GPU-NOW AS A SERVICE

The NVIDIA GeForce RTX 3090, powered by NVIDIA’s Ampere architecture, is a consumer GPU featuring 24GB of GDDR6X VRAM and 328 Tensor Cores. It offers solid performance for AI/ML workloads, content creation, and gaming, making it an excellent option for enthusiasts and solo developers tackling moderately demanding AI tasks.

✅ Training: Delivers solid speed improvements, around 5–15% faster than its predecessor, with 3rd-gen Tensor Cores providing basic support for deep learning.

✅ Fine-Tuning: Provides moderate performance gains, with improvements depending on the model size and task complexity.

✅ Inference: Handles real-time inference for small to medium AI tasks, though the 24GB VRAM may limit its capacity for larger projects.

The NVIDIA GeForce RTX 4090, built on NVIDIA’s Ada Lovelace architecture, is a high-end consumer GPU featuring 24GB of GDDR6X VRAM and 512 Tensor Cores. It significantly boosts compute performance for AI/ML workloads, gaming, and content creation, making it an ideal choice for users requiring both power and efficiency.

✅ Training: Offers up to 50–70% faster speeds than its predecessor, with 4th-gen Tensor Cores optimizing deep learning tasks and accelerating model training.
✅ Fine-Tuning: Provides substantial performance gains, with improvements depending on model complexity and the specific needs of the task.
✅ Inference: Handles real-time inference across a broad range of AI applications, enhanced by high bandwidth. However, the 24GB VRAM may limit the capacity for very large models.

Industry: AI Chatbot Development

Challenge: Traditional chatbots rely on pre-scripted responses and often fail to retrieve real-time information, providing outdated or generic answers.

Solution: AI developers can utilize TeamCloud GPU-Now to build Retrieval-Augmented Generation (RAG)-enhanced chatbots that combine real-time data retrieval with generative AI. By leveraging GPU-accelerated processing, these chatbots can understand complex queries, fetch up-to-date information, and deliver contextually relevant responses at scale.

The NVIDIA RTX 6000 Ada, a professional-grade GPU from NVIDIA’s Ada Lovelace lineup, features 48GB of GDDR6 VRAM and exceptional compute power. It’s designed for demanding tasks like AI, complex simulations, and 3D rendering, offering enhanced precision and capacity for advanced AI/ML users.

✅ Training: Up to 2x faster than its predecessor, with 4th-gen Tensor Cores driving robust deep learning performance and accelerated model training.
✅ Fine-Tuning: Delivers noticeable performance gains, depending on model size and task complexity, making it ideal for large-scale AI models.
✅ Inference: Excels in real-time inference for advanced AI applications, with extra VRAM supporting larger projects.

*Note: The NVIDIA RTX 6000 Ada is available only on Bare Metal GPU instances for top-tier performance.

The NVIDIA H200 NVL, based on NVIDIA’s Hopper architecture, is a datacenter GPU featuring an impressive 141GB of HBM3e VRAM and 528 Tensor Cores. Designed for next-generation AI/ML, high-performance computing (HPC), and enterprise workloads, it provides exceptional computational power and energy efficiency, with enhanced memory capacity and bandwidth.

 AI Training: Achieves up to 5x faster training than its predecessors for large language models (LLMs), leveraging 4th-gen Tensor Cores and the Transformer Engine optimized for deep learning.
 Fine-tuning: Delivers significant performance gains, scaling efficiently with model complexity and task demands, thanks to a 1.5x memory increase over the H100 NVL.
 Inference: Excels in real-time inference for large-scale AI applications, providing up to 1.7x faster performance than the H100 NVL, driven by its 4.8TB/s memory bandwidth and NVLink connectivity.