| --- |
| license: other |
| license_name: mixed-third-party-runtime-licenses |
| pretty_name: Portable vLLM runtime |
| tags: |
| - vllm |
| - inference |
| - cuda |
| - portable-runtime |
| --- |
| # Portable vLLM 0.32.0 / CUDA 13.0 |
|
|
| Release `vllm-0.32.0-cu130-20261028-r1`. Payload revision: `2f96debc23c2ae0ca333314587bf321b28c25f37`. |
| Standalone Python 3.12.12, vLLM 0.32.0, Torch 2.13.0, an exact `uv.lock`, |
| private CUDA 13.0 toolkit, support libraries and node helpers. |
| Linux x86_64, glibc >= 2.35. Fixed installation root: |
| `/opt/vllm-runtime-0.32.0-cu130` (root permission required). |
| |
| Archive size: **5,821,293,851 bytes**. |
| Unpacked regular-file bytes: **11,041,486,896**. |
| Archive SHA256: `b22e2ef9b1d1f1f2f233b9360bc82e8cb53b69c3d4811e3043167f0037db532b`. |
| Reserve space for the downloaded archive, extraction, JIT caches, models and outputs. |
| |
| ## Download |
| |
| Download [download_release.py](https://huggingface.co/datasets/codemaivanngu/vllm-portable-runtime/resolve/2f96debc23c2ae0ca333314587bf321b28c25f37/releases/vllm-0.32.0-cu130-20261028-r1/download_release.py). |
| With an existing Python 3.10+ on the company Linux instance: |
| |
| ```bash |
| python3 download_release.py --revision 2f96debc23c2ae0ca333314587bf321b28c25f37 --archive-sha256 b22e2ef9b1d1f1f2f233b9360bc82e8cb53b69c3d4811e3043167f0037db532b --output /your/node-local/vllm-payload --workers 8 |
| ``` |
| |
| Use your existing approved proxy environment. This public release requires no |
| HF token. The downloader verifies every manifest file; it neither installs nor |
| uses GPUs. From the payload directory, verify `sha256sum -c SHA256SUMS`, then |
| run `python3 install.py`. The installer refuses existing paths and runs CPU/import |
| checks with GPUs hidden. It changes no driver or system CUDA installation. |
| |
| ## Run |
| |
| The foreground CLI wrapper is |
| `/opt/vllm-runtime-0.32.0-cu130/node/vllm.sh`; pass normal vLLM arguments such as |
| `serve /path/to/your/model --host 127.0.0.1 --port 8000`. |
| `node/python-vllm.sh` runs Python scripts in the same independent runtime. |
| Both wrappers default to GPUs hidden. Explicitly set `CUDA_VISIBLE_DEVICES` |
| to your assigned GPU UUID(s), following your scheduler's assignment. |
| Stopping the server and its owned workers releases their VRAM; shell |
| deactivation alone does not stop processes. |
| |
| Production models/data/output and JIT caches remain external. HF defaults to |
| offline mode; stage weights separately. Override `VLLM_PORTABLE_CACHE` for the |
| cache directory and `VLLM_PORTABLE_HF_HOME` for the model cache. |
| The node still needs a compatible NVIDIA driver, host glibc and a C/C++ |
| compiler with development headers (GCC 11 was tested). nvcc/CUDA headers/ptxas |
| come from the private bundled toolkit. No NVIDIA kernel driver or host glibc |
| is bundled. Third-party licenses and CUDA notices remain applicable; this |
| bundle does not relicense dependencies. |
| |
| ## Evidence and limits |
| |
| Publication requires CPU checks, native B200 CUDA kernels, normal compiled |
| synthetic dense BF16 generation and loopback HTTP serving, plus archive restore |
| and repeated GPU inference/HTTP checks on a separate Ubuntu 22.04 image with |
| no system CUDA toolkit and Internet blocked. See `qualification.json`, both restore receipts, |
| `build-facts.json`, `manifest.json` and `uv.lock` under `releases/vllm-0.32.0-cu130-20261028-r1/`. |
| |
| Fixtures are tiny random models, not production weights or benchmark results. |
| The company node, real model families, multi-GPU/NCCL, quantization, multimodal |
| and all optional backends have not been qualified by these tests. |
| The release contains no corporate data, credentials or run caches. |
| A full anonymous download of the archive and every manifest file passed SHA256 verification. The receipt is published under `validation/vllm-0.32.0-cu130-20261028-r1/public-download-receipt.json`. |
| |
