The original title is "GPUs for AI in 2026: NVIDIA, AMD, Intel Compared"

Short summary

A practical 2026 GPU comparison for local AI inference covering NVIDIA's Blackwell RTX 50-series, AMD's Radeon AI Pro R9700, and Intel's Arc Pro B70. The article argues VRAM capacity and memory bandwidth matter more than peak TOPS for running LLMs locally, provides a VRAM-to-model-size reference table, and assesses software ecosystem maturity across CUDA, ROCm, and oneAPI. CUDA leads in ecosystem breadth; ROCm is now functional for common stacks; Intel trails but is improving.

• •VRAM and memory bandwidth matter more than peak TOPS for local LLM inference
• •NVIDIA CUDA leads ecosystem maturity; AMD ROCm is now solid for PyTorch/llama.cpp/Ollama; Intel oneAPI trails
• •VRAM requirements scale from 8-12 GB for 7B models to multiple GPUs for 120B+ models

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