546] Linking CXX executable bin/llama-server
FAILED: [code=1] bin/llama-server
: && /usr/bin/c++ -march=x86-64 -mtune=generic -O2 -pipe -fno-plt -fexceptions -Wp,-D_FORTIFY_SOURCE=3 -Wformat -Werror=format-security -fstack-clash-protection -fcf-protection -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -Wp,-D_GLIBCXX_ASSERTIONS -g -ffile-prefix-map={user}/.cache/paru/clone/llama.cpp-cuda-git/src=/usr/src/debug/llama.cpp-cuda-git -flto=auto -O3 -DNDEBUG -Wl,-O1 -Wl,--sort-common -Wl,--as-needed -Wl,-z,relro -Wl,-z,now -Wl,-z,pack-relative-relocs -flto=auto -Wl,--dependency-file=tools/server/CMakeFiles/llama-server.dir/link.d tools/server/CMakeFiles/llama-server.dir/server.cpp.o tools/server/CMakeFiles/llama-server.dir/server-http.cpp.o tools/server/CMakeFiles/llama-server.dir/server-models.cpp.o -o bin/llama-server -Wl,-rpath,{user}/.cache/paru/clone/llama.cpp-cuda-git/src/build/bin: tools/server/libserver-context.a bin/libllama-common.so.0.0.0 vendor/cpp-httplib/libcpp-httplib.a common/libllama-common-base.a bin/libmtmd.so.0.0.0 bin/libllama.so.0.0.0 bin/libggml.so.0.10.0 bin/libggml-cpu.so.0.10.0 bin/libggml-cuda.so.0.10.0 /opt/cuda/targets/x86_64-linux/lib/stubs/libcuda.so bin/libggml-rpc.so.0.10.0 bin/libggml-base.so.0.10.0 /usr/lib/libssl.so /usr/lib/libcrypto.so && :
/usr/bin/ld: final link failed: bad value
collect2: error: ld returned 1 exit status
ninja: build stopped: subcommand failed.
==> ERROR: A failure occurred in build().
Aborting...
error: failed to build 'llama.cpp-cuda-git-b8851.r0.e365e658f0-1':
error: packages failed to build: llama.cpp-cuda-git-b8851.r0.e365e658f0-1
Installing the two optional dependencies nccl and ccache didn't fix the issue. I wonder if it could be due to some recent build flag changes?
TeddyHuang-00 commented on 2026-04-22 19:55 (UTC) (edited on 2026-04-22 19:55 (UTC) by TeddyHuang-00)
@dareme7 I am also using fish shell. The only two things cuda.sh does is 1. Add /opt/cuda/bin to path, and 2. set NVCC_CCBIN to /usr/bin/g++.
You can bypass the script by setting NVCC_CCBIN to the same /usr/bin/g++ (PKGBUILD will be happy with it set), and of course add /opt/cuda/bin to your path using fish_add_path to make sure nvcc is available.
I don't know if it is the best thing to do to put them into your config, but should definitely get the issues resolved for now.
dareme7 commented on 2026-04-21 20:52 (UTC)
This now crashes by saying append_path command in /etc/profile.d/cuda.sh is not found.
By googling I found a forum thread saying PKGBUILD should not be sourcing like this.
For reference I'm using the fish shell, which might be relevant here.
Bink commented on 2026-04-20 01:25 (UTC)
The package now leverages ninja to ensure parallel builds regardless of makepkg.conf settings.
If you have multiple Nvidia GPU's, be sure to install the optional dependency nccl, for multi-GPU parallelism.
To improve re-build times, install the optional dependency ccache.
Bink commented on 2026-02-23 22:29 (UTC) (edited on 2026-02-23 22:32 (UTC) by Bink)
Hi @zeroxoneafour. Thanks for the feedback! Suggestions are always welcome!
The -j$(nproc) flag should be added to your /etc/makepkg.conf file, and you'll then enjoy the benefit of that optimisation for all applicable compile tasks.
See here: https://wiki.archlinux.org/title/Makepkg#Parallel_compilation
The Release build is already specified in the PKGBUILD:
-DCMAKE_BUILD_TYPE=Release
zeroxoneafour commented on 2026-02-23 05:44 (UTC)
Should add --config Release -j $(nproc) to the cmake build to speed up build times.
Bink commented on 2026-01-30 01:16 (UTC)
Thanks for spotting and sharing that @ryant0000. I've now removed that flag.
ryant0000 commented on 2026-01-24 17:42 (UTC)
CMake Warning at CMakeLists.txt:121 (message): LLAMA_CURL option is deprecated and will be ignored
This can/should probably be removed.
Pinned Comments
Bink commented on 2026-04-20 01:25 (UTC)
The package now leverages ninja to ensure parallel builds regardless of
makepkg.confsettings.If you have multiple Nvidia GPU's, be sure to install the optional dependency
nccl, for multi-GPU parallelism.To improve re-build times, install the optional dependency
ccache.