- 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
This page was researched and written by the ATB Editorial Team. Our team researches each AI tool by reviewing its official website, testing features, exploring real use cases, and considering user feedback. Every page is fact-checked and regularly updated to ensure the information stays accurate, neutral, and useful for our readers.
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