Meta Releases Less Expensive AI Model Aimed at Open Source Developers

Meta has unveiled a more efficient artificial intelligence (AI) model that could slash computing costs for businesses adopting AI technology.

“Llama 3.3 improves core performance at a significantly lower cost, making it even more accessible to the entire open-source community,” Meta’s Vice President of Generative AI Ahmad Al-Dahle wrote in a Friday (Dec. 6) post on X.

Introducing Llama 3.3 – a new 70B model that delivers the performance of our 405B model but is easier & more cost-efficient to run. By leveraging the latest advancements in post-training techniques including online preference optimization, this model improves core performance at… pic.twitter.com/6oQ7b3Yuzc

— Ahmad Al-Dahle (@Ahmad_Al_Dahle) December 6, 2024

While Google and Amazon recently unveiled systems focused on enhanced capabilities like emotional understanding and video generation, Meta’s new model reduces the computing power needed to run AI models to just 4 gigabytes of memory. The lower requirements could make advanced AI more accessible to smaller businesses, potentially saving money on hardware costs.

Small Can Be Big

Al-Dahle said the new model matches the capabilities of its other larger AI systems while using just 70 billion parameters, down from 405 billion in its predecessor. This reduction means companies could save up to $600,000 in hardware costs, as Llama 3.3 requires only 4 gigabytes of GPU memory compared to nearly 2,000 gigabytes for previous versions.

Al-Dahle noted in his post that the model costs about $0.01 per million tokens to operate. It’s being released as open-source software, though companies with more than 700 million monthly active users must obtain a commercial license.

The model outperformed Amazon’s Nova Pro — released earlier this week as part of a new GenAI suite, with additional coverage below — in multilingual dialogue and reasoning tasks, though Nova Pro maintains an advantage in coding tests. It achieved 91.1% accuracy on multilingual reasoning tasks, supporting languages including English, German, French, Italian, Hindi, Portuguese, Spanish and Thai.

The release comes as tech companies race to reduce the computing resources needed for AI systems, a key factor in their commercial viability. Meta’s shrinking model size while maintaining performance could make advanced AI models more accessible to smaller businesses.

Experts previously told PYMNTS that open-source AI models are closing the gap between businesses and Big Tech’s expensive systems, potentially bringing AI tools within the reach of smaller companies. Open source technology allows anyone to access, modify and share it.

Multiplying AI Models

In other news, Google unveiled on Thursday (Dec. 5) PaliGemma 2, an AI system the company said can understand emotions and context in pictures.

Unlike older systems that simply identify objects in photos, PaliGemma 2 can describe the emotional story behind an image. It comes in three sizes to fit different needs, and the largest version analyzes images using 28 billion parameters.

“PaliGemma 2 generates detailed, contextually relevant captions for images, going beyond simple object identification to describe actions, emotions, and the overall narrative of the scene,” Google wrote in a blog post.

The system also shows promise in specialized tasks. It can interpret medical X-rays and recognize complex chemical formulas. Google has made PaliGemma 2 available to developers through popular AI platforms Hugging Face and Kaggle.

Meanwhile, Amazon has unveiled a new suite of AI models called Nova, signaling its expanded presence in the AI market. Announced Tuesday (Dec. 3) at the AWS conference in Las Vegas, the platform includes Nova Reel for six-second video generation and Nova Canvas for text-to-image creation.

The company said the new models offer improved speed, lower costs and fine-tuning capabilities. Nova Reel will soon support two-minute videos, while Canvas includes watermarking features to prevent misuse.

“Inside Amazon, we have about 1,000 GenAI applications in motion, and we’ve had a bird’s-eye view of what application builders are still grappling with,” said Rohit Prasad, senior vice president of Amazon Artificial General Intelligence, in a news release.

“Our new Amazon Nova models are intended to help with these challenges for internal and external builders, and provide compelling intelligence and content generation while also delivering meaningful progress on latency, cost-effectiveness, customization, information grounding, and agentic capabilities,” Prasad added.