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Meta Llama 2 open-source
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4/5
High(4)High quality. Established institution or organization with editorial oversight and accountability.
Rating inherited from publication venue: Meta AI
Meta's Llama models are a leading open-source AI system relevant to AI safety discussions around open-weight model risks, deployment governance, and the implications of widely accessible frontier-capable models.
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Importance: 52/100tool pagehomepage
Summary
Meta's Llama is a family of open-source large language models including Llama 3 and Llama 4 variants, offering multimodal capabilities, extended context windows, and various model sizes for deployment across diverse use cases. The latest Llama 4 models feature native multimodality with early fusion architecture, supporting up to 10M token context windows. Models are freely downloadable and fine-tunable, positioning Llama as a major open-source alternative to proprietary AI systems.
Key Points
- •Llama 4 introduces native multimodality via early fusion, supporting combined text and image understanding with 10M-token context windows.
- •Model family spans multiple sizes (1B to 405B parameters), enabling deployment from edge devices to large-scale infrastructure.
- •Open-source licensing allows fine-tuning, distillation, and deployment anywhere, accelerating broad adoption and third-party development.
- •Includes safety-focused tooling via 'Llama Protections' and the Llama Defenders Program for responsible deployment.
- •Competitive benchmark performance: Llama 4 Maverick scores 80.5 on MMLU Pro and 69.8 on GPQA Diamond at low cost ($0.19–$0.49/Mtok).
Cited by 8 pages
| Page | Type | Quality |
|---|---|---|
| Multipolar Trap Dynamics Model | Analysis | 61.0 |
| AI Proliferation Risk Model | Analysis | 65.0 |
| Meta AI (FAIR) | Organization | 51.0 |
| AI Governance Coordination Technologies | Approach | 91.0 |
| Open Source AI Safety | Approach | 62.0 |
| RLHF | Research Area | 63.0 |
| AI Proliferation | Risk | 60.0 |
| AI Winner-Take-All Dynamics | Risk | 54.0 |
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Industry Leading, Open-Source AI | Llama
Search Documentation Products API Overview API waitlist Login Llama Stack Overview Models Models families Llama 4 Llama 3 Get started Download Learn Resources Cookbook Videos AI at Meta Blog Community Built with Llama Case studies Research AI research community Network Hugging Face GitHub Safety Llama Protections Overview Llama Defenders Program Developer use guide Llama API Stay updated Download models Build on your own terms
Optimized models for easy deployment, cost efficiency, and performance that scale to billions of users. Download models Stay updated MODELS Latest Llama models
The latest models feature native multimodality, advanced reasoning, and industry-leading context windows. Model overview Llama 4
Native multimodality leveraging early fusion to pre-train unlabeled text and vision data enabling a change in intelligence from separate, frozen multimodal weights. More details Llama 4 Maverick Natively multimodal for image and text understanding.
10M-token context for long-form work
Multimodal text + image understanding
For use cases around memory, personalization, and multi-modal applications
More details Download models Llama 4 Scout Natively multimodal offering text and visual intelligence Offers single H100 GPU efficiency
10M context window
For use cases around long document analysis
More details Download models Llama 3
The open-source AI models you can fine-tune, distill and deploy anywhere. Choose from our collection of models: Llama 3.1, Llama 3.2, Llama 3.3. More details Llama 3.3 Multilingual open source large language model.
Available in 70B
Experience 405B performance and quality at a fraction of the cost
Built for text-based use cases such as synthetic data generation
More details Download models Llama 3.2 Flexible, cost-effective, and built for edge use cases. 1B & 3B are lightweight and cost-efficient allowing you to run them anywhere
11B & 90B are flexible multimodal models that can reason on high resolution images and output text
More details Download models Llama 3.1 Open-foundation model built for flexibility and control. Available in 8B, 70B, and 405B sizes
Capabilities in general knowledge, steerability, math, tool use, and multilingual translation
Text summarization, multilingual agents, and coding use cases
More details Download models
Model optimization
Documentation overview Prompt Engineering Used in natural language processing to improve the performance of LLMs. Learn more Fine-tuning Adapting pre-trained models to perform better for a specific use case. Learn more Vision capabilities Letting the model understand and reason over images and text together. Learn more Quantization Used to reduce the computational and memory requirements of models. Learn more Distillation Teaching a smaller model to match a larger model's performance. Learn more Evaluations Automated and manual tests to systematically measure model
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