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features
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support

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Description

The Qualcomm AI Hub serves as a comprehensive resource center for developers focused on creating and implementing AI applications that are specifically optimized for Qualcomm chipsets. It features a vast collection of pre-trained models, an array of development tools, and tailored SDKs for various platforms, facilitating efficient, low-power AI processing across a range of devices, including smartphones and wearables, as well as edge devices. Additionally, the hub provides a collaborative environment where developers can share insights and innovations, further enhancing the ecosystem of AI solutions.

Description

Accelerate the building, training, and deployment of models at scale through a fully managed infrastructure that provides essential tools and streamlined workflows. Launch personalized AI and LLMs on any infrastructure in mere seconds, effortlessly scaling inference as required. Tackle your most intensive tasks with batch job scheduling, ensuring you only pay for what you use on a per-second basis. Reduce costs effectively by utilizing GPU resources, spot instances, and a built-in automatic failover mechanism. Simplify complex infrastructure configurations by deploying with just a single command using YAML. Adjust to demand by automatically increasing worker capacity during peak traffic periods and reducing it to zero when not in use. Release advanced models via persistent endpoints within a serverless architecture, maximizing resource efficiency. Keep a close eye on system performance and inference metrics in real-time, tracking aspects like worker numbers, GPU usage, latency, and throughput. Additionally, carry out A/B testing with ease by distributing traffic across various models for thorough evaluation, ensuring your deployments are continually optimized for performance.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS) No 
FLUX.1 No 
FLUX.2 No 
Gemma 2 No 
IBM watsonx Yes 
Kubernetes No 
Llama 3 No 
Llama 3.1 No 
Llama 3.2 No 
Mistral AI Yes 
Mixtral 8x22B No 
Mixtral 8x7B No 
MusicGen No 
NetsPresso Yes 
ONNX Yes 
Pinecone No 
Stable Diffusion No 
TensorFlow Yes 
Visual Studio Code No 

Integrations

Amazon Web Services (AWS) Yes 
FLUX.1 Yes 
FLUX.2 Yes 
Gemma 2 Yes 
IBM watsonx No 
Kubernetes Yes 
Llama 3 Yes 
Llama 3.1 Yes 
Llama 3.2 Yes 
Mistral AI No 
Mixtral 8x22B Yes 
Mixtral 8x7B Yes 
MusicGen Yes 
NetsPresso No 
ONNX No 
Pinecone Yes 
Stable Diffusion Yes 
TensorFlow No 
Visual Studio Code Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$100 + compute/month
Free Trial No 
Free Version Yes 

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) No 
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

Qualcomm

Country

United States

Website

aihub.qualcomm.com

Vendor Details

Company Name

VESSL AI

Founded

2020

Country

United States

Website

vessl.ai/

Product Features

Artificial Intelligence

Chatbot No 
For Healthcare No 
For Sales No 
For eCommerce No 
Image Recognition No 
Machine Learning No 
Multi-Language No 
Natural Language Processing No 
Predictive Analytics No 
Process/Workflow Automation No 
Rules-Based Automation No 
Virtual Personal Assistant (VPA) No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Alternatives

Alternatives