Average Ratings 0 Ratings
Average Ratings 0 Ratings
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.
Description
gpu.nz is a service that provides cloud-based GPU rentals tailored for developers, machine-learning professionals, researchers, and creators who require immediate computing power for tasks such as AI inference, model training, image and video creation, and rendering. Users can assess various GPU options based on model, memory capacity, geographical location, and hourly pricing, and subsequently initiate servers with pre-established configurations including tools like ComfyUI, Stable Diffusion Forge, Ollama with Open WebUI, vLLM, PyTorch, and Jupyter, or opt for a personalized Docker image. GPU usage is charged by the minute from a preloaded balance, with a fixed rate established at the moment a server is activated; halting the server stops the GPU fees while disk storage continues to incur charges. Additionally, the platform offers a web console, a REST API, a command-line interface, and a hosted Model Context Protocol server to facilitate both manual and automated processes for searching, launching, and managing servers. This comprehensive system ensures that users have the flexibility and tools necessary to optimize their computing tasks effectively.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
Docker
Yes
Claude Code
No
Claude Desktop
No
Codex CLI
No
Compute with Hivenet
Yes
DashboardGPT
Yes
DocsGPT
Yes
KServe
Yes
Kubernetes
Yes
LFM3
Yes
Integrations
Docker
Yes
Claude Code
Yes
Claude Desktop
Yes
Codex CLI
Yes
Compute with Hivenet
No
DashboardGPT
No
DocsGPT
No
KServe
No
Kubernetes
No
LFM3
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$0.067/hour
GPU rental is billed per minute from an account balance at the hourly rate for the selected server; the rate is fixed when the server starts. A $2 minimum top-up applies. Stopping a server ends GPU charges, but disk storage remains billable. Data transfer is billed per gigabyte. Prices and availability vary by offer.
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
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
vLLM
Country
United States
Website
vllm.ai
Vendor Details
Company Name
Transtrade
Founded
2026
Country
Kyrgyzstan
Website
gpu.nz/en