Cohere vs Yi
Which Model Provider is right for you? See our complete breakdown.
| Feature | Cohere | Yi |
|---|---|---|
| MegaOne Score | 8/10 | 6/10 |
| Category | Model Provider | Open Source Model |
| Pricing Model | Paid Only | Freemium |
| Starting Price | $0.04/mo | $0.14/mo |
| Free Tier | Yes | Yes |
| API Available | No | Yes |
| Open Source | No | Yes |
| iOS App | No | No |
| Android App | No | No |
| Chrome Extension | No | No |
| Company | Cohere Inc. | 01.AI |
| Total Funding | $1.7B | $300M |
Visual Comparison
About Cohere
Cohere provides enterprise-grade large language models and a platform for building AI applications, focusing on secure and flexible deployment for businesses.
Cohere specializes in large language models (LLMs) and AI products tailored for enterprise customers, particularly in regulated industries like finance, healthcare, manufacturing, and government. Its platform offers generative AI capabilities for tasks such as chatbots, search engines, copywriting, summarization, and agentic workflows. Cohere emphasizes retrieval-augmented generation (RAG) and flexible deployment options, including on-premises, private cloud, and cloud-agnostic configurations, to address data security and sovereignty requirements.
About Yi
01.AI offers a series of open-source large language models and enterprise AI solutions, including the Yi-Lightning model, designed to enhance productivity and decision-making.
01.AI develops open-source large language models and full-stack enterprise AI solutions, including the Yi series. Its flagship Yi-Lightning model, a 100B-parameter Mixture-of-Experts (MoE) model, is known for its competitive performance and smart routing capabilities, dynamically selecting between Yi-Lightning, DeepSeek-V3, and Qwen3-30B-A3B for optimal latency and cost. The company aims to enhance human productivity through its AI platforms, decision intelligence tools, and AI transformation services for enterprises.
Cohere takes the edge
With a MegaOne score of 8/10 versus 6/10, Cohere edges ahead of Yi in our analysis. However, Yi may still be the better choice depending on your specific use case and budget.