Head-to-Head Comparison

Cohere vs Yi

Which Model Provider is right for you? See our complete breakdown.

Cohere

8/10 Our Pick Visit Cohere
VS

Yi

6/10 Visit Yi
FeatureCohereYi
MegaOne Score8/106/10
CategoryModel ProviderOpen Source Model
Pricing ModelPaid OnlyFreemium
Starting Price$0.04/mo$0.14/mo
Free TierYesYes
API AvailableNoYes
Open SourceNoYes
iOS AppNoNo
Android AppNoNo
Chrome ExtensionNoNo
CompanyCohere Inc.01.AI
Total Funding$1.7B$300M

Visual Comparison

Score Reach Value Team Funding Reviews
Cohere Yi

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.