Meta Hands Over a 405 Billion Parameter Model You Can Run Yourself
Meta released Llama 3.1 405B as fully open weights with a commercial license, allowing anyone to download and run the model on their own hardware or rented GPUs. The release includes instruction tuned and base versions plus a new Llama Stack toolkit for local inference. Quantized versions run on a single 8xH100 node or on consumer grade 4090 cards with 4 bit quantization.
Teams gain the ability to keep data inside their own infrastructure instead of sending it to third party APIs. This changes cost calculations from per token pricing to electricity and hardware budgets. The result is greater control over model behavior and the option to fine tune without vendor approval.
Together AI has already deployed Llama 3.1 405B on its platform and reports inference costs 60 percent lower than comparable closed models for high volume coding workloads. Independent researchers on Hugging Face have published 4 bit GGUF versions that achieve 35 tokens per second on a single RTX 4090.
Step 1: Download the 405B weights from https://huggingface.co/meta-llama/Llama-3.1-405B-Instruct using the Hugging Face CLI. Step 2: Load the model with vLLM or Ollama on an 8xH100 instance or a quantized version on a single 4090. Step 3: Run a local inference script to generate responses without sending any data outside your machine.