FINDING #7634 · UNIT ID 679366051
NVIDIA/TensorRT-LLM
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.
SURPRISE SCORE
0.00
Score Breakdown
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
0% OF STARS IN ARCHIVE
Growth Telemetry
VELOCITY /D
6.67
ACCEL
+3.50
RETENTION
0.0%
PEAK 2026-10-12 · FORK-RETENTION 0.0% · 20 STARS / WINDOW
Author Audience
AUDIENCE
564,012
FOLLOWERS
31,288
OWNER ★
439,379
Engagement Signals
FORKS
2,814
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 20 / 20 (DIVERSITY 1.00)
Why This Is A Finding
NVIDIA/TensorRT-LLM собрал 20 звёзд за окно, тогда как у автора всего 31,288 подписчиков — эффективная аудитория ≈ 564,012. Это даёт surprise-индекс 0.0000118 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 0.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация положительная — рост ещё не выдохся.
Related Findings
RANKS ABOVE 5% OF 8038 FINDINGS
METRICS IN CONTEXT
MEDIAN ACROSS ALL 8038 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00-0.00ABOVE 5%
VELOCITY6.675.67+1.00ABOVE 55%
RETENTION0.0%14.3%-14.3 PPABOVE 0%
FORKS2,814333+2,482ABOVE 86%
SURPRISE0.000.01-0.01ABOVE 2%