name: Cohere
aid: cohere
deliveryModel:
  model: unknown
  open_source: false
  commercial: false
  callable_host: true
  label: Delivery model not determined — needs a product licence on record
  confidence: low
  source:
  - openapi
  generated: '2026-08-28'
  method: derived
specificationVersion: '0.23'
accessModel:
  pricing: paid
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Paid
  confidence: medium
  source:
  - plans
  - authentication
  - security
  generated: '2026-09-03'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/cohere.png
url: https://raw.githubusercontent.com/api-evangelist/cohere/refs/heads/main/apis.yml
apis:
- aid: cohere:chat-api
  name: Cohere Chat API
  tags:
  - Artificial Intelligence
  - Chat
  - Conversational AI
  - LLM
  - Text Generation
  tags_raw:
  - Artificial Intelligence
  - Chat
  - Conversational AI
  - Large Language Models
  - Text Generation
  image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
  baseURL: https://api.cohere.com
  humanURL: https://docs.cohere.com/reference/chat
  properties:
  - url: https://docs.cohere.com/reference/chat
    type: Documentation
  - url: openapi/cohere-chat-api-openapi.yml
    type: OpenAPI
  - url: asyncapi/cohere-asyncapi.yml
    type: AsyncAPI
  description: The Cohere Chat API enables developers to integrate large language model text generation
    capabilities into their applications through a conversational interface. It supports multi-turn conversations,
    tool use with JSON schema definitions, retrieval-augmented generation, and streaming responses. The
    API is available via the v2 endpoint and works with Cohere's Command family of models.
- aid: cohere:embed-api
  name: Cohere Embed API
  tags:
  - Artificial Intelligence
  - Embeddings
  - Natural Language Processing
  - Semantic Search
  - Vector Search
  image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
  baseURL: https://api.cohere.com
  humanURL: https://docs.cohere.com/reference/embed
  properties:
  - url: https://docs.cohere.com/reference/embed
    type: Documentation
  - url: openapi/cohere-embed-api-openapi.yml
    type: OpenAPI
  description: The Cohere Embed API generates vector embeddings from text and images, enabling semantic
    search, clustering, and classification use cases. It supports multilingual content and can process
    both text and image inputs using the Embed v3 model family. Developers can use these embeddings to
    build retrieval systems, recommendation engines, and other applications that require understanding
    semantic similarity between content.
- aid: cohere:rerank-api
  name: Cohere Rerank API
  tags:
  - Artificial Intelligence
  - Information Retrieval
  - Relevance
  - Reranking
  - Search
  image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
  baseURL: https://api.cohere.com
  humanURL: https://docs.cohere.com/reference/rerank
  properties:
  - url: https://docs.cohere.com/reference/rerank
    type: Documentation
  - url: openapi/cohere-rerank-api-openapi.yml
    type: OpenAPI
  description: The Cohere Rerank API takes a query and a list of text documents and returns them ordered
    by relevance with assigned relevance scores. It is commonly used as a second-stage ranker in retrieval-augmented
    generation pipelines to improve the quality of search results before passing them to a language model.
    The API supports multilingual reranking and can significantly improve the precision of search and
    retrieval systems.
- aid: cohere:classify-api
  name: Cohere Classify API
  tags:
  - Artificial Intelligence
  - Classification
  - Natural Language Processing
  - Text Analysis
  image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
  baseURL: https://api.cohere.com
  humanURL: https://docs.cohere.com/reference/classify
  properties:
  - url: https://docs.cohere.com/reference/classify
    type: Documentation
  - url: openapi/cohere-classify-api-openapi.yml
    type: OpenAPI
  description: The Cohere Classify API performs text classification by assigning labels to input text
    based on provided examples. It can be used for sentiment analysis, content moderation, topic categorization,
    and other classification tasks. Developers provide a set of labeled examples along with texts to classify,
    and the API returns predicted labels with confidence scores for each input.
- aid: cohere:embed-jobs-api
  name: Cohere Embed Jobs API
  tags:
  - Artificial Intelligence
  - Batch Processing
  - Embeddings
  - Vector Search
  image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
  baseURL: https://api.cohere.com
  humanURL: https://docs.cohere.com/reference/list-embed-jobs
  properties:
  - url: https://docs.cohere.com/reference/list-embed-jobs
    type: Documentation
  - url: openapi/cohere-embed-jobs-api-openapi.yml
    type: OpenAPI
  description: The Cohere Embed Jobs API allows developers to create and manage batch embedding jobs for
    processing large volumes of text data asynchronously. Rather than embedding texts one at a time, developers
    can submit datasets for bulk embedding and monitor job progress. This is useful for initializing vector
    databases, processing large document collections, and other scenarios where embedding large amounts
    of content is needed.
- aid: cohere:datasets-api
  name: Cohere Datasets API
  tags:
  - Artificial Intelligence
  - Data Management
  - Datasets
  - Fine-Tuning
  image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
  baseURL: https://api.cohere.com
  humanURL: https://docs.cohere.com/reference/list-datasets
  properties:
  - url: https://docs.cohere.com/reference/list-datasets
    type: Documentation
  - url: openapi/cohere-datasets-api-openapi.yml
    type: OpenAPI
  description: The Cohere Datasets API provides endpoints for uploading, managing, and retrieving datasets
    used with other Cohere services such as fine-tuning and embed jobs. Developers can create datasets
    from files, list existing datasets, retrieve dataset metadata, and delete datasets they no longer
    need. The API supports various data formats and validates uploaded data against expected schemas.
- aid: cohere:models-api
  name: Cohere Models API
  tags:
  - Artificial Intelligence
  - Machine Learning
  - Models
  tags_raw:
  - Artificial Intelligence
  - Machine Learning
  - Models
  - Machine-Learning
  image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
  baseURL: https://api.cohere.com
  humanURL: https://docs.cohere.com/reference/list-models
  properties:
  - url: https://docs.cohere.com/reference/list-models
    type: Documentation
  - url: openapi/cohere-models-api-openapi.yml
    type: OpenAPI
  description: The Cohere Models API allows developers to list and retrieve information about available
    Cohere models, including the Command, Embed, and Rerank model families. It provides details such as
    model names, versions, supported endpoints, context lengths, and capabilities. This API is useful
    for programmatically discovering which models are available and selecting the appropriate model for
    a given task.
- aid: cohere:tokenize-api
  name: Cohere Tokenize API
  tags:
  - Artificial Intelligence
  - Natural Language Processing
  - Text Processing
  - Tokenization
  image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
  baseURL: https://api.cohere.com
  humanURL: https://docs.cohere.com/reference/tokenize
  properties:
  - url: https://docs.cohere.com/reference/tokenize
    type: Documentation
  - url: openapi/cohere-tokenize-api-openapi.yml
    type: OpenAPI
  description: The Cohere Tokenize API splits input text into tokens using the tokenizer associated with
    a specified model. It returns both the token strings and their corresponding token IDs. This is useful
    for understanding how text will be processed by Cohere models, estimating token counts for billing
    purposes, and debugging input formatting issues.
- aid: cohere:detokenize-api
  name: Cohere Detokenize API
  tags:
  - Artificial Intelligence
  - Natural Language Processing
  - Text Processing
  - Tokenization
  image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
  baseURL: https://api.cohere.com
  humanURL: https://docs.cohere.com/reference/detokenize
  properties:
  - url: https://docs.cohere.com/reference/detokenize
    type: Documentation
  - url: openapi/cohere-detokenize-api-openapi.yml
    type: OpenAPI
  description: The Cohere Detokenize API converts a sequence of token IDs back into their corresponding
    text string using the tokenizer for a specified model. It is the inverse operation of the Tokenize
    API and is useful for inspecting model outputs at the token level, debugging tokenization behavior,
    and reconstructing text from token representations.
common:
- type: CapabilityMap
  url: capabilities/cohere-capability-edges.yml
  name: Cohere Business Capability Map
- type: RateLimits
  url: rate-limits/cohere-rate-limits.yml
- type: FinOps
  url: finops/cohere-finops.yml
- type: Pricing
  url: https://cohere.com/pricing
- type: Plans
  url: plans/cohere-plans-pricing.yml
- type: Website
  url: https://www.cohere.com/
- type: AgenticAccess
  url: agentic-access/cohere-agentic-access.yml
- type: DomainSecurity
  url: security/cohere-domain-security.yml
- type: Authentication
  url: authentication/cohere-authentication.yml
- url: https://cohere.com/blog
  type: Blog
- type: GitHubOrganization
  url: https://github.com/cohere-ai
- type: LinkedIn
  url: https://www.linkedin.com/company/cohere-ai
- type: JSONLD
  url: json-ld/cohere-context.jsonld
- type: JSONSchema
  url: json-schema/cohere-chat-message-schema.json
- type: JSONSchema
  url: json-schema/cohere-embedding-schema.json
- type: JSONSchema
  url: json-schema/cohere-model-schema.json
- type: JSONSchema
  url: json-schema/cohere-dataset-schema.json
- type: Features
  data:
  - Command at $1/$2 per MTok input/output
  - Command-light at $0.30/$0.60
  - Command R at $0.50/$1.50
  - Command R+ 08-2024 at $2.50/$10
  - Command R+ 04-2024 at $3/$15
  - Aya Expanse multilingual at $0.50/$1.50
  - Embed v3 with English/multilingual
  - Rerank for relevance scoring
  - 'Production keys: 10K req/min Chat, 2K Embed, 10K Rerank'
  - 'Trial keys: 20/min Chat, 100/min Embed'
  - Connectors for RAG over data sources
  - Tool use and function calling
  - Compass for unstructured data search
  - Available on AWS Bedrock, Azure, Oracle Cloud
  - Fine-tuning for Command and Aya
  - OpenAI-compatible Chat Completions endpoint
  sources:
  - https://cohere.com/pricing
  updated: '2026-05-04'
- type: LlmsText
  url: https://docs.cohere.com/llms.txt
modified: '2026-09-16'
description: Generates a text response to a user message and streams it down, token by token.
tags:
- Artificial Intelligence
- Natural Language Processing
- Embeddings
- Vector Search
- LLM
- Canada
- Foundation Models
x-tags-removed:
- Tokenization