Pulse
2026-09-18-v3.0
Dataset
2026-10-27-catalog-ai-v2
Ruleset
b2e8889c66f7
Scanned
2026-10-27
Window
February–September 15, 2026
Catalog tracking observation. This repository is measured with the same fixed window and ruleset, but it is not part of the published benchmark or its aggregate claims.

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.

01Result

NVIDIA/Model-Optimizer ↗

NVIDIA/Model-Optimizer AI coding statistics: 30%

of 787 commits in February–September 15, 2026 were committed by an AI agent — a floor, not an estimate
30% agent · top contributor 27.5%25 contributors
org-wide

Adoption is broad. Many contributors are committing agent-authored work, which is what a real organisational rollout looks like.

236
agent commits
551
other considered commits
25
agent contributors
27.5%
largest contributor

02Drivers

What shapes this result

Mode, timing, and detected signatures show whether the result reflects broad adoption or one concentrated workflow.

Assisted or autonomous

236assisted
0autonomous

Assisted — a developer’s identity authored the commit and the agent added itself as co-author. Autonomous — a bot identity authored the commit without a human identity attached.

Agent share by month

Agent-attributed commit share by month
MonthAgent shareConsidered commits
2026-022.9%70
2026-039%100
2026-0421.6%134
2026-0518.6%97
2026-0645.3%159
2026-0737%81
2026-0853.9%89
2026-0949.1%57

Peak month: 53.9%. Bars are scaled to that peak, not to 100%.

Which agents

AgentVendorCommitsShare
Claude CodeAnthropic22528.6%
OpenAI CodexOpenAI91.1%
Cursor AgentAnysphere10.1%
GitHub CopilotGitHub10.1%

03Evidence

Inspect the matches

Public commit samples let you inspect the signatures behind the aggregate result.

Matched commit samples

  • c37a6948 on GitHubfeat(quantization): fail fast when a quant config matches no weight quantiClaude Code
  • b80e1644 on GitHubCarry a checkpoint's ModelOpt PTQ run into its eval's MLflow run (#2407)Claude Code
  • d69e93a7 on GitHubRecord the MLflow run that produced a checkpoint in .experiment.json (#237Claude Code
  • 51de53e4 on GitHub[6463897] Fix narrow FP16 histogram calibration (#2412)OpenAI Codex
  • 5b1f7e86 on GitHub[6701308][OMNIML-5805] Correct ONNX PTQ documentation contracts (#2413)OpenAI Codex
  • bd90a5ed on GitHub[OMNIML-5774] Add BEVFormer ONNX PTQ and evaluation example (#2208)OpenAI Codex
  • 1030791f on GitHubFix distributed AutoQuantize scoring and share backward setup (#2231)Cursor Agent
  • 03a1899d on GitHubSupport force tokens to % of total experts during calibration (#910)GitHub Copilot

04Method

What entered the denominator

The result begins with commit history, removes merges and routine automation, and reports literal agent signatures as a lower bound.

Exclusion ledger

Commits in window809
Merge commits removed−0
CI / dependency bots removed−22
Considered787

Bots are excluded from the denominator entirely. Agent attribution requires a literal supported signature; no code-style inference is used.

Continue exploring

Claude Code commitsBrowse repositories with detected Claude Code signatures →GitHub Copilot commitsBrowse repositories with detected GitHub Copilot signatures →Cursor Agent commitsBrowse repositories with detected Cursor Agent signatures →OpenAI Codex commitsBrowse repositories with detected OpenAI Codex signatures →Python AI coding statisticsCompare evidence across Python repositories →GitHub AI commit analyzerInspect another repository with the same evidence model →
Reproduce this observation

Run the same detector locally.

Deterministic signature matching; no code-style inference. Squash merges can remove trailers, so this result remains a measured floor.

npx qmmit-cli NVIDIA/Model-Optimizer

Scan another repository

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