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Average Ratings 0 Ratings

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ease
features
design
support

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Description

Intel’s Gaudi software provides developers with an extensive array of tools, libraries, containers, model references, and documentation designed to facilitate the creation, migration, optimization, and deployment of AI models on Intel® Gaudi® accelerators. This platform streamlines each phase of AI development, encompassing training, fine-tuning, debugging, profiling, and enhancing performance for generative AI (GenAI) and large language models (LLMs) on Gaudi hardware, applicable in both data center and cloud settings. The software features current documentation that includes code samples, best practices, API references, and guides aimed at maximizing the efficiency of Gaudi solutions such as Gaudi 2 and Gaudi 3, while also ensuring compatibility with widely-used frameworks and tools for model portability and scalability. Users have access to performance metrics to evaluate training and inference benchmarks, can leverage community and support resources, and benefit from specialized containers and libraries designed for high-performance AI workloads. Furthermore, Intel's commitment to ongoing updates ensures that developers remain equipped with the latest advancements and optimizations for their AI projects.

Description

vLLM is an advanced library tailored for the efficient inference and deployment of Large Language Models (LLMs). Initially created at the Sky Computing Lab at UC Berkeley, it has grown into a collaborative initiative enriched by contributions from both academic and industry sectors. The library excels in providing exceptional serving throughput by effectively handling attention key and value memory through its innovative PagedAttention mechanism. It accommodates continuous batching of incoming requests and employs optimized CUDA kernels, integrating technologies like FlashAttention and FlashInfer to significantly improve the speed of model execution. Furthermore, vLLM supports various quantization methods, including GPTQ, AWQ, INT4, INT8, and FP8, and incorporates speculative decoding features. Users enjoy a seamless experience by integrating easily with popular Hugging Face models and benefit from a variety of decoding algorithms, such as parallel sampling and beam search. Additionally, vLLM is designed to be compatible with a wide range of hardware, including NVIDIA GPUs, AMD CPUs and GPUs, and Intel CPUs, ensuring flexibility and accessibility for developers across different platforms. This broad compatibility makes vLLM a versatile choice for those looking to implement LLMs efficiently in diverse environments.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon EC2 Yes 
Database Mart No 
Docker No 
DocsGPT No 
Hugging Face No 
IONOS Cloud GPU Servers Yes 
Intel Tiber AI Cloud Yes 
KServe No 
Kubernetes No 
Muse Spark Open No 
NGINX No 
NVIDIA DRIVE No 
Nemotron 3.5 Bolt No 
Nemotron 3.5 Super VL No 
OpenAI No 
PyTorch No 
Thunder Compute No 
omp No 

Integrations

Amazon EC2 No 
Database Mart Yes 
Docker Yes 
DocsGPT Yes 
Hugging Face Yes 
IONOS Cloud GPU Servers No 
Intel Tiber AI Cloud No 
KServe Yes 
Kubernetes Yes 
Muse Spark Open Yes 
NGINX Yes 
NVIDIA DRIVE Yes 
Nemotron 3.5 Bolt Yes 
Nemotron 3.5 Super VL Yes 
OpenAI Yes 
PyTorch Yes 
Thunder Compute Yes 
omp Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Intel

Founded

1968

Country

United States

Website

www.intel.com/content/www/us/en/developer/platform/gaudi/overview.html

Vendor Details

Company Name

vLLM

Country

United States

Website

vllm.ai

Product Features

Product Features

Alternatives

Alternatives

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