14 GB — That's How Much a 7B Model Weighs in FP16. In 4-bit Quantization — Just 4. That's the Difference You Need to Calculate

🚀 14 GB — that's how much a 7B model weighs in FP16. In 4-bit quantization — just 4. That's the difference you need to calculate before buying a GPU, rather than hoping for headroom for the future. In free lessons, you'll learn how to estimate VRAM for a specific LLM: what quantization gives you, how Ollama, llama.cpp, and vLLM differ, and why the same model might either fit in 8 GB or require 24. This isn't theory — it's a practical checklist you can use to check your configuration right away. Bottom line: calculate first, buy later. Otherwise, you risk overpaying for a card that will never run at full capacity. 🔗 Read on habr.com #LLM #GPU #LocalLLMs #GPU #AI #NeuralNetworks Habr Running an LLM Locally: What to Calculate Before Buying a GPU? Hi everyone, my name is Sergey Proshchaev, I'm a Tech Lead and head of Java/Kotlin development in FinTech & E-commerce, and I teach development and architecture courses at OTUS....

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