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NVIDIA/TensorRT-LLM

Coolingrank #193

TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.

15k+29 · 7d 2.9k 134est. NOASSERTIONPythonpushed 5m ago
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Composite

63

conf 65%

Momentum

43

conf 60%

Vitality (PVI)

75

conf 67%

Community

62

conf 60%

Security & maint.

77

conf 85%

Ecosystem influence

69

conf 60%

Opportunity

65

conf 60%

Breakout · 7d

20%

conf 71%

Executive summary

TensorRT-LLM is currently classified as cooling with a composite score of 63/100. Momentum (43) and vitality (75) are aligned — growth is backed by sustained maintenance. Estimated 7-day gain of 29 stars against a 15k-star base. Risk is assessed as low; the interpretable model puts its probability of entering the top trend cohort within 7 days at 20%.

90-day trajectory

+162 · 30d
2026-07-302026-10-27

Score breakdown

Every input, weight and normalized value — nothing hidden. Inputs marked est. are estimated until the full ingestion pipeline lands.

Momentum

Star velocityest.25%41
Star accelerationest.15%38
Fork velocityest.10%25
Contributor growthest.10%64
Issue activity growthest.10%67
PR activity growthest.10%49
External mention velocityest.10%2
Release event impactest.5%78
Trending-rank persistenceest.5%55

Model tn-interpretable-1.0.0 · confidence 60% · coverage 100%

Project Vitality Index

Commit consistency20%100
Release cadenceest.15%79
PR responsivenessest.15%77
Issue responsivenessest.15%41
Contributor diversityest.10%79
Maintainer continuityest.10%77
Documentation qualityest.5%88
Dependency freshnessest.5%50
Security hygieneest.5%60

Model tn-interpretable-1.0.0 · confidence 67% · coverage 92% · missing: licenseClarity

Security & maintenance

Release recency25%100
License clarity20%30
Maintenance status25%100
Dependency stalenessest.15%42
Bus factorest.15%99

Model tn-interpretable-1.0.0 · confidence 85% · coverage 100%

Ecosystem influence

Dependent repositoriesest.30%85
Quality-weighted dependentsest.20%73
Documentation citationsest.15%78
Contributor overlapest.15%30
Registry adoptionest.10%34
Topic centralityest.10%92

Model tn-interpretable-1.0.0 · confidence 60% · coverage 92% · missing: packageRegistryAdoption