FINDING #4111 · 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
12.00
ACCEL
+0.50
RETENTION
0.0%
PEAK 2026-07-27 · FORK-RETENTION 0.0% · 36 STARS / WINDOW
Author Audience
AUDIENCE
495,419
FOLLOWERS
28,361
OWNER ★
394,318
Engagement Signals
FORKS
2,611
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 36 / 36 (DIVERSITY 1.00)
Why This Is A Finding
NVIDIA/TensorRT-LLM собрал 36 звёзд за окно, тогда как у автора всего 28,361 подписчиков — эффективная аудитория ≈ 495,419. Это даёт surprise-индекс 0.0000242 (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 9% OF 4503 FINDINGS
METRICS IN CONTEXT
MEDIAN ACROSS ALL 4503 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00-0.00ABOVE 9%
VELOCITY12.005.33+6.67ABOVE 78%
RETENTION0.0%0.0%0.0 PPABOVE 0%
FORKS2,611457+2,154ABOVE 81%
SURPRISE0.000.00-0.00ABOVE 3%