Model catalog
One endpoint, every model. Compare context windows, capabilities and real per-token pricing side by side, then swap the model string in your request — nothing else changes.
- 472
- Models
- 48
- Providers
- 4
- Free to try
- $0.0001
- Cheapest input / 1M
7 of 472 models
LanguageCommand A
cohere/command-a
Command A is Cohere's most performant model to date, excelling at tool use, agents, retrieval augmented generation (RAG), and multilingual use cases. Command A has a context length of 256K, only requires two GPUs to run, and has 150% higher throughput compared to Command R+ 08-2024.
- Context
- 256K
- In / 1M
- $2.50
- Out / 1M
- $10.00
- Tool use
- Structured output
- open weights
- Embedding
Embed 5 Fast
cohere/embed-v5.0-fast
Cohere's lightweight embedding model optimized for low latency and high throughput in interactive search, agent loops, and high-volume retrieval. Embed 5 Fast supports text, images, and mixed content, over 100 languages, and a 128,000-token context window, with output dimensions from 256 to 2,048. It shares an embedding space with Embed 5 Pro.
- Context
- 128K
- In / 1M
- $0.080
- Out / 1M
- —
- Embedding
Embed 5 Pro
cohere/embed-v5.0-pro
Cohere's most capable embedding model for quality-critical enterprise retrieval across text, images, and mixed content such as PDFs. Embed 5 Pro supports over 100 languages and a 128,000-token context window, with output dimensions from 256 to 2,048. It shares an embedding space with Embed 5 Fast, enabling Pro indexing with Fast querying.
- Context
- 128K
- In / 1M
- $0.120
- Out / 1M
- —
- Reranking
Cohere Rerank 4 Fast
cohere/rerank-v4-fast
A light version of Rerank 4 Pro, this is a multilingual model that allows for re-ranking English and non-english documents and semi-structured data (JSON). This model is better suited for low latency and high throughput use-cases than its pro variant.
- Context
- 32K
- In / 1M
- —
- Out / 1M
- —
- Reranking
Cohere Rerank 4 Pro
cohere/rerank-v4-pro
A multilingual model that allows for re-ranking English and non-english documents and semi-structured data (JSON). This model is better suited for state-of-the-art quality and complex use-cases than its fast variant.
- Context
- 32K
- In / 1M
- —
- Out / 1M
- —
- Embedding
Embed v4.0
cohere/embed-v4.0
A model that allows for text, images, or mixed content to be classified or turned into embeddings.
- Context
- 128K
- In / 1M
- $0.120
- Out / 1M
- —
- Reranking
Cohere Rerank 3.5
cohere/rerank-v3.5
A model that allows for re-ranking English Language documents and semi-structured data (JSON).
- Context
- 4K
- In / 1M
- —
- Out / 1M
- —