Model Parallelism Trend 2026

Model parallelism splits a large neural network across multiple devices, with each handling different layers or operations. This technique enables training of massive models that exceed single-GPU memory limits. It benefits researchers and engineers working on LLMs, image generation, or recommendation systems, allowing them to scale computations efficiently while managing hardware constraints.