Llama 3.1 Instruct 405B

Llama 3.1 405B Instruct is a large-scale dense transformer model developed by Meta, representing the flagship of the Llama 3.1 collection. Released in July 2024, it was trained on more than 15 trillion tokens using a cluster of over 16,000 H100 GPUs. The model is designed for high-level reasoning, multilingual translation, and complex instruction following, rivaling the performance of major proprietary models while maintaining an open-weights approach. It features a decoder-only architecture with a 128,000-token context window and supports eight primary languages. Meta utilized a multi-stage post-training process, including Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF), to optimize the model for tool use and dialogue accuracy. Beyond direct inference, the 405B variant is intended for synthetic data generation and model distillation to assist in the development of smaller, more efficient models.