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About

VLLM is a high-performance library designed to facilitate efficient inference and serving of Large Language Models (LLMs). 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. It offers state-of-the-art serving throughput by efficiently managing attention key and value memory through its PagedAttention mechanism. It supports continuous batching of incoming requests and utilizes optimized CUDA kernels, including integration with FlashAttention and FlashInfer, to enhance model execution speed. Additionally, vLLM provides quantization support for GPTQ, AWQ, INT4, INT8, and FP8, as well as speculative decoding capabilities. Users benefit from seamless integration with popular Hugging Face models, support for various decoding algorithms such as parallel sampling and beam search, and compatibility with NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs, and more.

About

WebLLM is a high-performance, in-browser language model inference engine that leverages WebGPU for hardware acceleration, enabling powerful LLM operations directly within web browsers without server-side processing. It offers full OpenAI API compatibility, allowing seamless integration with functionalities such as JSON mode, function-calling, and streaming. WebLLM natively supports a range of models, including Llama, Phi, Gemma, RedPajama, Mistral, and Qwen, making it versatile for various AI tasks. Users can easily integrate and deploy custom models in MLC format, adapting WebLLM to specific needs and scenarios. The platform facilitates plug-and-play integration through package managers like NPM and Yarn, or directly via CDN, complemented by comprehensive examples and a modular design for connecting with UI components. It supports streaming chat completions for real-time output generation, enhancing interactive applications like chatbots and virtual assistants.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI infrastructure engineers looking for a solution to optimize the deployment and serving of large-scale language models in production environments

Audience

Developers seeking a tool to implement high-performance, in-browser language model inference without relying on server-side processing

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

VLLM
United States
docs.vllm.ai/en/latest/

Company Information

WebLLM
webllm.mlc.ai/

Alternatives

OpenVINO

OpenVINO

Intel

Alternatives

Qwen2.5-1M

Qwen2.5-1M

Alibaba

Categories

Categories

Integrations

OpenAI
Database Mart
Docker
Dolly
Gemma
JSON
KServe
Llama 2
Llama 3.3
Mathstral
Ministral 3B
Mistral NeMo
Mixtral 8x7B
NVIDIA DRIVE
PyTorch
Qwen
RedPajama
Vicuna
Yarn
npm

Integrations

OpenAI
Database Mart
Docker
Dolly
Gemma
JSON
KServe
Llama 2
Llama 3.3
Mathstral
Ministral 3B
Mistral NeMo
Mixtral 8x7B
NVIDIA DRIVE
PyTorch
Qwen
RedPajama
Vicuna
Yarn
npm
Claim VLLM and update features and information
Claim VLLM and update features and information
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