Deploy Long-Context Reasoning and Agentic Workflows with MiniMax M3 on NVIDIA Accelerated Infrastructure | NVIDIA Technical Blog

This post details the deployment of MiniMax M3, a 428B parameter multimodal MoE model with 1M-token context, on NVIDIA Blackwell infrastructure. It highlights MiniMax Sparse Attention (MSA) for efficient KV cache access and reduced per-token compute cost. The post provides deployment instructions for TensorRT LLM, SGLang, and vLLM, showcasing performance insights on Blackwell Ultra with up to 10x higher throughput than H100. It also covers scaling with NVIDIA Dynamo for distributed inference and customization with NVIDIA NeMo Framework for fine-tuning (SFT, LoRA) and reinforcement learning, including context parallelism up to 128k tokens.