Perplexity AI vs Cohere
Which one should you choose? Here's how they compare.
| Feature | Perplexity AI | Cohere |
|---|---|---|
| Rating | ★ 4.4 | ★ 4.1 |
| Pricing | $20/mo | API pricing |
| Type | freemium | pay-per-use |
| Company | Perplexity | Cohere |
| Founded | 2022 | 2019 |
Perplexity AI Features
- •Web-sourced answers
- •Citation links
- •Multiple model choices
- •Collections feature
Cohere Features
- •Enterprise LLM
- •RAG
- •Embeddings
- •Classification
Perplexity AI Pros
- ✓Always cites sources
- ✓Real-time web search
- ✓Less hallucination
Perplexity AI Cons
- ✗Requires internet for best results
- ✗Less creative writing ability
- ✗Free tier limited
Cohere Pros
- ✓Enterprise focused
- ✓Good RAG
- ✓Data privacy
Cohere Cons
- ✗Less consumer friendly
- ✗Complex pricing
- ✗Smaller community
The Verdict
Perplexity AI (by Perplexity, founded 2022) and Cohere (by Cohere, founded 2019) both compete in the chatbot space, but they serve slightly different needs. Both tools offer 4 core features, but their strengths differ. Perplexity AI excels at web-sourced answers, whereas Cohere puts more emphasis on rag. However, Perplexity AI has a distinct advantage for Research and Fact-checking. On the other hand, Cohere is better suited for Enterprise AI and RAG systems. Perplexity AI is particularly popular among Researchers and Students, while Cohere tends to attract Enterprises and Developers. Perplexity AI costs $20/mo (freemium), while Cohere is priced at API pricing (pay-per-use). Choose based on which pricing model aligns better with your budget. No tool is perfect. Perplexity AI's main limitation is requires internet for best results, which might be a dealbreaker for some workflows. Meanwhile, Cohere's biggest drawback is less consumer friendly. We recommend Perplexity AI as the stronger overall choice (4.4 vs 4.1). It pulls ahead with stronger web-sourced answers capabilities. However, if your workflow centers on enterprise llm, Cohere remains a highly capable alternative.
- • You prioritize web-sourced answers
- • You prioritize citation links
- • You prioritize enterprise llm
- • You prioritize rag