AI Platform

Fine Tune & Train AI Models, Develop Applications and Unleash the Power of AI on Hybrid GPU Cloud

AI is exciting but complex. Too many tools and models. Hard to get started, expensive and difficult to extract business value. Qubrid AI a single platform to get started in minutes and features No-setup/No-Code/Low-Code RAG/Fine-Tuning on optimized GPUs, curated AI models, drag & drop workflows etc. Rapidly develop use-cases and commercial applications. Designed for hybrid GPU cloud infrastructure, Qubrid AI platform can be installed on your local GPU Servers or you can simply logon to our public GPU cloud platform to get started and build AI applications now!

Try AI models to generate images, create content or launch Jupyter Notebook for fine-tuning on compute instances in our CPU & GPU Cloud for free (No credit card required).

AI Model Studio

Train, Fine-tune and Deploy Generative AI & LLM Models – Stable Diffusion, Llama, Mistral, Falcon, Yolo, Gemma and other AI Models.

Pre-trained Models

Jumpstart your project with a library of industry-leading models for tasks like image recognition, natural language processing, and more

Frictionless Model Building

Craft your own custom models with a user-friendly, code-optional interface

Advanced Training and Tuning

Fine-tune pre-trained models or your own creations with robust optimization tools and access to high-performance compute resources

Seamless Deployment

Integrate trained models into your applications with a few clicks, accelerating the path to market

Instantly Demo & See Your AI Model in Action

# pip install bits and bytes accelerate 
from diffusers import StableDiffusionXLPipeline, StableDiffusionXLImg2 ImgPipeline import torch
pipeline = StableDiffusionXLPipeline.from_pretrained ( "stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True) .to ("cuda") 
refiner = StableDiffusionXLImg2ImgPipeline.from_pretrained("stable-   diffusion-xl-refiner-1.0", torch_dtype=torch.float16, use_safetensors= True, variant="fp16") .to ("cuda") 
input_text = "a photo of an astronaut riding a horse on mars"

Browse Catalog

AI Compute Platform

Flexible Infrastructure Options – Workload Orchestration Across GPU, CPU, QPU Cloud

Choose from a diverse range of on-demand compute instances for general development
Optimized inference GPUs for lightning-fast model deployment
Cutting-edge NVIDIA, AMD and Intel GPUs specifically designed for training and tuning large language models
Cutting-edge access to quantum simulations across various GPUs, supporting up to 1000 qubits for those exploring the future of computing
On-demand access to real quantum computing resources (first-come, first-served)

On-Demand or Reserve Cloud Instances

Focus on innovation, not infrastructure costs. GPU Cloud – Pay only for the resources you use, scaling up or down as your projects evolve.

Deploy AI applications or simulate Quantum programs on GPUs
Reserve access to ‘hard to get’ GPUs such as NVIDIA GH200, H200, H100, A100 etc
On-demand access to GPUs such as NVIDIA Tesla T4, V100 etc
Scale from single GPU to thousands of GPUs for Generative AI and LLM applications
Free basic compute (CPU) for AI/ML or Quantum simulation
Flexible plans – from hourly to monthly to annual plans

Try Now

AI Data Connector

Tools and Resources to Transform Raw Data into Fuel for Your AI Models

“The Qubrid Platform has shown outstanding performance and reliability in various computational tasks. In higher dimensional matrix multiplication, it displayed a smooth increase in execution time while consistently producing accurate results, demonstrating its efficiency in handling complex mathematical operations. Similarly, in evaluating large linear regression models, the platform proved its ability to deliver stable and reliable performance, a critical factor for predictive analytics and data modeling. Overall, the Qubrid Platform stands out in its ability to manage diverse computational tasks with stability, accuracy, and scalability.”

AI Researcher, Rochester University