Video Demo: How Does Model Compression Change AI Reasoning?

In this video, I benchmark Mistral-7B-Instruct-v0.2 on an NVIDIA H200 DigitalOcean GPU in three formats: FP16, INT8, and 4-bit AWQ — and test how precision impacts reasoning quality, speed, VRAM usage, and real serving density. We’ll cover: 👉 What quantization actually does to model weights 👉 Where reasoning starts breaking down (FP16 → INT8 → 4-bit) 👉 Why memory savings don’t always reduce total GPU usage in vLLM 👉 Tokens/sec vs aggregate throughput 👉 When 4-bit wins — and when it doesn’t...