gpt_academic vs deep-research-ai — Trust Score Comparison
Side-by-side trust comparison of gpt_academic and deep-research-ai. Scores based on security, compliance, maintenance, popularity, and ecosystem signals.
Detailed Metric Comparison
| Metric | gpt_academic | deep-research-ai |
|---|---|---|
| Trust Score | 60.9/100 | 68.5/100 |
| Grade | C | C |
| Stars | 70,114 | 2 |
| Category | research | research |
| Security | 0 | 0 |
| Compliance | 79 | 87 |
| Maintenance | 1 | 1 |
| Documentation | 0 | 1 |
| EU AI Act Risk | minimal | minimal |
| Verified | No | No |
Verdict
deep-research-ai leads with a trust score of 68.5/100 compared to gpt_academic's 60.9/100 (a 7.6-point difference). deep-research-ai scores higher on compliance (87 vs 79). However, gpt_academic has stronger community adoption (70,114 vs 2 stars). Both agents should be evaluated based on your specific requirements.
Detailed Analysis
Security
gpt_academic leads on security with a score of 0/100 compared to deep-research-ai's 0/100. This score reflects dependency vulnerability analysis, known CVE exposure, and security best practices. A higher security score means fewer known vulnerabilities and better security hygiene in the codebase.
Maintenance & Activity
gpt_academic demonstrates stronger maintenance activity (1/100 vs 1/100). This metric captures commit frequency, issue response times, and release cadence. Actively maintained tools receive faster security patches and are less likely to accumulate technical debt.
Documentation
deep-research-ai has better documentation (1/100 vs 0/100). Good documentation reduces onboarding time and helps teams adopt the tool safely. This score evaluates README completeness, API documentation, code examples, and tutorial availability.
Community & Adoption
gpt_academic has 70,114 GitHub stars while deep-research-ai has 2. gpt_academic has significantly broader community adoption, which typically means more Stack Overflow answers, more third-party tutorials, and faster ecosystem development.
When to Choose Each Tool
Choose gpt_academic if you need:
- Larger community (70,114 vs 2 stars)
Choose deep-research-ai if you need:
- Higher overall trust score — more reliable for production use
- Better documentation for faster onboarding
Switching from gpt_academic to deep-research-ai (or vice versa)
When migrating between gpt_academic and deep-research-ai, consider these factors:
- API Compatibility: gpt_academic (research) and deep-research-ai (research) share similar interfaces since they are in the same category.
- Security Review: Run a security audit after migration. Check the gpt_academic safety report and deep-research-ai safety report for known issues.
- Testing: Ensure your test suite covers all integration points before switching in production.
- Community Support: gpt_academic has 70,114 stars and deep-research-ai has 2. Larger communities typically mean better Stack Overflow answers and migration guides.
Related Pages
Frequently Asked Questions
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Last updated: 2026-09-19 | Data refreshed weekly
Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.