Llama 3 8B Instruct by Meta

Llama 3 70B Instruct

Llama is a 70 billion parameter open source model by Meta fine-tuned for instruction following purposes. Served by Groq with their custom Language Processing Units (LPUs) hardware to provide fast and efficient inference.

Llama 3.1 70B Instruct

An update to Meta Llama 3 70B Instruct that includes an expanded 128K context length, multilinguality and improved reasoning capabilities.

Llama 3.1 8B

Llama 3.1 8B brings powerful performance in a smaller, more efficient package. With improved multilingual support, tool use, and a 128K context length, it enables sophisticated use cases like interactive agents and compact coding assistants while remaining lightweight and accessible.

Llama 3.2 11B Vision Instruct

Instruction-tuned image reasoning generative model (text + images in / text out) optimized for visual recognition, image reasoning, captioning and answering general questions about the image.

Llama 3.2 1B Instruct

Text-only model, supporting on-device use cases such as multilingual local knowledge retrieval, summarization, and rewriting.

Llama 3.2 3B Instruct

Text-only model, fine-tuned for supporting on-device use cases such as multilingual local knowledge retrieval, summarization, and rewriting.

Llama 3.2 90B Vision Instruct

Instruction-tuned image reasoning generative model (text + images in / text out) optimized for visual recognition, image reasoning, captioning and answering general questions about the image.

Llama 3.3 70B

The upgraded Llama 3.1 70B model features enhanced reasoning, tool use, and multilingual abilities, along with a significantly expanded 128K context window. These improvements make it well-suited for demanding tasks such as long-form summarization, multilingual conversations, and coding assistance.

Llama 4 Maverick 17B 128E Instruct

High-efficiency language processing

Llama 4 Scout

The Llama-4-Scout-17B-16E-Instruct model is a state-of-the-art, instruction-tuned, multimodal AI model developed by Meta as part of the Llama 4 family. It is designed to handle both text and image inputs, making it suitable for a wide range of applications, including conversational AI, code generation, and visual reasoning.