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Studio: match the Linux llama.cpp prebuilt to the runtime cudart major (#5914)

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* Studio: match the Linux llama.cpp prebuilt to the runtime cudart major

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Daniel Han 2026-06-01 02:55:57 -07:00 • committed by GitHub
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11
studio/install_llama_prebuilt.py
View file

@ -1402,7 +1402,16 @@ def direct_linux_release_plan(
attempts: list[AssetChoice] = []
if host.has_usable_nvidia:
selection = linux_cuda_choice_from_release(host, bundle)
# Prefer the cudart major Studio loads at runtime (torch's bundled
# libcudart), not the newest detected on disk. Without this a stray
# cuda13 runtime outranks the torch cuda12 the binary links against.
torch_preference = detect_torch_cuda_runtime_preference(host)
selection = linux_cuda_choice_from_release(
host,
bundle,
preferred_runtime_line = torch_preference.runtime_line,
selection_preamble = torch_preference.selection_log,
)
if selection is not None:
attempts.extend(selection.attempts)
if host.has_rocm and not host.has_usable_nvidia:

74
tests/studio/install/test_install_llama_prebuilt_logic.py
View file

@ -438,6 +438,80 @@ def test_simple_linux_direct_release_uses_published_source_checksums_for_branch(
assert exact_source is True
def test_simple_linux_direct_release_honors_torch_cudart_preference(
monkeypatch: pytest.MonkeyPatch,
):
# Regression: a Blackwell host (sm_120, driver 13.0) with BOTH cudart majors
# visible -- a stray cuda13 wheel plus torch's cuda12 -- must install the
# cuda12 build that matches the runtime torch, not the newest-major cuda13
# build (which loads no GPU and silently falls back to CPU).
release = {
"tag_name": "b9334",
"assets": [
{
"name": f"app-b9334-linux-x64-{profile}.tar.gz",
"browser_download_url": f"https://example.test/app-b9334-linux-x64-{profile}.tar.gz",
}
for profile in (
"cuda12-newer",
"cuda12-portable",
"cuda13-newer",
"cuda13-portable",
)
],
}
# cuda13 detected first (newest-major order); both compatible with driver 13.0.
monkeypatch.setattr(
INSTALL_LLAMA_PREBUILT,
"detected_linux_runtime_lines",
lambda: (
["cuda13", "cuda12"],
{
"cuda13": ["/usr/local/lib/python3.13/site-packages/nvidia/cu13/lib"],
"cuda12": [
"/venv/lib/python3.13/site-packages/nvidia/cuda_runtime/lib"
],
},
),
)
host = HostInfo(
system = "Linux",
machine = "x86_64",
is_windows = False,
is_linux = True,
is_macos = False,
is_x86_64 = True,
is_arm64 = False,
nvidia_smi = "nvidia-smi",
driver_cuda_version = (13, 0),
compute_caps = ["120"],
visible_cuda_devices = None,
has_physical_nvidia = True,
has_usable_nvidia = True,
)
def first_asset_for_torch(line):
monkeypatch.setattr(
INSTALL_LLAMA_PREBUILT,
"detect_torch_cuda_runtime_preference",
lambda h: INSTALL_LLAMA_PREBUILT.CudaRuntimePreference(
runtime_line = line, selection_log = []
),
)
plan = INSTALL_LLAMA_PREBUILT.direct_linux_release_plan(
release, host, "unslothai/llama.cpp", "latest"
)
return plan.attempts[0]
# torch reports cuda12 (the cu128 runtime) -> install the cuda12 build.
primary = first_asset_for_torch("cuda12")
assert primary.name == "app-b9334-linux-x64-cuda12-newer.tar.gz"
assert primary.runtime_line == "cuda12"
# torch unavailable -> unchanged newest-major fallback (documents the residual).
assert first_asset_for_torch(None).name == "app-b9334-linux-x64-cuda13-newer.tar.gz"
@pytest.mark.parametrize(
"mutate, expected_match",
[