With the LLaMA 4 series, Meta AI continues its successful open source model development and launches a new generation of powerful language models. Building on the experience gained from LLaMA 3 and the further developments in LLaMA 3.1 and 3.3, LLaMA 4 aims for even deeper language understanding capabilities, better multi-turn communication and fine-tuned controllability. The models combine enhanced context understanding with optimized efficiency and offer an attractive basis for demanding applications in research, industry and product development – openly accessible and future-oriented.
LLaMA 4 series (includes LLaMA 4 Scout, LLaMA 4 Maverick, LLaMA 4 Behemoth)
Meta AI
April 5, 2025
Open-Weight. The license is aimed at enabling developers and companies to use it.
Native multimodal language models based on a Mixture-of-Experts (MoE) architecture. The models are designed from the ground up for processing text, images and videos.
We would be happy to advise you individually on which AI model suits your requirements. Arrange a no-obligation initial consultation with our AI experts and exploit the full potential of AI for your project!
LLaMA 4 was trained on an extremely large and diverse database: Over 30 trillion tokens from publicly accessible text, image and video data form the basis of the pre-training. A novel, three-stage post-training process was used for the Instruct and Chat variants: first a light supervised fine-tuning (SFT), followed by online reinforcement learning with an adaptive data filter and finally direct preference optimization (DPO).
A special focus was placed on mastering particularly difficult prompts, which were specifically incorporated into the training pipeline via continuous RL. Within the series, the LLaMA 4 Maverick model was trained using codistillation from its more powerful sister model LLaMA 4 Behemoth – a targeted transfer of knowledge for high efficiency with reduced resource consumption.
Is LLaMA 4 the right AI model for your individual application? We will be happy to advise you comprehensively and personally.
Top performance: Competitive or superior to models such as GPT-4o, Gemini 2.0 and others in benchmarks for coding, reasoning and image understanding.
Outstanding efficiency: The MoE architecture offers a first-class performance to cost ratio.
Extreme context length: Opens up completely new application possibilities.
Native multimodal: Designed from the ground up for the joint processing of different data modalities.
Open-Weight & Open Source: Promotes transparency, security and innovation through the community.
Improved security & bias reduction: Comprehensive safeguards and demonstrable reduction of bias on controversial topics.
High hardware requirements: Despite the efficiency, powerful GPUs are still required for the inference of the larger models.
General LLM risks: Potential for hallucination, bias and generation of inappropriate content remains, even if mitigation measures have been taken.
Complexity of the architecture: MoE models can be more demanding to handle and fine-tune than traditional dense models.
Availability: The most powerful model, LLaMA 4 Behemoth, is not publicly available.
Whether you need a powerful Instruct variant or an efficient codistilled model, the LLaMA 4 series offers flexible options for complex applications. We support you with the selection, integration and secure hosting – individually tailored to your requirements.
