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Command R7B (12-2024) is a small, fast update of the Command R+ model, delivered in December 2024. It excels at RAG, tool use, agents, and similar tasks requiring complex reasoning and multiple steps. Use of this model is subject to Cohere's Usage Policy and SaaS Agreement.

command-r-plus-08-2024 is an update of the Command R+ with roughly 50% higher throughput and 25% lower latencies as compared to the previous Command R+ version, while keeping the hardware footprint the same. Read the launch post here. Use of this model is subject to Cohere's Usage Policy and SaaS Agreement.

Command R+ is a new, 104B-parameter LLM from Cohere. It's useful for roleplay, general consumer usecases, and Retrieval Augmented Generation (RAG). It offers multilingual support for ten key languages to facilitate global business operations. See benchmarks and the launch post here. Use of this model is subject to Cohere's Usage Policy and SaaS Agreement.

Command R+ is a new, 104B-parameter LLM from Cohere. It's useful for roleplay, general consumer usecases, and Retrieval Augmented Generation (RAG). It offers multilingual support for ten key languages to facilitate global business operations. See benchmarks and the launch post here. Use of this model is subject to Cohere's Usage Policy and SaaS Agreement.

command-r-08-2024 is an update of the Command R with improved performance for multilingual retrieval-augmented generation (RAG) and tool use. More broadly, it is better at math, code and reasoning and is competitive with the previous version of the larger Command R+ model. Read the launch post here. Use of this model is subject to Cohere's Usage Policy and SaaS Agreement.

Command-R is a 35B parameter model that performs conversational language tasks at a higher quality, more reliably, and with a longer context than previous models. It can be used for complex workflows like code generation, retrieval augmented generation (RAG), tool use, and agents. Read the launch post here. Use of this model is subject to Cohere's Usage Policy and SaaS Agreement.

Command-R is a 35B parameter model that performs conversational language tasks at a higher quality, more reliably, and with a longer context than previous models. It can be used for complex workflows like code generation, retrieval augmented generation (RAG), tool use, and agents. Read the launch post here. Use of this model is subject to Cohere's Usage Policy and SaaS Agreement.

Command is an instruction-following conversational model that performs language tasks with high quality, more reliably and with a longer context than our base generative models. Use of this model is subject to Cohere's Usage Policy and SaaS Agreement.

Your prompt will be processed by a meta-model and routed to one of dozens of models (see below), optimizing for the best possible output. To see which model was used, visit Activity, or read the model attribute of the response. Your response will be priced at the same rate as the routed model. The meta-model is powered by Not Diamond. Learn more in our docs. Requests will be routed to the following models: - openai/gpt-4o-2024-08-06 - openai/gpt-4o-2024-05-13 - openai/gpt-4o-mini-2024-07-18 - openai/chatgpt-4o-latest - openai/o1-preview-2024-09-12 - openai/o1-mini-2024-09-12 - anthropic/claude-3.5-sonnet - anthropic/claude-3.5-haiku - anthropic/claude-3-opus - anthropic/claude-2.1 - google/gemini-pro-1.5 - google/gemini-flash-1.5 - mistralai/mistral-large-2407 - mistralai/mistral-nemo - deepseek/deepseek-r1 - meta-llama/llama-3.1-70b-instruct - meta-llama/llama-3.1-405b-instruct - mistralai/mixtral-8x22b-instruct - cohere/command-r-plus - cohere/command-r

GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters, it achieves state-of-the-art results in video understanding, image Q&A, OCR, and document parsing, with strong gains in front-end web coding, grounding, and spatial reasoning. It offers a hybrid inference mode: a "thinking mode" for deep reasoning and a "non-thinking mode" for fast responses. Reasoning behavior can be toggled via the reasoning enabled boolean. Learn more in our docs

GLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a more compact parameter size. GLM-4.5-Air also supports hybrid inference modes, offering a "thinking mode" for advanced reasoning and tool use, and a "non-thinking mode" for real-time interaction. Users can control the reasoning behaviour with the reasoning enabled boolean. Learn more in our docs

GLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a more compact parameter size. GLM-4.5-Air also supports hybrid inference modes, offering a "thinking mode" for advanced reasoning and tool use, and a "non-thinking mode" for real-time interaction. Users can control the reasoning behaviour with the reasoning enabled boolean. Learn more in our docs