EXPLORE MODELS

Meta Llama 3.1 is a collection of advanced, multilingual large language models designed for dialogues, available in 8B, 70B, and 405B sizes, that outperform many chat models on industry benchmarks and emphasize safe, responsible use in various applications.

Meta Llama 3.1 is a collection of advanced, multilingual large language models designed for dialogues, available in 8B, 70B, and 405B sizes, that outperform many chat models on industry benchmarks and emphasize safe, responsible use in various applications.

The Meta Llama 3.1 collection consists of high-performing, multilingual large language models optimized for dialogue and capable of handling text and code across 8 languages, available in 8B, 70B, and 405B parameter sizes, with a focus on safety, inclusivity, and societal benefit.

The Meta Llama 3.1 collection consists of high-performing, multilingual large language models optimized for dialogue and capable of handling text and code across 8 languages, available in 8B, 70B, and 405B parameter sizes, with a focus on safety, inclusivity, and societal benefit.

Meta's Llama 3.3 is a 70B parameter multilingual instruction-tuned language model designed for dialogue use, outperforming many open and closed-source models and incorporating safety features such as supervised fine-tuning and reinforcement learning with human feedback.

Meta's Llama 3.3 is a 70B parameter multilingual instruction-tuned language model designed for dialogue use, outperforming many open and closed-source models and incorporating safety features such as supervised fine-tuning and reinforcement learning with human feedback.

Llama 3.2 is a multilingual large language model collection from Meta, fine-tuned for dialogue and summarization tasks in multiple languages, designed for enhanced retrieval and conversational agents.

Llama 3.2 is a multilingual large language model collection optimized for dialogue, retrieval, and summarization tasks with enhanced performance on industry benchmarks, employing supervised fine-tuning and reinforcement learning for safety and human-aligned responses.

Llama 3.2-Vision, developed by Meta, is a state-of-the-art multimodal language model optimized for image recognition, reasoning, and captioning, surpassing both open and closed models in industry benchmarks.

Mistral-NeMo-12B-Instruct is a 12-billion-parameter multilingual large language model designed for English-language chat applications, featuring impressive multilingual and code comprehension, with customization options via NVIDIA's NeMo Framework.

DeepSeek-V3 is a 671 billion parameter Mixture-of-Experts (MoE) language model optimized for efficiency and performance, demonstrating superior results across various benchmarks through innovative strategies and extensive pre-training on high-quality data.

DeepSeek-R1 is an open-source first-generation reasoning model leveraging large-scale reinforcement learning to achieve state-of-the-art performance in math, code, and reasoning tasks, and includes distilled models suitable for various applications.

Qwen2.5-72B-Instruct is a state-of-the-art multilingual large language model with enhanced capabilities in knowledge, coding, mathematics, and long-context processing, offering improved instruction-following and structured data handling with a 72 billion parameter architecture.

UnslopNemo v4.1 is the latest addition from the creator of Rocinante, designed for adventure writing and role-play scenarios.

Rocinante 12B v1.1 is a versatile language model designed for creative and engaging storytelling, offering enhanced prose and rich vocabulary for a dynamic adventure experience.

MythoMax-L2 is an enhanced variant of MythoMix designed for coherent roleplaying and storywriting, utilizing a unique tensor merge technique to blend robust understanding and extensive writing capabilities.