What is BianQue?
47/100
Trust Score (D)
⚠️ Use Caution
BianQue is a health that Chinese medical dialogue model BianQue. It has a Nerq Trust Score of 47/100 (D). 863 GitHub stars. Published by Unknown. Last analyzed October 2026.
Why This Score
- ⚠️ Security: 0/100 — Some security concerns
- ⚠️ Maintenance: 1/100 — Maintenance activity is low
- ⚠️ Community: 863 stars, 0 downloads — Growing community
- ⚠️ Transparency: License: Not specified — No license specified
Trust & Safety Overview
47
TRUST SCORE
D
GRADE
863
STARS
0
DOWNLOADS
What BianQue Does
BianQue is a tool in the health category. Chinese medical dialogue model BianQue. It is published by an independent developer and has no specified license. With 863 GitHub stars and 0 downloads, it has a growing community of users and contributors.
Who Should Use BianQue
BianQue is recommended only for experimental use. Consider alternatives with higher trust scores for production systems.
Details
| Author | Unknown |
|---|---|
| Category | health |
| License | Not specified |
| Type | tool |
| Source | View on GitHub |
| Security Score | 0/100 |
| Activity Score | 1/100 |
How to Get Started
Check the trust score before installing:
curl nerq.ai/v1/preflight?target=scutcyr-bianque
Setup guide · Full safety report · Production review · Is it safe?
Safer Alternatives
| Tool | Trust | Stars |
|---|---|---|
| MedicalGPT | 52 | 4.8K |
| open-health | 52 | 3.8K |
| Awesome-AI4Med | 50 | 2.5K |
| medical-o1-reasoning-SFT | 52 | 1.1K |
| WellAlly-health | 49 | 723 |
Frequently Asked Questions
What is BianQue used for?
BianQue is a health tool. Chinese medical dialogue model BianQue.
Is BianQue free?
License: Check project page. BianQue has 863 GitHub stars.
Is BianQue safe?
BianQue has a Nerq Trust Score of 47/100 (D). Evaluate carefully.
What are alternatives to BianQue?
Top alternatives: MedicalGPT, open-health, Awesome-AI4Med. See full comparison.
Safety Report Is It Safe?
Alternatives Prediction
Trending Leaderboard
Discover MCP Servers
Packages Models
Stats API
Last updated October 2026. Trust scores based on automated analysis of public data.