ahtx/kindi
Kindi 0.5: local LLM inference on low-cost NVIDIA GPUs (Kepler to the RTX 50 series and the CMP 170HX), AMD Radeon 780M, 840M and 8060S, and CPUs. Bonsai 2B-27B, AH-Nanbeige4.3-33B and experimental Nemotron, with an OpenAI-compatible server.
157
Stars
36
Forks
0.0
Radar Score
Declining
Momentum
Scoring Breakdown
Impact0.0
Velocity0.0
Health0.0
Growth Metrics
7-Day Stars
+0
30-Day Stars
+0
Acceleration
x
Language
Python
Popular Alternatives & Competitors
Top projects in the same category (LLM Frameworks) — compare side by side.
🛡️ Enterprise Readiness & Commercial Safety
Organic Growth
98%
High Confidence
License
AGPL-3.0
Review license terms carefully before commercial adoption.
Health Grade
C
Based on maintenance, issue response, and release cadence.
Radar Score
0.0
Composite of Impact, Velocity, and Health.
Disclaimer: This is an automated heuristic assessment based on public GitHub signals. Always perform your own security audit, dependency review, and legal compliance check before production deployment.
Share & Embed
Display live Radar metrics in your documentation, website, or social profiles.