How to train a Language Model with Megatron-LM

Megatron-LM is NVIDIA's open-source framework for training large models using tensor, pipeline, and sequence parallelism across GPU clusters. It requires explicit configuration of parallelism strategies and gradient checkpointing before any run starts.

Teams on A100/H100 clusters typically default to DeepSpeed ZeRO-3, which stalls past 30B parameters without tuning. Megatron-LM's 3D parallelism cuts per-GPU memory 60–70% at that scale. Treating DeepSpeed as a universal answer past 13B is how training budgets get torched.

Teams doing full-parameter pre-training above 13B should benchmark Megatron-LM against their current stack. LoRA and QLoRA fine-tuners on single nodes can skip it entirely.