Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 04:58 UTC

openvinotoolkit / nncf

Neural Network Compression Framework for enhanced OpenVINO™ inference

PythonApache-2.0★ 1,189 stars⑂ 301 forkssince May 2020View on GitHub ↗

openvinotoolkit/nncf holds a health index of 99 out of 100, placing it in the Exceptional band. It scores highest on Vitality (96/100) and lowest on AI Readiness (76/100). It was last updated today. 4 contributors account for most of its recent work.

99
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.

99
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 89 is calibrated to 99 on the published index scale (record calibration 2026-08-02).

Ownership

1,836 followers48 public repossince Sep 2019

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

Package ecosystems

Metrics by category

Vitality

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

96Exceptional · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
35.3/36Commit cadence51/52 weeks with commits
18/18Commit volume377 commits in the last year
0/10OpenSSF Scorecard: Maintainedno data
Inputs used
commits_last_year377
human_commit_share0.81
days_since_last_push0
active_weeks_last_year51
How it's scored
27/27Ships releases36 releases published
36/36Release recencylatest release 7 days ago
19.8/27Release cadencea release every ~66 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count36
latest_release_tagv3.3.0
releases_from_tagsno
days_since_latest_release7
mean_days_between_releases66

Community & Adoption

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

89Excellent · 17% of overall
How it's scored
49.9/60Stars1,189 stars
20.6/25Forks301 forks
8.3/15Watchers32 watchers
Inputs used
forks301
stars1,189
watchers32
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized 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_badges6
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesshields.io
has_pull_request_templateyes
How it's scored
80/80Monthly downloads1,333,362 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesnncf
dependents
ecosystemspypi
total_downloads
monthly_downloads1,333,362
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?

92Excellent · 23% of overall
How it's scored
43.2/54Bus factor4 contributor(s) cover half of all commits
17.5/22.5Commit distributiontop contributor authored 22% of commits
13.5/13.5Contributor breadth77 contributors
0/10OpenSSF Scorecard: Contributorsno data
Inputs used
bus_factor4
contributors_sampled77
top_contributor_share0.224
How it's scored
39.7/42Issue resolution94% of issues closed
26.2/30PR acceptance3,240/3,713 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs3,240
open_issues21
closed_issues360
prs_merged_7d3
prs_decided_7d3
prs_merged_30d17
prs_decided_30d19
issue_closed_ratio0.945
closed_unmerged_prs473
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
23.5/25Owner reach1,836 followers of openvinotoolkit
24.3/25Track record48 public repos, account ~6 yr old
Inputs used
followers1,836
owner_typeOrganization
is_verified
owner_loginopenvinotoolkit
public_repos48
account_age_days2,521
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 7 days ago
20/20Version history34 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesnncf
ecosystemspypi
any_deprecatedno
min_days_since_publish7

Engineering Quality

Are baseline engineering and documentation practices in place?

89Excellent · 19% of overall
How it's scored
24/24CI workflows25 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

85Excellent
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics19 topics
10/10Wiki
Inputs used
topicsquantization, pruning, sparsity, quantization-aware-training, mixed-precision-training, compression, semantic-segmentation, object-detection, classification, nlp, bert, transformers, pytorch, tensorflow, onnx, openvino, deep-learning, genai, llm
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

78Good · 16% of overall
How it's scored
30/30Security policy (SECURITY.md)
25/25Dependabot config
0/25Dependency lockfilespublished library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles
manifestspyproject.toml
has_codeql_workflowno
has_security_policyyes
has_dependabot_configyes
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 advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages19
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:nncf@3.3.0 runtime dependency closure — what installing the published package pulls in — 19 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.

76Good · 4% of overall
How it's scored
45/45Agent instructions.github/copilot-instructions.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history81 of 81 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share1
agent_instruction_files.github/copilot-instructions.md
agent_instruction_max_bytes2,356
How it's scored
18/18One-command bootstrapMakefile
22/22Automated tests
11/11Lint / format config
0/11Static type checking
0/10Reproducible environment
2/10Demonstrated agent practice1 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance19 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0.01
toolchain_manifests
dependency_bot_commit_share0.19
How it's scored
0/45Type-checkable codePython without a type-check config
54.3/55Manageable file sizes10/751 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes109,688
source_files_sampled751
oversized_source_files10
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesexamples, notebooks
Inputs used
example_dirsexamples, notebooks
has_mcp_signalno
api_schema_files
interfaces_expected_of
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

1,189GitHub stars
77contributors
377commits, last 12 months
0days since last push
36releases
4bus factor
21open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • OpenSSF Scorecard did not return a usable result (2026/08/13 04:57:15 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 ★ / 301 ⇿
0Stars
301Forks
36Releases

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.

05010015020025030029172020-052023-072026-08
Major 2Minor 25Patch 8

Each point covers 6 days.

Direct dependencies 12
RegistryPackageVersion constraintManifest
PyPInetworkx>=2.6, <=3.6.1pyproject.toml
PyPIninja>=1.10.0.post2, <1.14pyproject.toml
PyPInumpy>=1.24.0, <2.5.0pyproject.toml
PyPIopenvino-telemetry>=2023.2.0pyproject.toml
PyPIpackaging>=20.0pyproject.toml
PyPIpsutilpyproject.toml
PyPIpydot>=1.4.1, <=3.0.4pyproject.toml
PyPIrich>=13.5.2pyproject.toml
PyPIsafetensors>=0.4.1pyproject.toml
PyPIscikit-learn>=0.24.0pyproject.toml
PyPIscipy>=1.3.2pyproject.toml
PyPItabulate>=0.9.0pyproject.toml
All dependencies 104

Full resolved dependency set from the GitHub dependency graph: 18 direct and 86 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInetworkxdirect
PyPIninjadirect
PyPInumpydirect
PyPInumpy1.26.4direct
PyPInumpy2.2.6direct
PyPInumpy2.4.6direct
PyPIopenvino-telemetrydirect
PyPIpackagingdirect
PyPIpsutildirect
PyPIpydotdirect
PyPIrichdirect
PyPIsafetensorsdirect
PyPIsafetensors0.6.2direct
PyPIscikit-learndirect
PyPIscipydirect
PyPIscipy1.18.0direct
PyPItabulatedirect
PyPItabulate0.10.0direct
PyPIaccelerate1.9.0indirect
PyPIaddictindirect
PyPIanomalib0.6.0indirect
PyPIanomalib2.2.0indirect
PyPIastroid4.1.2indirect
PyPIatheris2.3.0indirect
PyPIdatasets4.6.1indirect
PyPIdatasets5.0.0indirect
PyPIefficientnet-pytorch0.7.1indirect
PyPIexecutorch1.3.1indirect
PyPIfastcore1.11.5indirect
PyPIfastdownload0.0.7indirect
PyPIfastprogress1.0.5indirect
PyPIfuro2025.12.19indirect
PyPIgptqmodel5.6.12indirect
PyPIhuggingface-hub0.36.2indirect
PyPIipykernel7.1.0indirect
PyPIipython8.37.0indirect
PyPIkaleidoindirect
PyPIkernels0.12.3indirect
PyPIlibrosa0.10.0indirect
PyPIlm-eval0.4.12indirect
PyPImatplotlib3.10.7indirect
PyPImatplotlib3.10.9indirect
PyPImdutilsindirect
PyPImemory-profiler0.61.0indirect
PyPInbclient0.10.4indirect
PyPInbformat5.10.4indirect
PyPIonnx1.21.0indirect
PyPIonnx1.22.0indirect
PyPIonnx-ir0.1.15indirect
PyPIonnxruntime1.23.2indirect
PyPIonnxruntime1.24.3indirect
PyPIonnxscript0.5.7indirect
PyPIonnxscript0.6.2indirect
PyPIopenvinoindirect
PyPIopenvino2026.1.0indirect
PyPIopenvino2026.2.1indirect
PyPIopenvino2026.3.0indirect
PyPIopenvino-tokenizersindirect
PyPIoptimum2.2.0indirect
PyPIoptimum-intelindirect
PyPIoptimum-intel2.0.0indirect
PyPIoptimum-onnxindirect
PyPIpandas2.3.3indirect
PyPIpillowindirect
PyPIplotly-expressindirect
PyPIpycocotoolsindirect
PyPIpycocotools2.0.7indirect
PyPIpytest9.0.3indirect
PyPIpytest-cov7.1.0indirect
PyPIpytest-forked1.6.0indirect
PyPIpytest-mock3.15.1indirect
PyPIpytest-ordering0.6indirect
PyPIpytest-splitindirect
PyPIpytest-split0.11.0indirect
PyPIpytest-xdist3.8.0indirect
PyPIpyyamlindirect
PyPIrequests2.33.0indirect
PyPIsentence-transformers5.6.0indirect
PyPIsetuptoolsindirect
PyPIsetuptools81.0.0indirect
PyPIsoundfile0.12.1indirect
PyPIsphinx9.1.0indirect
PyPIsphinx-autoapi3.8.0indirect
PyPItensorboard2.20.0indirect
PyPItensorflow-io0.37.1indirect
PyPItimm0.9.2indirect
PyPItimm1.0.22indirect
PyPItorchindirect
PyPItorch2.10.0indirect
PyPItorch2.12.0indirect
PyPItorch2.9.0indirect
PyPItorchao0.17.0indirect
PyPItorchmetrics1.0.1indirect
PyPItorchvisionindirect
PyPItorchvision0.25.0indirect
PyPItorchvision0.27.0indirect
PyPItqdmindirect
PyPItransformers4.57.6indirect
PyPItransformers5.0.0indirect
PyPIultralytics8.3.221indirect
PyPIultralytics8.4.21indirect
PyPIvirtualenvindirect
PyPIwhowhatbenchindirect
PyPIyattagindirect
Dependency advisories 0

Installing pypi:nncf@3.3.0 pulls in 19 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.

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 v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.