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Hi @xiota, can we change to libggml instead of libggml-git ?

Build fails now with:

"[ 5%] Building CXX object examples/CMakeFiles/common.dir/grammar-parser.c pp.o [ 6%] Linking CXX executable ../../bin/whisper-bench /var/cache/makepkg/whisper.cpp/src/whisper.cpp-1.8.4/examples/common-ggml. cpp: In function ‘bool ggml_common_quantize_0(std::ifstream&, std::ofstrea m&, ggml_ftype, const std::vector<std::__cxx11::basic_string\<char> >&, con st std::vector<std::__cxx11::basic_string\<char> >&)’: /var/cache/makepkg/whisper.cpp/src/whisper.cpp-1.8.4/examples/common-ggml. cpp:76:14: error: ‘GGML_FTYPE_MOSTLY_NVFP4’ was not declared in this scope ; did you mean ‘GGML_FTYPE_MOSTLY_MXFP4’? 76 | case GGML_FTYPE_MOSTLY_NVFP4: | ^ | GGML_FTYPE_MOSTLY_MXFP4 /var/cache/makepkg/whisper.cpp/src/whisper.cpp-1.8.4/examples/common-ggml. cpp:217:22: error: ‘GGML_TYPE_NVFP4’ was not declared in this scope; did y ou mean ‘GGML_TYPE_MXFP4’? 217 | case GGML_TYPE_NVFP4: | ^ | GGML_TYPE_MXFP4 [ 6%] Built target whisper-bench make[2]: *** [examples/CMakeFiles/common.dir/build.make:93: examples/CMake Files/common.dir/common-ggml.cpp.o] Error 1 make[2]: *** Waiting for unfinished jobs.... make[1]: *** [CMakeFiles/Makefile2:435: examples/CMakeFiles/common.dir/all ] Error 2 make: *** [Makefile:136: all] Error 2 ==> ERROR: A failure occurred in build(). Aborting... -> error making: whisper.cpp-exit status 4 checking dependencies... "

# Maintainer: robertfoster

pkgname=whisper.cpp
pkgver=1.8.4 # renovate: datasource=github-tags depName=ggerganov/whisper.cpp
pkgrel=1
pkgdesc="Port of OpenAI's Whisper model in C/C++ (with OpenBLAS + Vulkan optimizations)"
arch=('armv7h' 'aarch64' 'x86_64')
url="https://github.com/ggerganov/whisper.cpp"
license=("MIT")
depends=('libggml' 'sdl2-compat')
makedepends=(
  'cmake'
  'git'
)
source=(
  "${pkgname}-${pkgver}.tar.gz::${url}/archive/v${pkgver}.tar.gz"
  disable-deprecated.patch
)

prepare() {
  cd "${srcdir}/${pkgname}-${pkgver}"
  patch -Np1 -i "${srcdir}/disable-deprecated.patch"
}

build() {
  cmake \
    -B "${srcdir}/build" \
    -S "${srcdir}/${pkgname}-${pkgver}" \
    -DCMAKE_INSTALL_PREFIX=/usr \
    -DCMAKE_BUILD_TYPE=Release \
    -DWHISPER_SDL2=1 \
    -DWHISPER_BUILD_SERVER=0 \
    -DWHISPER_BUILD_TESTS=0 \
    -DWHISPER_USE_SYSTEM_GGML=1

  cmake --build "${srcdir}/build"
}

package() {
  DESTDIR="${pkgdir}" cmake --install "${srcdir}/build"

  cp -r ${srcdir}/build/bin "${pkgdir}"/usr
  install -Dm644 "${srcdir}/${pkgname}-${pkgver}/LICENSE" \
    -t "${pkgdir}/usr/share/licenses/${pkgname}"
}

sha256sums=('b26f30e52c095ccb75da40b168437736605eb280de57381887bf9e2b65f31e66'
            '5f880edae417c7083a9403260e5c381285e4c52ccc39f127c6510fdfa249c1ad')

@robertfoster, could you please change the dependency to the new libggml package?

you could do something similar to what I did in ffmpeg-whisper:

# Export the variable matching your GPU, then run makepkg:
#   CUDA_ARCH=sm_120 makepkg -si
#
# Architecture      Compute Cap.  GPUs
# ─────────────────────────────────────────────────────────────────────────────
# sm_121            12.1          GB10 (DGX Spark)
# sm_120            12.0          GeForce RTX 5090/5080/5070/5060/5050,
#                                 RTX PRO 6000/5000/4500/4000/2000 Blackwell
# sm_103            10.3          GB300, B300 (data center)
# sm_100            10.0          GB200, B200 (data center)
# sm_90             9.0           H100, H200, GH200 (data center)
# sm_89             8.9           GeForce RTX 4090/4080/4070/4060/4050,
#                                 RTX 6000/5000/4500/4000 Ada, L4, L40, L40S
# sm_87             8.7           Jetson AGX Orin, Orin NX, Orin Nano
# sm_86             8.6           GeForce RTX 3090/3080/3070/3060/3050,
#                                 RTX A6000/A5000/A4000/A3000/A2000, A40, A10
# sm_80             8.0           A100, A30 (data center)
# sm_75             7.5           GeForce RTX 2080/2070/2060, GTX 1650 Ti, T4
#
# Reference: https://developer.nvidia.com/cuda-gpus
# ==============================================================================
_cuda_arch="${CUDA_ARCH:-}"

Of course, strip off the leading "sm_" for your case.

Then:

build() {
  if [[ -z "$_cuda_arch" ]]; then
    echo ""
    echo "ERROR: CUDA_ARCH is not set. You must specify your GPU architecture."
    echo "       Set it before running makepkg, for example:"
    echo ""
    echo "         CUDA_ARCH=sm_120 makepkg -si"
    echo ""
    echo "  sm_121  → GB10 (DGX Spark)"
    echo "  sm_120  → GeForce RTX 5090/5080/5070/5060/5050, RTX PRO Blackwell"
    echo "  sm_103  → GB300, B300 (data center)"
    echo "  sm_100  → GB200, B200 (data center)"
    echo "  sm_90   → H100, H200, GH200"
    echo "  sm_89   → GeForce RTX 4090/4080/4070/4060/4050, Ada, L4, L40S"
    echo "  sm_87   → Jetson AGX Orin, Orin NX, Orin Nano"
    echo "  sm_86   → GeForce RTX 3090/3080/3070/3060/3050, RTX A-series, A40"
    echo "  sm_80   → A100, A30 (data center)"
    echo "  sm_75   → GeForce RTX 2080/2070/2060, GTX 1650 Ti, T4"
    echo ""
    echo "  See: https://developer.nvidia.com/cuda-gpus"
    echo ""
    return 1
  fi
...

And you can add that one line in your build function:

-DCMAKE_CUDA_ARCHITECTURES=${_cuda_arch}

Now that libggml has releases and whisper.cpp has been updated to work with the latest release, I'm in favor of changing the dependency to libggml.

It's just the old checksum from the previous version. Judging from the commit message the bump was automated, so can you please correct this and check if this is the GitHub action's fault, @robertfoster?

I can't install 1.8.3.

With wget https://github.com/ggerganov/whisper.cpp/archive/v1.8.3.tar.gz I get 870ba21409cdf66697dc4db15ebdb13bc67037d76c7cc63756c81471d8f1731a v1.8.3.tar.gz

Package has sha256sums=('bcee25589bb8052d9e155369f6759a05729a2022d2a8085c1aa4345108523077' '5f880edae417c7083a9403260e5c381285e4c52ccc39f127c6510fdfa249c1ad')

It didn't work out unfortunately, 0.9.4 is too old and it doesn't build:

whisper.cpp/src/whisper.cpp-1.8.2/examples/talk-llama/llama-model.cpp: In constructor ‘llm_build_apertus::llm_build_apertus(const llama_model&, const llm_graph_params&)’:
whisper.cpp/src/whisper.cpp-1.8.2/examples/talk-llama/llama-model.cpp:19330:43: error: ‘ggml_xielu’ was not declared in this scope; did you mean ‘ggml_silu’?
19330 |                 ggml_tensor * activated = ggml_xielu(ctx0, up, alpha_n_val, alpha_p_val, beta_val, eps_val);
      |                                           ^~~~~~~~~~
      |                                           ggml_silu
make[2]: *** [examples/talk-llama/CMakeFiles/whisper-talk-llama.dir/build.make:373: examples/talk-llama/CMakeFiles/whisper-talk-llama.dir/llama-model.cpp.o] Error 1
make[1]: *** [CMakeFiles/Makefile2:733: examples/talk-llama/CMakeFiles/whisper-talk-llama.dir/all] Error 2
make: *** [Makefile:136: all] Error 2

You could either pin libggml to the version vendored with whisper.cpp 1.8.2, which is based on this commit, or to the latest working commit, which is this one according to @berif69361. whisper.cpp's master branch now includes ggml 0.9.5, so let's just hope they stick to these stable releases in the future.

I also checked if it would be possible to just backport some commits for ggml 0.9.5 compatibility, but this includes multiple commits made over several weeks, so probably not worth the hassle.

Edit: I can confirm whisper.cpp 0.8.2 build successfully builds with either ggml commit.

I expect 0.9.4 to work, but I'll check and report back.