TaewoooPark/DRIFT
🧠 One LLM, split across a Mac (Apple MPS) + a Windows PC (NVIDIA CUDA) — heterogeneous pipeline inference over a framework-neutral wire, bit-for-bit identical to single-machine. No torch.distributed, no datacenter.
24
Stars
2
Forks
23.9
Radar Score
Stable
Momentum
Scoring Breakdown
Impact8.5
Velocity27.6
Health43.5
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
95%
High Confidence
Growth pattern looks organic.
License
Permissive (Commercial Friendly)
Safe for commercial use, modification, and distribution.
Health Grade
B
Based on maintenance, issue response, and release cadence.
Radar Score
23.9
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.
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