The Llama 3.3 70B Instruct is an auto-regressive transformer model designed to follow instructions and complete natural language tasks across a wide range of domains. Built as an instruction-tuned variant, it emphasizes conversational and task-oriented interactions, making it well-suited for chatbots, content generation, and language translation applications. The model supports multilingual dialogue across eight languages including English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai, positioning it as a strong choice for global applications. With a 128k context window and grouped query attention, it handles extended conversations and complex multi-turn interactions efficiently. This model achieves benchmark performance comparable to the much larger Llama 3.1 405B parameter version, offering frontier-level results at a more accessible scale.

Training leveraged a new mix of publicly available online data totaling over 15 trillion tokens, and the model was aligned to human preferences through supervised fine-tuning and reinforcement learning with human feedback. This post-training approach helps the model balance helpfulness with safety considerations. The model is ready for commercial deployment, accelerated by TensorRT-LLM for efficient inference on NVIDIA GPUs, and is available for on-demand inferencing, dedicated hosting, and fine-tuning. It outperforms both Llama 3.1 70B and Llama 3.2 90B on text tasks, making it a practical upgrade for organizations already invested in the Llama ecosystem. As an open-weights model, it provides teams with full control for customization and self-hosted deployment.