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What is NetApp AIPod?

NetApp AIPod offers a comprehensive solution for AI infrastructure that streamlines the implementation and management of artificial intelligence tasks. By integrating NVIDIA-validated turnkey systems such as the NVIDIA DGX BasePODâ„¢ with NetApp's cloud-connected all-flash storage, AIPod consolidates analytics, training, and inference into a cohesive and scalable platform. This integration enables organizations to run AI workflows efficiently, covering aspects from model training to fine-tuning and inference, while also emphasizing robust data management and security practices. With a ready-to-use infrastructure specifically designed for AI functions, NetApp AIPod reduces complexity, accelerates the journey to actionable insights, and guarantees seamless integration within hybrid cloud environments. Additionally, its architecture empowers companies to harness AI capabilities more effectively, thereby boosting their competitive advantage in the industry. Ultimately, the AIPod stands as a pivotal resource for organizations seeking to innovate and excel in an increasingly data-driven world.

What is DeepInfer?

DeepInfer is an open-source framework tailored for running DeepSeek language models on Linux systems equipped with compatible NVIDIA or Huawei Ascend accelerators. It boasts a range of features intended to streamline offline inference and enhance model performance, such as optimized kernels, distributed parallelism, asynchronous batch scheduling, speculative decoding, and the creation of structured outputs in formats including JSON Schema, regular expressions, and EBNF. The documentation for the project includes support details for DeepSeek-V4.1-Flash, along with thorough instructions for building, configuring, and utilizing various examples and evaluation tools. Targeted at developers and infrastructure teams, it aids in the development or evaluation of self-managed inference deployments. Furthermore, the repository emphasizes that for production environments, additional components like KV-cache, prefill/decode disaggregation, and load-balancing mechanisms may be necessary, making users conscious of possible extra requirements as they implement the framework. In summary, DeepInfer not only optimizes the deployment of language models across diverse applications but also caters to both essential and sophisticated operational needs, making it a versatile tool for developers. This framework ultimately encourages innovation in language processing and model deployment strategies.

Media

Media

Integrations Supported

NVIDIA DIGITS

Integrations Supported

API Availability

API Availability

Has API

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS

Supported Platforms

On-Prem
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

NetApp

Date Founded

1992

Company Location

United States

Company Website

www.netapp.com/artificial-intelligence/aipod/

Company Facts

Organization Name

DeepSeek

Date Founded

2023

Company Location

China

Company Website

github.com/deepseek-ai/DeepInfer

Categories and Features

AI Inference

Not specified

AI Infrastructure

Not specified

AI/ML Model Training

Not specified

Data Management

Not specified

Deep Learning

Not specified

Categories and Features

AI Inference

Not specified

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