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In this video, I'll be telling you about Nvidia's New Nemotron-70B Model by Nvidia. They claim that this model beats Claude 3.5 Sonnet, GPT-4O, Gemini & Others). They also claim that It is even better in Coding Tasks and is also really good at doing Text-To-Application, Text-To-Frontend and other things as well. I'll be testing it to find out if it can really beat other LLMs and i'll also be telling you that how you can use it.
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Key Takeaways:
🎯 Nemotron Model Shakes the Internet
Nemotron, fine-tuned from Llama-3.1 by Nvidia, is creating massive buzz online with its incredible AI benchmarks and performance.
🚀 Outperforms Leading AI Models
According to benchmarks, Nemotron outshines Claude 3.5 Sonnet, Llama-3.1 405b, and GPT-4O, showing it could be one of the best AI models yet.
💻 Open Weights & Free API Access
With open-source availability on Ollama, HuggingFace, and Nvidia's NIMs, plus a free API with 1,000 credits, anyone can test this AI model.
🔍 Skepticism Around Benchmarks
Not all benchmarks are trustworthy. Aider's results suggest Nemotron isn't as groundbreaking as it seems, falling behind the original Llama-3.1.
💰 Token Usage Could Cost You
While Nemotron matches Llama-3.1 in pricing per token, its high token consumption could significantly increase your overall costs in AI deployment.
🧠 Chain of Thought Built-In
Nemotron’s built-in Chain of Thought improves reasoning but leads to higher inference costs, making it more expensive to run in AI applications.
🏆 A Cool Model, But Not a Game-Changer
While Nemotron is impressive, its similarity to Llama-3.1 means it's not revolutionary. For users with hardware, Llama-3.1 remains a better choice for now.
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Timestamps:
00:00 - Introduction
00:13 - About Nemotron
01:36 - Testing
06:22 - Final Results & Charts
08:14 - Ending
