Exa
Semantic Scholar
| Feature | Exa | Semantic Scholar |
|---|---|---|
| Pricing | Free / from $100/mo | Free only |
| Free Plan | ✓ Yes | ✓ Yes |
| Rating | 4.2 / 5 | 4.4 / 5 |
| Best For | ai-developers, researchers, data-scientists, startup-builders | researchers, phd-students, academics, literature-reviewers |
| Founded | 2022 | 2015 |
| Neural Search | ✓ | ✗ |
| Content Retrieval | ✓ | ✗ |
| Similarity Search | ✓ | ✗ |
| Filtering | ✓ | ✗ |
| Auto Search | ✓ | ✗ |
| Api Access | ✓ | ✗ |
| Semantic Search | ✗ | ✓ |
| Tldr Summaries | ✗ | ✓ |
| Citation Graphs | ✗ | ✓ |
| Research Feeds | ✗ | ✓ |
| Author Profiles | ✗ | ✓ |
| Open Api | ✗ | ✓ |
✓ Exa Pros
- Semantic search beyond keywords
- Clean API for developers
- Returns full page content
- Excellent for AI agent use cases
✗ Exa Cons
- Developer-focused - no consumer product
- Free tier has limited requests
- Results can be unpredictable
✓ Semantic Scholar Pros
- Completely free to use
- AI-generated paper summaries (TLDR)
- Influence and citation metrics
- Research feeds and alerts
✗ Semantic Scholar Cons
- Coverage gaps in some disciplines
- No full-text access
- Interface less intuitive than Google Scholar
The Verdict
Exa is built for ai developers and researchers, with a focus on neural-search and content-retrieval. Semantic Scholar targets researchers and phd students and leads with semantic-search and tldr-summaries.
Semantic Scholar uses custom enterprise pricing, while Exa starts at $100/mo — a tangible advantage for teams with a fixed budget.
Both offer free plans, so you can test each with your real workflow before committing to a subscription.
Both tools are a solid fit for researchers — in those cases, the decision often comes down to workflow style and how your team prefers to organize work.
This is a genuinely close comparison. If you can, sign up for both free trials (where available) and run a one-week test with your actual team tasks before deciding.