Llama 3.2 11B

Today, we’re releasing Llama 3.2, which includes small and medium-sized vision LLMs (11B and 90B), and lightweight, text-only models (1B and 3B) that fit onto edge and mobile devices, including pre-trained and instruction-tuned versions. Supported by a broad ecosystem, the Llama 3.2 11B and 90B vision models are drop-in replacements for their corresponding text model equivalents, while exceeding on image understanding tasks compared to closed models, such as Claude 3 Haiku. Unlike other open multimodal models, both pre-trained and aligned models are available to be fine-tuned for custom applications using torchtune and deployed locally using torchchat. They’re also available to try using our smart assistant, Meta AI. We’re sharing the first official Llama Stack distributions, which will greatly simplify the way developers work with Llama models in different environments, including single-node, on-prem, cloud, and on-device, enabling turnkey deployment of retrieval-augmented generation (RAG) and tooling-enabled applications with integrated safety. We’ve been working closely with partners like AWS, Databricks, Dell Technologies, Fireworks, Infosys, and Together AI to build Llama Stack distributions for their downstream enterprise clients. On-device distribution is via PyTorch ExecuTorch, and single-node distribution is via Ollama. We continue to share our work because we believe openness drives innovation and is good for developers, Meta, and the world. Llama is already leading the way on openness, modifiability, and cost efficiency—enabling more people to have creative, useful, and life-changing breakthroughs using generative AI. We’re making Llama 3.2 models available for download on llama.com and Hugging Face, as well as available for immediate development on our broad ecosystem of partner platforms, including AMD, AWS, Databricks, Dell, Google Cloud, Groq, IBM, Intel, Microsoft Azure, NVIDIA, Oracle Cloud, Snowflake, and more.