OpenAI's most advanced multimodal model in the GPT-4 family. Can handle both text and image inputs.

An affordable, efficient AI solution for diverse text and image tasks.

Smaller, faster, and 80% cheaper than o1-preview, performs well at code generation and small context operations.

Focused on advanced reasoning and solving complex problems, including math and science tasks. Ideal for applications that require deep contextual understanding and agentic workflows.

Text-embedding-3 series models are the latest and most capable embedding model from OpenAI.

Text-embedding-3 series models are the latest and most capable embedding model from OpenAI.

A new mixture of experts model

Refresh of Phi-3-mini model.

Refresh of Phi-3-vision model.

Same Phi-3-medium model, but with a larger context size for RAG or few shot prompting.

A 14B parameters model, proves better quality than Phi-3-mini, with a focus on high-quality, reasoning-dense data.

Same Phi-3-mini model, but with a larger context size for RAG or few shot prompting.

Tiniest member of the Phi-3 family. Optimized for both quality and low latency.

Same Phi-3-small model, but with a larger context size for RAG or few shot prompting.

A 7B parameters model, proves better quality than Phi-3-mini, with a focus on high-quality, reasoning-dense data.

A 398B parameters (94B active) multilingual model, offering a 256K long context window, function calling, structured output, and grounded generation.

A 52B parameters (12B active) multilingual model, offering a 256K long context window, function calling, structured output, and grounded generation.

A production-grade Mamba-based LLM model to achieve best-in-class performance, quality, and cost efficiency.

Command R is a scalable generative model targeting RAG and Tool Use to enable production-scale AI for enterprise.

Command R is a scalable generative model targeting RAG and Tool Use to enable production-scale AI for enterprise.

Command R+ is a state-of-the-art RAG-optimized model designed to tackle enterprise-grade workloads.

Command R+ is a state-of-the-art RAG-optimized model designed to tackle enterprise-grade workloads.

Cohere Embed English is the market's leading text representation model used for semantic search, retrieval-augmented generation (RAG), classification, and clustering.

Cohere Embed Multilingual is the market's leading text representation model used for semantic search, retrieval-augmented generation (RAG), classification, and clustering.

Excels in image reasoning capabilities on high-res images for visual understanding apps.

Advanced image reasoning capabilities for visual understanding agentic apps.

The Llama 3.1 instruction tuned text only models are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.

The Llama 3.1 instruction tuned text only models are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.

The Llama 3.1 instruction tuned text only models are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.

A powerful 70-billion parameter model excelling in reasoning, coding, and broad language applications.

A versatile 8-billion parameter model optimized for dialogue and text generation tasks.

Mistral Nemo is a cutting-edge Language Model (LLM) boasting state-of-the-art reasoning, world knowledge, and coding capabilities within its size category.

Mistral's flagship model that's ideal for complex tasks that require large reasoning capabilities or are highly specialized (Synthetic Text Generation, Code Generation, RAG, or Agents).

Mistral Large (2407) is an advanced Large Language Model (LLM) with state-of-the-art reasoning, knowledge and coding capabilities.

Mistral Small can be used on any language-based task that requires high efficiency and low latency.