Meta has launched Llama 4, its latest open-weight AI suite, featuring multimodality with models like Llama 4 Scout, Llama 4 Behemoth and Llama 4 Maverick.
The Llama 4 series includes three models :
Llama 4 Scout: Efficient, runs on a single GPU, with a 10 million token context window, excelling in long-context tasks.
Llama 4 Maverick: Flagship model with strong coding support, a 1 million token context window, and excellent image and text understanding across 12 languages.
Llama 4 Behemoth: A powerful teacher model (288 billion parameters) currently in training, outperforming models like GPT-4.5 on STEM benchmarks.
What the Benchmarks says:
The Mixture-of-Experts (MoE) architecture allows these models to achieve high performance with fewer active parameters.
Llama 4 offers several key advancements :
Native Multimodality: Understands and processes text and images together.
Mixture-of-Experts (MoE) Architecture: Enhances efficiency by activating only a fraction of parameters.
Massive Context Window: Up to 10 million tokens in the Scout model.
Enhanced Multilingual Understanding: Trained on over 30 trillion tokens across 200 languages.
Advanced Reasoning and Coding Skills: Maverick shows strong coding performance, rivaling DeepSeek v3.1 in some evaluations.
Llama 4 demonstrates significant progress over its predecessors, Llama 2 and 3, in several key areas, including multimodality and context window size. Benchmarks show Llama 4 Scout outperforming models like Gemma 3 and Mistral 3.1. Llama 4 Maverick has shown comparable performance to DeepSeek v3.1 in reasoning and coding, even surpassing GPT-4o and Gemini 2.0 Flash in certain evaluations . The experimental chat version of Maverick achieved a notable ELO score on the LMArena benchmark. Furthermore, Llama 4 Behemoth has outperformed top-tier models like GPT-4.5 on STEM benchmarks. Performance benchmarks for different hardware configurations are available, showcasing the efficiency of Llama 4 .
Here is the link to find the llama 4 models:
https://huggingface.co/collections/meta-llama/llama-4-67f0c30d9fe03840bc9d0164**
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