- Developers & Engineers: Handle massive text/code/video datasets, build advanced assistants, perform multimodal reasoning.
- Researchers & Analysts: Summarize entire books, analyze multimedia documents, and run code-heavy tasks within one prompt.
- Enterprise & API Users: Integrate through Meta AI, Vertex AI, AWS SageMaker, Databricks, or Hugging Face.
- Content & Language Teams: Process multilingual content, image-based QA, and translation across 12+ languages.
- Open-Source Community: Download Scout and Maverick to experiment and build applications (with certain usage restrictions).
How to Use Meta Llama 4?
- Access the Models: Scout and Maverick are available via Meta’s platforms and Hugging Face; Behemoth will be released from LlamaCon.
- Choose a Variant: Use Scout for extreme long-context tasks, Maverick for balanced reasoning & multimodal use, or await Behemoth for peak performance.
- Input Text or Images: Models accept mixed modalities with context windows up to 10M tokens (Scout) or 1M tokens (Maverick).
- Run Tasks: Perform summarization, coding, document analysis, image question answering, or complex reasoning.
- Deploy Safely: Use Llama Guard, Prompt Guard, and watermarked outputs as available; comply with license for larger platforms.
- Mixture-of-Experts Efficiency: Only relevant expert subnetworks are activated, enabling high performance with fewer resources.
- Record Context Windows: Scout supports up to 10 million tokens; no other open model approaches this scale.
- Native Multimodality: Joint training on text, images, and video enables coherent understanding across media types.
- Benchmark-Topping: Maverick rivals GPT-4o, Gemini 2.0 Flash, and DeepSeek-V3 on reasoning, code, and image tasks. Scout outperforms peers in efficiency benchmarks.
- Open-Weight with Guardrails: Scout and Maverick weights are publicly available (with usage limits); safety features include content filters and watermarking.
- Long-context support up to 10 million tokens
- Superior multimodal performance with joint text-image/video
- Efficient architecture yields strong performance per compute
- Open-source access fosters innovation
- Strong safety tooling with Llama Guard and watermarking
- Behemoth is still in development—limited for now
- License restricts commercial use for very large platforms
- Early releases may exhibit inconsistencies or minor artifacts
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Editorial Note
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