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Llama 4 continues to spread to other inference providers, but it's safe to say the initial release has not been a slam dunk.Read More

On Saturday, Meta released its newest Llama 4 multimodal AI models in a surprise weekend move that caught some AI experts off guard. The announcement touted Llama 4 Scout and Llama 4 Maverick as major advancements, with Meta claiming top performance in their categories and an enormous 10 million token context window for Scout. But so far the open-weights models have received an initial mixed-to-negative reception from the AI community, highlighting a familiar tension between AI marketing and user experience.

"The vibes around llama 4 so far are decidedly mid," independent AI researcher Simon Willison told Ars Technica. Willison often checks the community pulse around open source and open weights AI releases in particular.

While Meta positions Llama 4 in competition with closed-model giants like OpenAI and Google, the company continues to use the term "open source" despite licensing restrictions that prevent truly open use. As we have noted in the past with previous Llama releases, "open weights" more accurately describes Meta's approach. Those who sign in and accept the license terms can download the two smaller Llama 4 models from Hugging Face or llama.com.

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While DeepSeek R1 and OpenAI o1 edge out Behemoth on a couple metrics, Llama 4 Behemoth remains highly competitive.Read More

Meta has released a new collection of AI models, Llama 4, in its Llama family — on a Saturday, no less. There are four new models in total: Llama 4 Scout, Llama 4 Maverick, and Llama 4 Behemoth. All were trained on “large amounts of unlabeled text, image, and video data” to give them “broad […]