Peter Kanage

Introducing Willow, our new state-of-the-art quantum computing chip with a breakthrough that can reduce errors exponentially as we scale up using more qubits, cracking a 30-year challenge in the field. In benchmark tests, Willow solved a standard computation in <5 mins that would take a leading supercomputer over 10^25 years, far beyond the age of the universe(!).

Mechazilla has caught the Super Heavy booster!

Combined, training these lightweight Llama models required 916K GPU hours on NVIDIA H100-80GB. As part of Meta’s commitment starting in 2020, we’ve maintained net zero greenhouse gas emissions in our global operations and matched 100% of the electricity use from the training operations with renewable energy. Because we’re releasing these models openly, the training energy use and greenhouse gas emissions will not need to be incurred by others.

A few technical insights on the new Llama vision models we’re releasing today 🦙🧵

📣 Introducing Llama 3.2: Lightweight models for edge devices, vision models and more! What’s new? • Llama 3.2 1B & 3B models deliver state-of-the-art capabilities for their class for several on-device use cases — with support for @Arm, @MediaTek & @Qualcomm on day one. • Llama 3.2 11B & 90B vision models deliver performance competitive with leading closed models — and can be used as drop-in replacements for Llama 3.1 8B & 70B. • New Llama Guard models to support multimodal use cases and edge deployments. • The first official distro of Llama Stack simplifies and supercharges the way developers & enterprises can build around Llama to support agentic applications and more. Details in the full announcement ➡️ go.fb.me/229ug4 Download Llama 3.2 models ➡️ go.fb.me/w63yfd These models are available to download now directly from Meta and @HuggingFace — and will be available across offerings from 25+ partners that are rolling out starting today, including @accenture, @awscloud, @AMD, @azure, @Databricks, @Dell, @Deloitte, @FireworksAI_HQ, @GoogleCloud, @GroqInc, @IBMwatsonx, @Infosys, @Intel, @kaggle, @NVIDIA, @OracleCloud, @PwC, @scale_AI, @snowflakeDB, @togethercompute and more. With Llama 3.2 we’re making it possible to run Llama in even more places, with even more flexible capabilities. We’ve said it before and we’ll say it again: open source AI is how we ensure that these innovations reflect the global community they’re built for and benefit everyone. We’re continuing our drive to make open source the standard with Llama 3.2.