Models

Llama 3.2 is the latest iteration of Meta's open-source AI model family, offering enhanced capabilities and versatility. The new release includes models of various sizes: 1B, 3B, 11B, and 90B parameters. The 1B and 3B models are lightweight, multilingual, and text-only, designed for efficient deployment on mobile and edge devices. The larger 11B and 90B models are multimodal, capable of processing both text and high-resolution images. Key features of Llama 3.2 include: 1. Improved performance across over 150 benchmark datasets in multiple languages. 2. Multimodal capabilities in larger models for image understanding and visual reasoning. 3. Integration with Llama Stack, providing a streamlined developer experience with support for multiple programming languages and deployment options. 4. Enhanced support for agentic components, including tool calling, safety guardrails, and retrieval augmented generation. 5. Compatibility with various hardware platforms, including ARM, MediaTek, and Qualcomm for mobile and edge devices. Llama 3.2 has garnered significant attention, with over 350 million downloads on Hugging Face alone. It's being utilized across various industries for applications such as data privacy, productivity enhancement, contextual understanding, and solving complex business needs. The ecosystem around Llama continues to grow, with partners like Dell, Zoom, DoorDash, and KPMG leveraging the technology for diverse use cases.

Llama 3.2 is the latest iteration of Meta's open-source AI model family, offering enhanced capabilities and versatility. The new release includes models of various sizes: 1B, 3B, 11B, and 90B parameters. The 1B and 3B models are lightweight, multilingual, and text-only, designed for efficient deployment on mobile and edge devices. The larger 11B and 90B models are multimodal, capable of processing both text and high-resolution images. Key features of Llama 3.2 include: 1. Improved performance across over 150 benchmark datasets in multiple languages. 2. Multimodal capabilities in larger models for image understanding and visual reasoning. 3. Integration with Llama Stack, providing a streamlined developer experience with support for multiple programming languages and deployment options. 4. Enhanced support for agentic components, including tool calling, safety guardrails, and retrieval augmented generation. 5. Compatibility with various hardware platforms, including ARM, MediaTek, and Qualcomm for mobile and edge devices. Llama 3.2 has garnered significant attention, with over 350 million downloads on Hugging Face alone. It's being utilized across various industries for applications such as data privacy, productivity enhancement, contextual understanding, and solving complex business needs. The ecosystem around Llama continues to grow, with partners like Dell, Zoom, DoorDash, and KPMG leveraging the technology for diverse use cases.

Llama 3.2 is the latest iteration of Meta's open-source AI model family, offering enhanced capabilities and versatility. The new release includes models of various sizes: 1B, 3B, 11B, and 90B parameters. The 1B and 3B models are lightweight, multilingual, and text-only, designed for efficient deployment on mobile and edge devices. The larger 11B and 90B models are multimodal, capable of processing both text and high-resolution images. Key features of Llama 3.2 include: 1. Improved performance across over 150 benchmark datasets in multiple languages. 2. Multimodal capabilities in larger models for image understanding and visual reasoning. 3. Integration with Llama Stack, providing a streamlined developer experience with support for multiple programming languages and deployment options. 4. Enhanced support for agentic components, including tool calling, safety guardrails, and retrieval augmented generation. 5. Compatibility with various hardware platforms, including ARM, MediaTek, and Qualcomm for mobile and edge devices. Llama 3.2 has garnered significant attention, with over 350 million downloads on Hugging Face alone. It's being utilized across various industries for applications such as data privacy, productivity enhancement, contextual understanding, and solving complex business needs. The ecosystem around Llama continues to grow, with partners like Dell, Zoom, DoorDash, and KPMG leveraging the technology for diverse use cases.

The Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out). The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.

The Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out). The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.

The Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out). The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.

Meta's latest class of model (Llama 3) launched with a variety of sizes & flavors. This 70B instruct-tuned version was optimized for high quality dialogue usecases. It has demonstrated strong performance compared to leading closed-source models in human evaluations. To read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).

Meta's latest class of model (Llama 3) launched with a variety of sizes & flavors. This is the base 70B pre-trained version. It has demonstrated strong performance compared to leading closed-source models in human evaluations. To read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).

Meta's latest class of model (Llama 3) launched with a variety of sizes & flavors. This is the base 8B pre-trained version. It has demonstrated strong performance compared to leading closed-source models in human evaluations. To read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).

Meta's latest class of model (Llama 3) launched with a variety of sizes & flavors. This 8B instruct-tuned version was optimized for high quality dialogue usecases. It has demonstrated strong performance compared to leading closed-source models in human evaluations. To read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).

Code Llama is built upon Llama 2 and excels at filling in code, handling extensive input contexts, and folling programming instructions without prior training for various programming tasks.

The flagship, 70 billion parameter language model from Meta, fine tuned for chat completions. Llama 2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align to human preferences for helpfulness and safety.

This safeguard model has 8B parameters and is based on the Llama 3 family. Just like is predecessor, [LlamaGuard 1](https://huggingface.co/meta-llama/LlamaGuard-7b), it can do both prompt and response classification. LlamaGuard 2 acts as a normal LLM would, generating text that indicates whether the given input/output is safe/unsafe. If deemed unsafe, it will also share the content categories violated. For best results, please use raw prompt input or the `/completions` endpoint, instead of the chat API. It has demonstrated strong performance compared to leading closed-source models in human evaluations. To read more about the model release, [click here](https://ai.meta.com/blog/meta-llama-3/). Usage of this model is subject to [Meta's Acceptable Use Policy](https://llama.meta.com/llama3/use-policy/).

Code Llama is a family of large language models for code. This one is based on [Llama 2 70B](/models/meta-llama/llama-2-70b-chat) and provides zero-shot instruction-following ability for programming tasks.

Llama3 Sonar is Perplexity's latest model family. It surpasses their earlier Sonar models in cost-efficiency, speed, and performance. This is a normal offline LLM, but the [online version](/models/perplexity/llama-3-sonar-large-32k-online) of this model has Internet access.

Llama3 Sonar is Perplexity's latest model family. It surpasses their earlier Sonar models in cost-efficiency, speed, and performance. This is the online version of the [offline chat model](/models/perplexity/llama-3-sonar-large-32k-chat). It is focused on delivering helpful, up-to-date, and factual responses. #online

Llama3 Sonar is Perplexity's latest model family. It surpasses their earlier Sonar models in cost-efficiency, speed, and performance. This is a normal offline LLM, but the [online version](/models/perplexity/llama-3-sonar-small-32k-online) of this model has Internet access.

Llama3 Sonar is Perplexity's latest model family. It surpasses their earlier Sonar models in cost-efficiency, speed, and performance. This is the online version of the [offline chat model](/models/perplexity/llama-3-sonar-small-32k-chat). It is focused on delivering helpful, up-to-date, and factual responses. #online

A fine-tune of CodeLlama-34B on an internal dataset that helps it exceed GPT-4 on some benchmarks, including HumanEval.

The flagship, 70 billion parameter language model from Meta, fine tuned for chat completions. Llama 2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align to human preferences for helpfulness and safety.