NVIDIA/Model-Optimizer
A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
5.6k
Stars
806
Forks
70.1
Radar Score
Rising
Momentum
Scoring Breakdown
Impact86.5
Velocity56.0
Health63.8
Growth Metrics
7-Day Stars
+69
30-Day Stars
+288
Acceleration
0.96x
Language
Python
Why it ranks
Strong momentum — adoption is accelerating week over week.
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
Permissive (Commercial Friendly)
Safe for commercial use, modification, and distribution.
Health Grade
A
Based on maintenance, issue response, and release cadence.
Radar Score
70.1
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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