Subscribe for free access to 
Data Points!
Meta launched two new Llama 4 multimodal models, boasting performance improvements over previous generations and 10 million token context windows. Llama 4 Maverick, with 400 billion parameters, outperforms GPT-4o and matches DeepSeek v3.1 on several benchmarks, including MMMU and MathVista, with strong performance on MMLU-Pro’s reasoning tasks, GPQA Diamond’s expert-level knowledge, and LiveCodeBench coding tests. Meta’s team distilled both Maverick and Scout (a 109 billion parameter variant) from Llama 4 Behemoth, a not-yet-available 2 trillion parameter model that reportedly outperforms GPT-4.5 and other top models on STEM tasks. Developers can download Scout’s and Maverick’s weights from llama.com and Hugging Face, while Maverick costs an estimated $0.19-$0.495 per million tokens for inference. (Meta)