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Welcome to vLLM!
================
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.. figure :: ./assets/logos/vllm-logo-text-light.png
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:alt: vLLM
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.. raw :: html
<p style="text-align:center">
<strong>Easy, fast, and cheap LLM serving for everyone
</strong>
</p>
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vLLM is a fast and easy-to-use library for LLM inference and serving.
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vLLM is fast with:
* State-of-the-art serving throughput
* Efficient management of attention key and value memory with **PagedAttention**
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* Continuous batching of incoming requests
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* Fast model execution with CUDA/HIP graph
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* Quantization: `GPTQ <https://arxiv.org/abs/2210.17323> `_ , `AWQ <https://arxiv.org/abs/2306.00978> `_ , `SqueezeLLM <https://arxiv.org/abs/2306.07629> `_ , FP8 KV Cache
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* Optimized CUDA kernels
vLLM is flexible and easy to use with:
* Seamless integration with popular HuggingFace models
* High-throughput serving with various decoding algorithms, including *parallel sampling* , *beam search* , and more
* Tensor parallelism support for distributed inference
* Streaming outputs
* OpenAI-compatible API server
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* Support NVIDIA GPUs and AMD GPUs
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* (Experimental) Prefix caching support
* (Experimental) Multi-lora support
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For more information, check out the following:
* `vLLM announcing blog post <https://vllm.ai> `_ (intro to PagedAttention)
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* `vLLM paper <https://arxiv.org/abs/2309.06180> `_ (SOSP 2023)
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* `How continuous batching enables 23x throughput in LLM inference while reducing p50 latency <https://www.anyscale.com/blog/continuous-batching-llm-inference> `_ by Cade Daniel et al.
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* :ref: `vLLM Meetups <meetups>` .
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Documentation
-------------
.. toctree ::
:maxdepth: 1
:caption: Getting Started
getting_started/installation
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getting_started/amd-installation
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getting_started/cpu-installation
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getting_started/neuron-installation
getting_started/tpu-installation
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getting_started/quickstart
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getting_started/debugging
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getting_started/examples/examples_index
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.. toctree ::
:maxdepth: 1
:caption: Serving
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serving/openai_compatible_server
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serving/deploying_with_docker
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serving/distributed_serving
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serving/metrics
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serving/env_vars
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serving/usage_stats
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serving/integrations
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serving/tensorizer
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.. toctree ::
:maxdepth: 1
:caption: Models
models/supported_models
models/adding_model
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models/engine_args
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models/lora
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models/vlm
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models/spec_decode
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models/performance
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.. toctree ::
:maxdepth: 1
:caption: Quantization
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quantization/auto_awq
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quantization/fp8
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quantization/fp8_e5m2_kvcache
quantization/fp8_e4m3_kvcache
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.. toctree ::
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:maxdepth: 1
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:caption: Automatic Prefix Caching
automatic_prefix_caching/apc
automatic_prefix_caching/details
.. toctree ::
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:caption: Developer Documentation
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dev/sampling_params
dev/offline_inference/offline_index
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dev/engine/engine_index
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dev/kernel/paged_attention
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dev/multimodal/multimodal_index
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dev/dockerfile/dockerfile
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.. toctree ::
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:maxdepth: 1
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:caption: Community
community/meetups
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community/sponsors
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Indices and tables
==================
* :ref: `genindex`
* :ref: `modindex`