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LocalAI [bot] 8565febe45 fix(vllm): pin L4T arm64 backend to vllm==0.24.0 for GB10 stability (#10725 )

The nvidia-l4t-cuda-13-arm64 vLLM backend left `vllm` unpinned, so the
prebuilt image drifted onto whatever aarch64 wheel was latest at build
time (0.23.x). On GB10 / DGX Spark (Grace Blackwell, unified memory),
0.23 crashes deterministically during cold model loads with an empty
"Engine core initialization failed" set and pins GPU memory until a host
reboot.

vLLM 0.24.0 carries vllm-project/vllm#45179 ("release cached device
memory under pressure on UMA GPUs during weight loading"), which the
reporter verified fixes the crash on GB10. Pin the L4T requirements to
0.24.0 to match the already-pinned cublas13 build
(requirements-cublas13-after.txt) and keep the image deterministic.

Editing this file also re-triggers the single-arch L4T image build via
the path filter, republishing the gallery image with 0.24.0 (the
single-arch matrix builds again after #10703).

Closes #10722


Assisted-by: Claude:claude-opus-4-8 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>

2026-07-07 20:18:23 +00:00

..

backend.py

fix(vllm): non-streaming tool-call regression after #10351 (#10638 )

2026-07-02 09:26:14 +02:00

install.sh

chore: ⬆️ Update vllm-metal (darwin) to v0.3.0.dev20260706123649 (#10712 )

2026-07-07 08:41:34 +02:00

Makefile

feat(mlx): add mlx backend (#6049 )

2025-08-22 08:42:29 +02:00

package.sh

feat(vllm, distributed): tensor parallel distributed workers (#9612 )

2026-05-06 00:22:50 +02:00

README.md

refactor: move backends into the backends directory (#1279 )

2023-11-13 22:40:16 +01:00

requirements-after.txt

feat(vllm): parity with llama.cpp backend (#9328 )

2026-04-13 11:00:29 +02:00

requirements-cpu-after.txt

feat(vllm): parity with llama.cpp backend (#9328 )

2026-04-13 11:00:29 +02:00

requirements-cpu.txt

feat(vllm): parity with llama.cpp backend (#9328 )

2026-04-13 11:00:29 +02:00

requirements-cublas12-after.txt

fix(vllm): drop flash-attn wheel to avoid torch 2.10 ABI mismatch (#9557 )

2026-04-25 15:38:13 +00:00

requirements-cublas12.txt

fix(vllm): drop flash-attn wheel to avoid torch 2.10 ABI mismatch (#9557 )

2026-04-25 15:38:13 +00:00

requirements-cublas13-after.txt

chore: ⬆️ Update vllm-project/vllm cu130 wheel to 0.24.0 (#10618 )

2026-07-01 08:53:03 +02:00

requirements-cublas13.txt

feat(backends): add CUDA 13 + L4T arm64 CUDA 13 variants for vllm/vllm-omni/sglang (#9553 )

2026-04-25 12:26:29 +02:00

requirements-hipblas.txt

feat(rocm): bump to 7.x (#9323 )

2026-04-12 08:51:30 +02:00

requirements-install.txt

fix(vllm): seed pybind11 for fastsafetensors build under --no-build-isolation

2026-04-28 20:08:26 +00:00

requirements-intel-after.txt

feat(vllm, distributed): tensor parallel distributed workers (#9612 )

2026-05-06 00:22:50 +02:00

requirements-intel.txt

feat(vllm, distributed): tensor parallel distributed workers (#9612 )

2026-05-06 00:22:50 +02:00

requirements-l4t13-after.txt

fix(vllm): pin L4T arm64 backend to vllm==0.24.0 for GB10 stability (#10725 )

2026-07-07 20:18:23 +00:00

requirements-l4t13.txt

fix(L4T13 backends): switch vllm/sglang/vllm-omni to PyPI aarch64+cu130 wheels (#9950 )

2026-05-22 23:01:22 +02:00

requirements.txt

chore(deps): bump grpcio from 1.81.0 to 1.81.1 in /backend/python/vllm (#10347 )

2026-06-15 22:57:38 +02:00

run.sh

fix(python-backend): make JIT subprocesses work on hosts of any size (#9679 )

2026-05-06 00:28:01 +02:00

test.py

feat(vllm): progressive streaming via parser.extract_tool_calls_streaming (follow-up to #10346 ) (#10351 )

2026-06-21 17:07:15 +02:00

test.sh

feat: Add backend gallery (#5607 )

2025-06-15 14:56:52 +02:00

README.md

Creating a separate environment for the vllm project

make vllm