Best Large Language Models for VESSL AI

Meta AI is our intelligent assistant that allows people to create, connect and get things done. We've integrated Llama 3. Meta AI can be used to code and solve problems, allowing you to see the performance of Llama 3. Llama 3, in 8B or 70B, will give you the flexibility and capabilities you need to create your ideas, whether you're creating AI-powered agents or other applications. We've updated our Responsible Use Guide (RUG), to provide the most comprehensive and up-to-date information on responsible development using LLMs. Our system-centric approach includes updates for our trust and security tools, including Llama Guard 2 optimized to support MLCommons' newly announced taxonomy, code shield and Cybersec Evaluation 2.

Mixtral 8x7B has open weights and is a high quality sparse mixture expert model (SMoE). Licensed under Apache 2.0. Mixtral outperforms Llama 70B in most benchmarks, with 6x faster Inference. It is the strongest model with an open-weight license and the best overall model in terms of cost/performance tradeoffs. It matches or exceeds GPT-3.5 in most standard benchmarks.

Open source AI model that you can fine-tune and distill anywhere. Our latest instruction-tuned models are available in 8B 70B and 405B version. Our open ecosystem allows you to build faster using a variety of product offerings that are differentiated and support your use cases. Choose between real-time or batch inference. Download model weights for further cost-per-token optimization. Adapt to your application, improve using synthetic data, and deploy on-prem. Use Llama components and extend the Llama model using RAG and zero shot tools to build agentic behavior. Use 405B high-quality data to improve specialized model for specific use cases.

Mixtral 8x22B is our latest open model. It sets new standards for performance and efficiency in the AI community. It is a sparse Mixture-of-Experts model (SMoE), which uses only 39B active variables out of 141B. This offers unparalleled cost efficiency in relation to its size. It is fluently bilingual in English, French Italian, German and Spanish. It has strong math and coding skills. It is natively able to call functions; this, along with the constrained-output mode implemented on La Plateforme, enables application development at scale and modernization of tech stacks. Its 64K context window allows for precise information retrieval from large documents. We build models with unmatched cost-efficiency for their respective sizes. This allows us to deliver the best performance-tocost ratio among models provided by the Community. Mixtral 8x22B continues our open model family. Its sparse patterns of activation make it faster than any 70B model.

There are now more versions of the open-source AI model that you can refine, distill and deploy anywhere. Choose from 1B or 3B, or build with Llama 3. Llama 3.2 consists of a collection large language models (LLMs), which are pre-trained and fine-tuned. They come in sizes 1B and 3B, which are multilingual text only. Sizes 11B and 90B accept both text and images as inputs and produce text. Our latest release allows you to create highly efficient and performant applications. Use our 1B and 3B models to develop on-device applications, such as a summary of a conversation from your phone, or calling on-device features like calendar. Use our 11B and 90B models to transform an existing image or get more information from a picture of your surroundings.

Gemma is the family of lightweight open models that are built using the same research and technology as the Gemini models. Gemma was developed by Google DeepMind, along with other teams within Google. The name is derived from the Latin gemma meaning "precious stones". We're also releasing new tools to encourage developer innovation, encourage collaboration, and guide responsible use of Gemma model. Gemma models are based on the same infrastructure and technical components as Gemini, Google's largest and most powerful AI model. Gemma 2B, 7B and other open models can achieve the best performance possible for their size. Gemma models can run directly on a desktop or laptop computer for developers. Gemma is able to surpass much larger models in key benchmarks, while adhering our rigorous standards of safe and responsible outputs.

Gemini models are a family of light-open, state-of-the art models that was created using the same research and technology as Gemini models. These models include comprehensive security measures, and help to ensure responsible and reliable AI through selected data sets. Gemma models have exceptional comparative results, even surpassing some larger open models, in their 2B and 7B sizes. Keras 3.0 offers seamless compatibility with JAX TensorFlow PyTorch and JAX. Gemma 2 has been redesigned to deliver unmatched performance and efficiency. It is optimized for inference on a variety of hardware. The Gemma models are available in a variety of models that can be customized to meet your specific needs. The Gemma models consist of large text-to text lightweight language models that have a decoder and are trained on a large set of text, code, or mathematical content.