Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-17 07:40 UTC

NVIDIA / Model-Optimizer

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.

PythonApache-2.0★ 3,818 stars⑂ 600 forkssince Apr 2024View on GitHub ↗
KindLibraryhow this is determined

NVIDIA/Model-Optimizer holds a health index of 98 out of 100, placing it in the Exceptional band. It scores highest on Vitality (100/100) and lowest on Security (52/100). It was last updated today. 7 contributors account for most of its recent work.

98
overall / 100
Exceptional

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

98
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 86 is calibrated to 98 on the published index scale (record calibration 2026-08-02).

Ownership

NVIDIA CorporationOrganization · verified domain
30,142 followers803 public repossince May 2012

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPInvidia-modelopt0.46.1326,565397 days ago

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

100Exceptional · 21% of overall

Development activity

100Exceptional
How it's scored
36/36Push recency — last push 0 days ago
36/36Commit cadence — 52/52 weeks with commits
18/18Commit volume — 1,131 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year1,131
human_commit_share0.97
days_since_last_push0
active_weeks_last_year52

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 48 releases published
36/36Release recency — latest release 7 days ago
27/27Release cadence — a release every ~7.8 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count48
latest_release_tag0.47.0rc1
releases_from_tagsno
days_since_latest_release7
mean_days_between_releases7.8

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

91Excellent · 17% of overall

Popularity & adoption

90Excellent
How it's scored
58.1/60Stars — 3,818 stars
23.1/25Forks — 600 forks
8.3/15Watchers — 32 watchers
Inputs used
forks600
stars3,818
watchers32
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges3
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesshields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

92Excellent
How it's scored
73.5/80Monthly downloads — 326,565 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesnvidia-modelopt
dependents—
ecosystemspypi
total_downloads—
monthly_downloads326,565
unverified_packages_excluded—
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

93Exceptional · 23% of overall

Maintainer resilience (bus factor)

91Excellent
How it's scored
51.3/54Bus factor — 7 contributor(s) cover half of all commits
17.1/22.5Commit distribution — top contributor authored 24% of commits
13.5/13.5Contributor breadth — 86 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor7
contributors_sampled86
top_contributor_share0.241

Issue & PR responsiveness

82Excellent
How it's scored
33/42Issue resolution — 78% of issues closed
23.5/30PR acceptance — 1,335/1,705 decided PRs merged
13/13Newcomer PR acceptance — 1/1 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs1,335
open_issues94
closed_issues343
prs_merged_7d40
prs_decided_7d59
prs_merged_30d40
prs_decided_30d59
issue_closed_ratio0.785
closed_unmerged_prs370
first_time_authors_30d1
first_time_prs_merged_30d1
first_time_prs_decided_30d1

Ownership & stewardship

100Exceptional
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
25/25Owner reach — 30,142 followers of NVIDIA
25/25Track record — 803 public repos, account ~14 yr old
Inputs used
followers30,142
owner_typeOrganization
is_verifiedyes
owner_loginNVIDIA
public_repos803
account_age_days5,242

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 7 days ago
20/20Version history — 39 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesnvidia-modelopt
ecosystemspypi
any_deprecatedno
min_days_since_publish7

Engineering Quality

Are baseline engineering and documentation practices in place?

87Excellent · 19% of overall

Engineering practices

92Excellent
How it's scored
24/24CI workflows — 13 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

80Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://nvidia.github.io/Model-Optimizer/
10/10Repository description
0/10Topics
0/10Wiki
Inputs used
topics—
has_wikino
homepagehttps://nvidia.github.io/Model-Optimizer/
docs_sitehttps://nvidia.github.io/Model-Optimizer/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

52Moderate · 16% of overall

Security posture

40Weak
How it's scored
30/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfilesuv.lock
manifestspyproject.toml
has_codeql_workflowno
has_security_policyyes
has_dependabot_configno
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages49
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:nvidia-modelopt@0.46.1 runtime dependency closure — what installing the published package pulls in — 49 packages. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

85Excellent · 4% of overall

Agent context & guidance

100Exceptional
How it's scored
45/45Agent instructions — AGENTS.md, CLAUDE.md, tools/debugger/CLAUDE.md, tools/launcher/CLAUDE.md
15/15Machine-readable docs (llms.txt) — llms.txt served by the project website (https://docs.nvidia.com/llms.txt)
40/40Legible commit history — 97 of 97 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_urlhttps://docs.nvidia.com/llms.txt
legible_history_share1
agent_instruction_filesAGENTS.md, CLAUDE.md, tools/debugger/CLAUDE.md, tools/launcher/CLAUDE.md
agent_instruction_max_bytes3,952

Verify loop (build / test / typecheck)

79Good
How it's scored
18/18One-command bootstrap — noxfile.py
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
0/11Static type checking
10/10Reproducible environment — Dockerfile, lockfile
10/10Demonstrated agent practice — 40 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileyes
typed_languageno
bootstrap_filesnoxfile.py
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share0.4
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

54Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
53.6/55Manageable file sizes — 33/1,299 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes114,583
source_files_sampled1,299
oversized_source_files33

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
20/20MCP server
40/40Runnable examples — examples, notebooks, recipes
Inputs used
example_dirsexamples, notebooks, recipes
has_mcp_signalyes
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto). Remaining weights renormalized.

Key facts

3,818GitHub stars
86contributors
1,131commits, last 12 months
0days since last push
48releases
7bus factor
94open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • First-time contributor figures cover 12 of 16 authors (cap 12)
  • OpenSSF Scorecard did not return a usable result (killed by SIGKILL — most likely the container's memory limit; 2026/09/17 07:39:00 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks

More detail

Star and fork history 0 ★ / 600 ⇿
0Stars
600Forks
48Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

0100200300400500600590132024-052025-072026-09
Major 0Minor 16Patch 6

Each point covers 3 days.

Direct dependencies 15
RegistryPackageVersion constraintManifest
PyPIninja—pyproject.toml
PyPInumpy—pyproject.toml
PyPInvidia-ml-py>=12pyproject.toml
PyPIpackaging—pyproject.toml
PyPIsetuptools>=80pyproject.toml
PyPItorch>=2.8pyproject.toml
PyPItqdm—pyproject.toml
PyPIPyYAML>=6.0pyproject.toml
PyPIomegaconf>=2.3.0pyproject.toml
PyPIpulp<4.0pyproject.toml
PyPIpydantic>=2.0pyproject.toml
PyPIregex—pyproject.toml
PyPIrich—pyproject.toml
PyPIsafetensors—pyproject.toml
PyPIscipy—pyproject.toml
All dependencies 303

Full resolved dependency set from the GitHub dependency graph: 32 direct and 271 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIninja1.13.2direct
PyPInumpy—direct
PyPInumpy1.23.5direct
PyPInumpy1.26.4direct
PyPInumpy2.2.6direct
PyPInumpy2.4.6direct
PyPInumpy2.5.3direct
PyPInvidia-ml-py13.610.43direct
PyPIomegaconf—direct
PyPIomegaconf2.3.1direct
PyPIpackaging26.3direct
PyPIpulp3.3.2direct
PyPIpydantic—direct
PyPIpydantic2.13.5direct
PyPIpyyaml6.0.3direct
PyPIregex2026.9.10direct
PyPIrich—direct
PyPIrich15.0.0direct
PyPIsafetensors—direct
PyPIsafetensors0.8.0direct
PyPIscipy—direct
PyPIscipy1.15.3direct
PyPIscipy1.17.1direct
PyPIscipy1.18.1direct
PyPIsetuptools—direct
PyPIsetuptools84.0.0direct
PyPItorch—direct
PyPItorch2.14.0direct
PyPItorch2.7.0+cu128direct
PyPItqdm—direct
PyPItqdm4.66.5direct
PyPItqdm4.70.1direct
PyPIaccelerate—indirect
PyPIaccelerate1.15.0indirect
PyPIaccelerate1.4.0indirect
PyPIaiohappyeyeballs2.7.1indirect
PyPIaiohttp3.14.3indirect
PyPIaiosignal1.4.0indirect
PyPIalabaster1.0.0indirect
PyPIannotated-doc0.0.5indirect
PyPIannotated-types0.8.0indirect
PyPIantlr4-python3-runtime4.9.3indirect
PyPIanyio4.15.1indirect
PyPIargcomplete3.7.2indirect
PyPIast-serialize0.11.2indirect
PyPIasync-timeout5.0.1indirect
PyPIattrs26.1.0indirect
PyPIautodoc-pydantic2.2.0indirect
PyPIav20.2.1indirect
PyPIbabel2.18.0indirect
PyPIbandit1.7.9indirect
PyPIboto3—indirect
PyPIbotocore—indirect
PyPIcachetools7.1.8indirect
PyPIcertifi2026.7.22indirect
PyPIcffi2.1.1indirect
PyPIcfgv3.5.0indirect
PyPIcharset-normalizer3.5.1indirect
PyPIclick8.5.0indirect
PyPIcloudpickle3.1.2indirect
PyPIcolorama0.4.6indirect
PyPIcoloredlogs15.0.1indirect
PyPIcolorlog6.12.0indirect
PyPIcompressed-tensors—indirect
PyPIcoverage7.14.3indirect
PyPIcppimport26.4.17indirect
PyPIcryptography50.0.1indirect
PyPIcuda-pathfinder1.8.1indirect
PyPIcupy-cuda12x14.2.0indirect
PyPIdatabricks-sdk0.139.0indirect
PyPIdatasets—indirect
PyPIdatasets2.19.0indirect
PyPIdatasets4.4.2indirect
PyPIdatasets5.0.1indirect
PyPIdeepspeed0.19.6indirect
PyPIdefusedxml0.7.1indirect
PyPIdependency-groups1.3.2indirect
PyPIdescartes1.1.0indirect
PyPIdiffusers0.40.0indirect
PyPIdill0.4.1indirect
PyPIdistlib0.4.3indirect
PyPIdocutils0.22.4indirect
PyPIeinops0.8.1indirect
PyPIeinops0.8.2indirect
PyPIevaluate—indirect
PyPIexceptiongroup1.3.1indirect
PyPIfastapi0.141.1indirect
PyPIfilelock3.32.6indirect
PyPIfire—indirect
PyPIfire0.6.0indirect
PyPIfire0.7.1indirect
PyPIflash-attn—indirect
PyPIflash-attn0.2.8indirect
PyPIflatbuffers25.12.19indirect
PyPIfrozenlist1.8.0indirect
PyPIfsspec2026.6.0indirect
PyPIgitdb4.0.12indirect
PyPIgitpython3.1.62indirect
PyPIgoogle-auth2.58.0indirect
PyPIh110.16.0indirect
PyPIhf-xet1.6.0indirect
PyPIhjson3.1.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpx0.28.1indirect
PyPIhuggingface-hub1.31.0indirect
PyPIhumanfriendly10.0indirect
PyPIhumanize4.16.0indirect
PyPIhydra-core1.3.6indirect
PyPIidentify2.6.19indirect
PyPIidna3.19indirect
PyPIimagesize2.0.1indirect
PyPIimmutabledict4.3.1indirect
PyPIimportlib-metadata9.0.1indirect
PyPIiniconfig2.3.0indirect
PyPIipywidgets—indirect
PyPIjinja23.1.6indirect
PyPIjiwer—indirect
PyPIjoblib1.6.0indirect
PyPIkernels—indirect
PyPIkornia0.6.12indirect
PyPIlibrosa—indirect
PyPIlibrt0.15.0indirect
PyPIlief1.0.0indirect
PyPIliger-kernel—indirect
PyPIlm-eval—indirect
PyPIlru-dict1.4.1indirect
PyPIltx-core—indirect
PyPIltx-pipelines—indirect
PyPIltx-trainer—indirect
PyPIlyft-dataset-sdk0.0.8indirect
PyPImako1.4.1indirect
PyPImarkdown-it-py4.2.0indirect
PyPImarkupsafe3.0.3indirect
PyPImath-verify—indirect
PyPImcp—indirect
PyPImdurl0.1.2indirect
PyPIml-dtypes0.6.0indirect
PyPImlflow-skinny—indirect
PyPImlflow-skinny3.16.0indirect
PyPImmcv-full1.7.0indirect
PyPImmdet2.28.2indirect
PyPImmdet3d1.0.0rc6indirect
PyPImmsegmentation0.30.0indirect
PyPImpmath1.3.0indirect
PyPImsgpack1.2.2indirect
PyPImultidict6.8.0indirect
PyPImultiprocess0.70.19indirect
PyPImypy2.1.0indirect
PyPImypy-extensions1.1.0indirect
PyPInemo-automodel—indirect
PyPInemo-run—indirect
PyPInetworkx3.4.2indirect
PyPInetworkx3.6.1indirect
PyPInltk3.10.3indirect
PyPInodeenv1.10.0indirect
PyPInox2026.8.17indirect
PyPInuscenes-devkit1.1.11indirect
PyPInvidia-modelopt—indirect
PyPInvtx—indirect
PyPIonnx1.17.0indirect
PyPIonnx1.21.0indirect
PyPIonnx-graphsurgeon0.6.1indirect
PyPIonnx-ir1.0.0indirect
PyPIonnxconverter-common1.16.0indirect
PyPIonnxruntime1.19.2indirect
PyPIonnxruntime1.22.1indirect
PyPIonnxruntime1.24.4indirect
PyPIonnxruntime-ep-nv-tensorrt-rtx-cu130.4.0indirect
PyPIonnxruntime-genai—indirect
PyPIonnxruntime-gpu1.20.1indirect
PyPIonnxruntime-gpu1.22.0indirect
PyPIonnxruntime-gpu1.23.2indirect
PyPIonnxruntime-gpu1.24.4indirect
PyPIonnxscript0.7.2indirect
PyPIonnxsim0.5.0indirect
PyPIonnxslim0.1.96indirect
PyPIopenai—indirect
PyPIopencv-python—indirect
PyPIopencv-python4.5.5.64indirect
PyPIopencv-python-headless—indirect
PyPIopentelemetry-api1.44.0indirect
PyPIopentelemetry-proto1.44.0indirect
PyPIopentelemetry-sdk1.44.0indirect
PyPIopentelemetry-semantic-conventions0.65b0indirect
PyPIoptimum—indirect
PyPIoptimum1.23.3indirect
PyPIpandas—indirect
PyPIpandas2.2.2indirect
PyPIpandas2.3.3indirect
PyPIpandas3.0.5indirect
PyPIpathspec1.1.1indirect
PyPIpeft—indirect
PyPIpeft0.18.1indirect
PyPIpeft0.20.0indirect
PyPIpillow12.3.0indirect
PyPIplatformdirs4.11.8indirect
PyPIpluggy1.6.0indirect
PyPIpolygraphy0.53.4indirect
PyPIpre-commit4.6.0indirect
PyPIpropcache0.5.2indirect
PyPIprotobuf6.33.6indirect
PyPIpsutil—indirect
PyPIpsutil7.2.2indirect
PyPIpy-cpuinfo9.0.0indirect
PyPIpy7zr—indirect
PyPIpyarrow—indirect
PyPIpyarrow25.0.1indirect
PyPIpyasn10.6.4indirect
PyPIpyasn1-modules0.4.2indirect
PyPIpybind113.1.0indirect
PyPIpycparser3.0indirect
PyPIpydantic-core2.46.5indirect
PyPIpydantic-settings2.15.0indirect
PyPIpygments2.21.0indirect
PyPIpygments-styles0.3.0indirect
PyPIpyparsing3.3.2indirect
PyPIpyquaternion0.9.9indirect
PyPIpyreadline33.5.6indirect
PyPIpytest9.1.1indirect
PyPIpytest-cov7.1.0indirect
PyPIpytest-instafail0.5.0indirect
PyPIpytest-timeout2.4.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-discovery1.6.0indirect
PyPIpython-dotenv1.2.3indirect
PyPIpytz2026.3.post1indirect
PyPIray—indirect
PyPIrefile0.4.1indirect
PyPIrequests2.34.2indirect
PyPIroman-numerals4.1.0indirect
PyPIruff0.15.20indirect
PyPIrwkv—indirect
PyPIseaborn—indirect
PyPIsentencepiece—indirect
PyPIsentencepiece0.2.2indirect
PyPIshapely1.8.5.post1indirect
PyPIshellingham1.5.4indirect
PyPIshibuya2026.7.12indirect
PyPIsix1.17.0indirect
PyPIsmmap5.0.3indirect
PyPIsnowballstemmer3.1.1indirect
PyPIsoundfile—indirect
PyPIsphinx9.1.0indirect
PyPIsphinx-argparse0.6.1indirect
PyPIsphinx-autobuild2025.8.25indirect
PyPIsphinx-copybutton0.5.2indirect
PyPIsphinx-inline-tabs2025.12.21.14indirect
PyPIsphinx-togglebutton0.4.5indirect
PyPIsphinxcontrib-applehelp2.0.0indirect
PyPIsphinxcontrib-devhelp2.0.0indirect
PyPIsphinxcontrib-htmlhelp2.1.0indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
PyPIsphinxcontrib-qthelp2.0.0indirect
PyPIsphinxcontrib-serializinghtml2.0.0indirect
PyPIsqlparse0.6.0indirect
PyPIstarlette1.6.0indirect
PyPIstevedore5.8.0indirect
PyPIstevedore5.9.1indirect
PyPIsympy1.14.0indirect
PyPItensorboard—indirect
PyPItensorboardx—indirect
PyPItermcolor3.3.0indirect
PyPItiktoken—indirect
PyPItiktoken0.14.0indirect
PyPItiktoken0.7.0indirect
PyPItimm—indirect
PyPItimm1.0.29indirect
PyPItokenizers—indirect
PyPItokenizers0.22.2indirect
PyPItomli2.4.1indirect
PyPItorch-geometric2.8.0.post1indirect
PyPItorch-tensorrt—indirect
PyPItorchao—indirect
PyPItorchaudio2.7.0+cu128indirect
PyPItorchprofile0.0.4indirect
PyPItorchvision—indirect
PyPItorchvision0.29.0indirect
PyPItrackio—indirect
PyPItransformers—indirect
PyPItransformers4.57.3indirect
PyPItransformers5.14.1indirect
PyPItransformers-stream-generator—indirect
PyPItrimesh2.35.39indirect
PyPItrl—indirect
PyPItypeguard4.6.0indirect
PyPItyper0.27.2indirect
PyPItyping-extensions4.16.0indirect
PyPItyping-inspection0.4.4indirect
PyPItzdata2026.4indirect
PyPIurllib32.7.0indirect
PyPIuv0.12.13indirect
PyPIuvicorn0.53.0indirect
PyPIvirtualenv21.7.9indirect
PyPIwandb—indirect
PyPIwatchfiles1.2.0indirect
PyPIwebsockets17.1indirect
PyPIwheel0.48.0indirect
PyPIwonderwords3.0.1indirect
PyPIxxhash4.0.1indirect
PyPIyapf0.32.0indirect
PyPIyarl1.24.5indirect
PyPIzipp4.1.0indirect
PyPIzstandard—indirect
Dependency advisories 0

Installing pypi:nvidia-modelopt@0.46.1 pulls in 49 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Related records

Inspected repositories sharing catalogue tags or ecosystems with NVIDIA/Model-Optimizer. Read them side by side →

100run-llama/llama_indexLlamaIndex is the document processing platform for AIExceptional100awslabs/mcpOpen source MCP Servers for AWSExceptional100zephyrproject-rtos/zephyrPrimary Git Repository for the Zephyr Project. Zephyr is a new generation, scalable, optimized, secure RTOS for multiple hardware architectures.Exceptional100streamlit/streamlitStreamlit — A faster way to build and share data apps.Exceptional100aws/aws-sam-cliCLI tool to build, test, debug, and deploy Serverless applications using AWS SAMExceptional100kubeflow/trainerDistributed AI Model Training and LLM Fine-Tuning on KubernetesExceptional

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.