https://github.com/change72/vllm-test

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

○
CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
✓
.zenodo.json file
Found .zenodo.json file
○
DOI references
✓
Academic publication links
Links to: arxiv.org
○
Academic email domains
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Institutional organization owner
○
JOSS paper metadata
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Scientific vocabulary similarity
Low similarity (7.9%) to scientific vocabulary

Last synced: 10 months ago · JSON representation

Repository

Basic Info

Host: GitHub
Owner: Change72
License: apache-2.0
Language: Python
Default Branch: main
Size: 55.2 MB

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Open Issues: 1
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Created 12 months ago · Last pushed 10 months ago

Metadata Files

Readme Contributing Funding License Code of conduct Codeowners Security

Easy, fast, and cheap LLM serving for everyone

Latest News 🔥 - [2025/05] We hosted NYC vLLM Meetup! Please find the meetup slides here. - [2025/05] vLLM is now a hosted project under PyTorch Foundation! Please find the announcement here. - [2025/04] We hosted Asia Developer Day! Please find the meetup slides from the vLLM team here. - [2025/01] We are excited to announce the alpha release of vLLM V1: A major architectural upgrade with 1.7x speedup! Clean code, optimized execution loop, zero-overhead prefix caching, enhanced multimodal support, and more. Please check out our blog post here.

Previous News

- [2025/03] We hosted [vLLM x Ollama Inference Night](https://lu.ma/vllm-ollama)! Please find the meetup slides from the vLLM team [here](https://docs.google.com/presentation/d/16T2PDD1YwRnZ4Tu8Q5r6n53c5Lr5c73UV9Vd2_eBo4U/edit?usp=sharing). - [2025/03] We hosted [the first vLLM China Meetup](https://mp.weixin.qq.com/s/n77GibL2corAtQHtVEAzfg)! Please find the meetup slides from vLLM team [here](https://docs.google.com/presentation/d/1REHvfQMKGnvz6p3Fd23HhSO4c8j5WPGZV0bKYLwnHyQ/edit?usp=sharing). - [2025/03] We hosted [the East Coast vLLM Meetup](https://lu.ma/7mu4k4xx)! Please find the meetup slides [here](https://docs.google.com/presentation/d/1NHiv8EUFF1NLd3fEYODm56nDmL26lEeXCaDgyDlTsRs/edit#slide=id.g31441846c39_0_0). - [2025/02] We hosted [the ninth vLLM meetup](https://lu.ma/h7g3kuj9) with Meta! Please find the meetup slides from vLLM team [here](https://docs.google.com/presentation/d/1jzC_PZVXrVNSFVCW-V4cFXb6pn7zZ2CyP_Flwo05aqg/edit?usp=sharing) and AMD [here](https://drive.google.com/file/d/1Zk5qEJIkTmlQ2eQcXQZlljAx3m9s7nwn/view?usp=sharing). The slides from Meta will not be posted. - [2025/01] We hosted [the eighth vLLM meetup](https://lu.ma/zep56hui) with Google Cloud! Please find the meetup slides from vLLM team [here](https://docs.google.com/presentation/d/1epVkt4Zu8Jz_S5OhEHPc798emsYh2BwYfRuDDVEF7u4/edit?usp=sharing), and Google Cloud team [here](https://drive.google.com/file/d/1h24pHewANyRL11xy5dXUbvRC9F9Kkjix/view?usp=sharing). - [2024/12] vLLM joins [pytorch ecosystem](https://pytorch.org/blog/vllm-joins-pytorch)! Easy, Fast, and Cheap LLM Serving for Everyone! - [2024/11] We hosted [the seventh vLLM meetup](https://lu.ma/h0qvrajz) with Snowflake! Please find the meetup slides from vLLM team [here](https://docs.google.com/presentation/d/1e3CxQBV3JsfGp30SwyvS3eM_tW-ghOhJ9PAJGK6KR54/edit?usp=sharing), and Snowflake team [here](https://docs.google.com/presentation/d/1qF3RkDAbOULwz9WK5TOltt2fE9t6uIc_hVNLFAaQX6A/edit?usp=sharing). - [2024/10] We have just created a developer slack ([slack.vllm.ai](https://slack.vllm.ai)) focusing on coordinating contributions and discussing features. Please feel free to join us there! - [2024/10] Ray Summit 2024 held a special track for vLLM! Please find the opening talk slides from the vLLM team [here](https://docs.google.com/presentation/d/1B_KQxpHBTRa_mDF-tR6i8rWdOU5QoTZNcEg2MKZxEHM/edit?usp=sharing). Learn more from the [talks](https://www.youtube.com/playlist?list=PLzTswPQNepXl6AQwifuwUImLPFRVpksjR) from other vLLM contributors and users! - [2024/09] We hosted [the sixth vLLM meetup](https://lu.ma/87q3nvnh) with NVIDIA! Please find the meetup slides [here](https://docs.google.com/presentation/d/1wrLGwytQfaOTd5wCGSPNhoaW3nq0E-9wqyP7ny93xRs/edit?usp=sharing). - [2024/07] We hosted [the fifth vLLM meetup](https://lu.ma/lp0gyjqr) with AWS! Please find the meetup slides [here](https://docs.google.com/presentation/d/1RgUD8aCfcHocghoP3zmXzck9vX3RCI9yfUAB2Bbcl4Y/edit?usp=sharing). - [2024/07] In partnership with Meta, vLLM officially supports Llama 3.1 with FP8 quantization and pipeline parallelism! Please check out our blog post [here](https://blog.vllm.ai/2024/07/23/llama31.html). - [2024/06] We hosted [the fourth vLLM meetup](https://lu.ma/agivllm) with Cloudflare and BentoML! Please find the meetup slides [here](https://docs.google.com/presentation/d/1iJ8o7V2bQEi0BFEljLTwc5G1S10_Rhv3beed5oB0NJ4/edit?usp=sharing). - [2024/04] We hosted [the third vLLM meetup](https://robloxandvllmmeetup2024.splashthat.com/) with Roblox! Please find the meetup slides [here](https://docs.google.com/presentation/d/1A--47JAK4BJ39t954HyTkvtfwn0fkqtsL8NGFuslReM/edit?usp=sharing). - [2024/01] We hosted [the second vLLM meetup](https://lu.ma/ygxbpzhl) with IBM! Please find the meetup slides [here](https://docs.google.com/presentation/d/12mI2sKABnUw5RBWXDYY-HtHth4iMSNcEoQ10jDQbxgA/edit?usp=sharing). - [2023/10] We hosted [the first vLLM meetup](https://lu.ma/first-vllm-meetup) with a16z! Please find the meetup slides [here](https://docs.google.com/presentation/d/1QL-XPFXiFpDBh86DbEegFXBXFXjix4v032GhShbKf3s/edit?usp=sharing). - [2023/08] We would like to express our sincere gratitude to [Andreessen Horowitz](https://a16z.com/2023/08/30/supporting-the-open-source-ai-community/) (a16z) for providing a generous grant to support the open-source development and research of vLLM. - [2023/06] We officially released vLLM! FastChat-vLLM integration has powered [LMSYS Vicuna and Chatbot Arena](https://chat.lmsys.org) since mid-April. Check out our [blog post](https://vllm.ai).

About

vLLM is a fast and easy-to-use library for LLM inference and serving.

Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry.

vLLM is fast with:

State-of-the-art serving throughput
Efficient management of attention key and value memory with PagedAttention
Continuous batching of incoming requests
Fast model execution with CUDA/HIP graph
Quantizations: GPTQ, AWQ, AutoRound, INT4, INT8, and FP8
Optimized CUDA kernels, including integration with FlashAttention and FlashInfer
Speculative decoding
Chunked prefill

Performance benchmark: We include a performance benchmark at the end of our blog post. It compares the performance of vLLM against other LLM serving engines (TensorRT-LLM, SGLang and LMDeploy). The implementation is under nightly-benchmarks folder and you can reproduce this benchmark using our one-click runnable script.

vLLM is flexible and easy to use with:

Seamless integration with popular Hugging Face models
High-throughput serving with various decoding algorithms, including parallel sampling, beam search, and more
Tensor parallelism and pipeline parallelism support for distributed inference
Streaming outputs
OpenAI-compatible API server
Support NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs and GPUs, PowerPC CPUs, TPU, and AWS Neuron
Prefix caching support
Multi-LoRA support

vLLM seamlessly supports most popular open-source models on HuggingFace, including: - Transformer-like LLMs (e.g., Llama) - Mixture-of-Expert LLMs (e.g., Mixtral, Deepseek-V2 and V3) - Embedding Models (e.g., E5-Mistral) - Multi-modal LLMs (e.g., LLaVA)

Find the full list of supported models here.

Getting Started

Install vLLM with pip or from source:

bash pip install vllm

Visit our documentation to learn more. - Installation - Quickstart - List of Supported Models

Contributing

We welcome and value any contributions and collaborations. Please check out Contributing to vLLM for how to get involved.

Citation

If you use vLLM for your research, please cite our paper:

bibtex @inproceedings{kwon2023efficient, title={Efficient Memory Management for Large Language Model Serving with PagedAttention}, author={Woosuk Kwon and Zhuohan Li and Siyuan Zhuang and Ying Sheng and Lianmin Zheng and Cody Hao Yu and Joseph E. Gonzalez and Hao Zhang and Ion Stoica}, booktitle={Proceedings of the ACM SIGOPS 29th Symposium on Operating Systems Principles}, year={2023} }

Contact Us

For technical questions and feature requests, please use GitHub Issues or Discussions
For discussing with fellow users, please use the vLLM Forum
coordinating contributions and development, please use Slack
For security disclosures, please use GitHub's Security Advisories feature
For collaborations and partnerships, please contact us at vllm-questions@lists.berkeley.edu

Media Kit

If you wish to use vLLM's logo, please refer to our media kit repo

Owner

Login: Change72
Kind: user

Repositories: 1
Profile: https://github.com/Change72

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Dependencies

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nvidia-cusolver-cu12 ==11.7.2.55 test
nvidia-cusparse-cu12 ==12.5.7.53 test
nvidia-cusparselt-cu12 ==0.6.3 test
nvidia-nccl-cu12 ==2.26.2 test
nvidia-nvjitlink-cu12 ==12.8.61 test
nvidia-nvtx-cu12 ==12.8.55 test
opencensus ==0.11.4 test
opencensus-context ==0.1.3 test
opencv-python-headless ==4.11.0.86 test
packaging ==24.2 test
pandas ==2.2.3 test
pathspec ==0.12.1 test
pathvalidate ==3.2.1 test
patsy ==1.0.1 test
peft ==0.13.2 test
pillow ==10.4.0 test
platformdirs ==4.3.6 test
plotly ==5.24.1 test
pluggy ==1.5.0 test
polars ==1.29.0 test
pooch ==1.8.2 test
portalocker ==2.10.1 test
pqdm ==0.2.0 test
prometheus-client ==0.22.0 test
propcache ==0.2.0 test
proto-plus ==1.26.1 test
protobuf ==5.28.3 test
psutil ==6.1.0 test
py ==1.11.0 test
py-spy ==0.4.0 test
pyarrow ==18.0.0 test
pyasn1 ==0.6.1 test
pyasn1-modules ==0.4.2 test
pybind11 ==2.13.6 test
pycparser ==2.22 test
pycryptodomex ==3.22.0 test
pydantic ==2.11.5 test
pydantic-core ==2.33.2 test
pygments ==2.18.0 test
pyparsing ==3.2.0 test
pyrate-limiter ==3.7.0 test
pystemmer ==3.0.0 test
pytablewriter ==1.2.0 test
pytest ==8.3.3 test
pytest-asyncio ==0.24.0 test
pytest-forked ==1.6.0 test
pytest-mock ==3.14.0 test
pytest-rerunfailures ==14.0 test
pytest-shard ==0.1.2 test
pytest-subtests ==0.14.1 test
pytest-timeout ==2.3.1 test
python-dateutil ==2.9.0.post0 test
python-rapidjson ==1.20 test
pytrec-eval-terrier ==0.5.7 test
pytz ==2024.2 test
pyyaml ==6.0.2 test
rapidfuzz ==3.12.1 test
ray ==2.43.0 test
redis ==5.2.0 test
referencing ==0.35.1 test
regex ==2024.9.11 test
requests ==2.32.3 test
responses ==0.25.3 test
rfc3339-validator ==0.1.4 test
rfc3987 ==1.3.8 test
rich ==13.9.4 test
rouge-score ==0.1.2 test
rpds-py ==0.20.1 test
rsa ==4.9.1 test
runai-model-streamer ==0.11.0 test
runai-model-streamer-s3 ==0.11.0 test
s3transfer ==0.10.3 test
sacrebleu ==2.4.3 test
safetensors ==0.4.5 test
schemathesis ==3.39.15 test
scikit-learn ==1.5.2 test
scipy ==1.13.1 test
sentence-transformers ==3.2.1 test
sentencepiece ==0.2.0 test
setuptools ==77.0.3 test
shellingham ==1.5.4 test
six ==1.16.0 test
smart-open ==7.1.0 test
sniffio ==1.3.1 test
sortedcontainers ==2.4.0 test
soundfile ==0.12.1 test
soxr ==0.5.0.post1 test
sqlitedict ==2.1.0 test
starlette ==0.46.2 test
starlette-testclient ==0.4.1 test
statsmodels ==0.14.4 test
sympy ==1.13.3 test
tabledata ==1.3.3 test
tabulate ==0.9.0 test
tcolorpy ==0.1.6 test
tenacity ==9.0.0 test
tensorizer ==2.9.0 test
threadpoolctl ==3.5.0 test
tiktoken ==0.7.0 test
timm ==1.0.11 test
tokenizers ==0.21.1 test
tomli ==2.2.1 test
tomli-w ==1.2.0 test
torch ==2.7.0 test
torchaudio ==2.7.0 test
torchvision ==0.22.0 test
tqdm ==4.66.6 test
tqdm-multiprocess ==0.0.11 test
transformers ==4.52.4 test
transformers-stream-generator ==0.0.5 test
triton ==3.3.0 test
tritonclient ==2.51.0 test
typepy ==1.3.2 test
typer ==0.15.2 test
types-python-dateutil ==2.9.0.20241206 test
typing-extensions ==4.12.2 test
typing-inspection ==0.4.1 test
tzdata ==2024.2 test
uri-template ==1.3.0 test
urllib3 ==2.2.3 test
vector-quantize-pytorch ==1.21.2 test
virtualenv ==20.31.2 test
vocos ==0.1.0 test
webcolors ==24.11.1 test
werkzeug ==3.1.3 test
word2number ==1.1 test
wrapt ==1.17.2 test
xxhash ==3.5.0 test
yarl ==1.17.1 test
zstandard ==0.23.0 test

requirements/tpu.txt pypi

cmake >=3.26.1
jinja2 >=3.1.6
packaging >=24.2
ray *
setuptools ==78.1.0
setuptools-scm >=8
torch ==2.8.0.dev20250605
torchvision ==0.23.0.dev20250605
wheel *

requirements/xpu.txt pypi

cmake >=3.26.1
datasets *
intel-extension-for-pytorch ==2.7.10
jinja2 >=3.1.6
oneccl_bind_pt ==2.7.0
packaging >=24.2
pytorch-triton-xpu *
ray >=2.9
setuptools >=77.0.3,<80.0.0
setuptools-scm >=8
torch ==2.7.0
torchaudio *
torchvision *
wheel *

setup.py pypi

tests/plugins/vllm_add_dummy_model/setup.py pypi

tests/plugins/vllm_add_dummy_platform/setup.py pypi

tests/vllm_test_utils/setup.py pypi

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