Choosing the right GPU can feel daunting if you don’t understand what’s under the hood. Today’s graphics processing units are far more than just “graphics” cards. They’re sophisticated, multi-faceted compute platforms designed to excel at a wide array of tasks—from rendering lifelike imagery in real time to training massive AI models in record time.

In this post, we’ll break down the different core types inside modern NVIDIA GPUs, explain various precision modes, and show you how to choose the right configuration for your specific workloads—whether you’re researching AI, running a data center, developing HPC applications, or all three.

The rapid advancement of artificial intelligence and machine learning has made GPU selection more critical than ever. NVIDIA's H100 and A100 GPUs stand at the forefront of this evolution, offering unprecedented performance for complex AI workloads. In this article we explore the specifications, performance metrics, and value propositions to help you make an informed decision.

While the H100 leads in performance, dramatic market changes have made it the clear choice for most AI workloads. H100 cloud pricing has plummeted from $8/hour to $2.85-$3.50/hour due to increased availability and provider competition. This pricing shift has effectively eliminated the A100's previous cost advantage, making the H100's superior performance (2-3x faster for most workloads) the deciding factor. Combined with the A100's limited availability and the upcoming B200 release in early 2025, organizations are increasingly standardizing on H100 for their AI infrastructure.

LLMs have taken the tech community by storm. There are many types of LLM models out there. Recently I came across a particular type of models called Uncensored LLM models. In this blog post, I would like to share my learnings with you on what are foundational models, how chat-based models like ChatGPT are built on them and what are uncensored models.

Remember when 32GB of GPU VRAM seemed like a luxury? I sure do. Back in my Kaggle competition days, I was desperately trying to get my hands on a V100 with its "massive" 32GB VRAM. AWS had them, but by the time I cleared their quota hurdles, the competition was long over. Fast forward to 2025, and those numbers feel almost laughable.

Here's the short answer if you're in a hurry...

The Nvidia H200 costs $30 k–$40 k to buy outright and $3.72–$10.60 per GPU hour to rent (May 2025). Jarvislabs offers on‑demand H200 at $3.80/hr—cheapest single‑GPU access.

Looking for the most accurate and up-to-date NVIDIA H100 GPU pricing information? This guide covers everything from purchase costs to cloud pricing trends in 2025.

Quick Summary of NVIDIA H100 Price Guide 2025:

• Direct Purchase Cost: Starting at ~$25,000 per GPU; multi-GPU setups can exceed $400,000.
• Cloud GPU Pricing: Hourly rates range from $2.99 (Jarvislabs) to $9.984 (Baseten).
• Infrastructure Costs: Consider additional expenses like power, cooling, networking, and racks.
• Key Choices: PCIe vs SXM versions; choose based on workload, budget, and infrastructure capabilities.
• Future Trends: Prices are expected to stabilize in 2025 with potential discounts from new GPU releases.