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NVIDIA/Model-Optimizer

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A unified library of SOTA model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.

active 2025-12-07 → 2026-11-10 (UTC)

Complete coverage28,397 / 28,397 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-11-10 (UTC)
Events
13.5K
Pushes
6.2K
Pull requests
440
Issues
146
Stars
321
Forks
62

Activity over time

Daily event counts in the loaded window

Line chart, 339 days from 2025-12-07 to 2026-11-10. Pushes: 6,183 total, peak 123 in a day. Pull requests: 440 total, peak 29 in a day. Issues: 146 total, peak 10 in a day. Comments: 2,801 total, peak 179 in a day. Stars: 321 total, peak 8 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
copy-pr-bot[bot]1.9K1.8K0121
github-actions[bot]1.6K1.5K9117
coderabbitai[bot]1.2K41700
kevalmorabia9772440336143
cjluo-nv46511623167
realAsma44610212159
shengliangxu40522413105
h-guo183451992851
claude[bot]33500133
ChenhanYu3152012347
kaix-nv2591172470
meenchen2401041760
ajrasane240911496
jingyu-ml2321492229
danielkorzekwa216165829
Edwardf0t1208871160
yeyu-nvidia2061411229
kinjalpatel2716598828
codecov[bot]15800158
willg-nv15201072

Recent activity

Latest issues, pull requests and releases

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 321 stars here means stars gained during the window, not the repo's star count.