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OpenAI vs Cohere: Token Pricing, Speed & Intelligence

Full comparison of OpenAI and Cohere — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.

OpenAI

GPT-4o, o3, and the world's most widely-used AI API

OpenAI is the creator of the GPT model family and the ChatGPT product. Their API provides access to frontier models including GPT-4o, the o-series reasoning models, and the GPT-4.1 long-context family. Pricing is competitive for frontier-tier capability, with prompt caching available on most models.

CodingChatVisionReasoningAgents
Proprietary models

Cohere

Enterprise NLP — Command R+ with retrieval-augmented generation

Cohere focuses on enterprise NLP use cases, particularly retrieval-augmented generation (RAG) and search. Command R+ is their flagship model, optimised for tool use and multi-step reasoning in enterprise workflows. Cohere also offers embedding and reranking models that pair well with their LLMs.

RAGEnterprise searchEmbeddingsTool useMultilingual
Proprietary models

Key metrics

Cheapest input ($/1M)

Cheapest output ($/1M)

Peak throughput

Best latency (TTFT)

Intelligence score

Context window

Live token pricing

Strengths & weaknesses

OpenAI

Largest ecosystem & third-party integrations
Best-in-class function calling & structured outputs
Prompt caching on all major models
o3/o4-mini reasoning models for complex tasks
1M+ token context on GPT-4.1
No open-weight models — full vendor lock-in
Output pricing is among the highest for frontier tier
Rate limits can be restrictive on lower tiers

Cohere

Best-in-class RAG with native grounding and citations
Embedding and reranking models for full search pipeline
Enterprise SLAs and on-premise deployment options
Command R+ optimised for multi-step tool use
Strong multilingual support
Intelligence scores below frontier leaders
Less suitable for creative or general chat tasks
Smaller developer community than OpenAI/Anthropic

Key differentiators

OpenAI

The most widely-integrated LLM API — virtually every AI framework and tool supports OpenAI natively.

Cohere

The only major LLM provider with a complete RAG stack — LLM, embeddings, and reranking — all from one API.

Frequently asked questions

OpenAI FAQs

How much does the OpenAI API cost?

GPT-4o costs $2.50/1M input tokens and $10/1M output tokens. GPT-4o-mini is $0.15/$0.60 per 1M tokens. Prompt caching cuts input costs by 50% on eligible requests.

What is the difference between GPT-4o and o3?

GPT-4o is a fast, multimodal model optimised for chat, vision, and coding. o3 is a reasoning model that uses chain-of-thought to solve complex problems — it is slower and more expensive but significantly more capable on math, science, and hard coding tasks.

Does OpenAI support prompt caching?

Yes. Prompt caching is available on GPT-4o, GPT-4.1, o3, and o4-mini. Cached input tokens are billed at 50% of the standard input price, making long-context and repeated-system-prompt workloads significantly cheaper.

Cohere FAQs

What is Cohere best used for?

Cohere excels at retrieval-augmented generation (RAG), enterprise search, and document processing. Command R+ is optimised for grounded generation with citations, making it ideal for knowledge bases, customer support, and research tools.

Does Cohere offer embedding models?

Yes. Cohere's Embed models are among the best available for semantic search and RAG pipelines. Combined with their Rerank model, you can build a complete search stack using only Cohere's API.

How much does Cohere cost?

Command R+ pricing varies by use case. Cohere offers a free trial tier and enterprise pricing. Check their pricing page for current rates as they vary by model and volume.

Provider resources

OpenAIGPT-4o, o3, and the world's most widely-used AI API

OpenAI is the creator of the GPT model family and the ChatGPT product. Their API provides access to frontier models including GPT-4o, the o-series reasoning models, and the GPT-4.1 long-context family. Pricing is competitive for frontier-tier capability, with prompt caching available on most models.

The most widely-integrated LLM API — virtually every AI framework and tool supports OpenAI natively.

CohereEnterprise NLP — Command R+ with retrieval-augmented generation

Cohere focuses on enterprise NLP use cases, particularly retrieval-augmented generation (RAG) and search. Command R+ is their flagship model, optimised for tool use and multi-step reasoning in enterprise workflows. Cohere also offers embedding and reranking models that pair well with their LLMs.

The only major LLM provider with a complete RAG stack — LLM, embeddings, and reranking — all from one API.

Key strengths compared

OpenAI

  • Largest ecosystem & third-party integrations
  • Best-in-class function calling & structured outputs
  • Prompt caching on all major models

Cohere

  • Best-in-class RAG with native grounding and citations
  • Embedding and reranking models for full search pipeline
  • Enterprise SLAs and on-premise deployment options

Provider category context

OpenAI is a frontier lab, founded in 2015. Cohere is a frontier lab, founded in 2019. Both are frontier lab providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.

How to choose between them

Both OpenAI and Cohere are frontier labs with proprietary models. Choose based on benchmark performance for your specific task: OpenAI leads on largest ecosystem & third-party integrations, while Cohere leads on best-in-class rag with native grounding and citations. For cost-sensitive workloads, compare the cheapest model tier from each provider in the pricing table above — the gap between efficient-tier models is often larger than between flagship models.