Public record
Software health reportschema 0.16.0 · metrics 2.10.0 · 2026-07-21 03:07 UTC

NVIDIA / cudnn-frontend

cuDNN Frontend is NVIDIA's modern, open-source entry point to the cuDNN library and a growing collection of high-performance open-source kernels.

Python · C++MIT★ 886 stars⑂ 216 forkssince Jan 2021View on GitHub ↗

NVIDIA/cudnn-frontend holds a health index of 88 out of 100, placing it in the Excellent band. It scores highest on Vitality (91/100) and lowest on Security (58/100). It was last updated today. A single contributor accounts for most of its recent work.

88
overall / 100
Excellent

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.

88
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 74 is calibrated to 88 on the published index scale (record calibration 2026-08-02).

Ownership

NVIDIA CorporationOrganization
28,171 followers769 public repossince May 2012

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?

91Excellent · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
20.8/36Commit cadence30/52 weeks with commits
18/18Commit volume143 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 26 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year143
human_commit_share
days_since_last_push0
active_weeks_last_year30

Release discipline

100Exceptional
How it's scored
27/27Ships releases66 releases published
36/36Release recencylatest release 13 days ago
27/27Release cadencea release every ~13.2 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count66
latest_release_tagv1.26.0
releases_from_tagsno
days_since_latest_release13
mean_days_between_releases13.2
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

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

75Good · 17% of overall
How it's scored
47.8/60Stars886 stars
19.4/25Forks216 forks
6.7/15Watchers17 watchers
Inputs used
forks216
stars886
watchers17
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateyes

Sustainability & Governance

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

76Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
9.2/22.5Commit distributiontop contributor authored 59% of commits
13.5/13.5Contributor breadth42 contributors
10/10OpenSSF Scorecard: Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
Inputs used
bus_factor1
contributors_sampled42
top_contributor_share0.59
How it's scored
29.4/42Issue resolution70% of issues closed
25.6/30PR acceptance202/237 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
9/15OpenSSF Scorecard: Code-ReviewFound 20/30 approved changesets -- score normalized to 6
Inputs used
merged_prs202
open_issues46
closed_issues108
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.701
closed_unmerged_prs35
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
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
25/25Owner reach28,171 followers of NVIDIA
25/25Track record769 public repos, account ~14 yr old
Inputs used
followers28,171
owner_typeOrganization
is_verified
owner_loginNVIDIA
public_repos769
account_age_days5,184
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 13 days ago
20/20Version history31 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesnvidia-cudnn-frontend
ecosystemspypi
any_deprecatedno
min_days_since_publish13

Engineering Quality

Are baseline engineering and documentation practices in place?

66Good · 19% of overall
How it's scored
0/24CI workflows
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 28 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://docs.nvidia.com/deeplearning/cudnn/latest/
10/10Repository description
10/10Topics20 topics
0/10Wiki
Inputs used
topicsattention, blackwell, cuda-kernels, flash-attention, fp8, gemm, gpu, hopper, mixture-of-experts, moe, mxfp8, normalization, nvfp4, sdpa, transformer, grouped-gemm, cuda, cuda-toolkit, deep-learning, nvidia
has_wikino
homepagehttps://docs.nvidia.com/deeplearning/cudnn/latest/
docs_sitehttps://docs.nvidia.com/deeplearning/cudnn/latest/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

58Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
3.8/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
0/2.5CI-Tests0 out of 28 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
4.5/7.5Code-ReviewFound 20/30 approved changesets -- score normalized to 6
2.5/2.5Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
0/10Dangerous-Workflowno data
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained30 commit(s) and 26 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsno data
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated14
scorecard_versionv5.5.0
checks_inconclusive4
scorecard_aggregate4.8
Excluded from scoring (no data or not applicable): Dangerous-Workflow, Packaging, Signed-Releases, Token-Permissions. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages3
unassessed_packages9
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 3 resolved dependencies against OSV. 9 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

73Good · 4% of overall
How it's scored
45/45Agent instructionsAGENTS.md, CLAUDE.md, include/cudnn_frontend/AGENTS.md, python/cudnn/AGENTS.md, samples/AGENTS.md, test/AGENTS.md
15/15Machine-readable docs (llms.txt)llms.txt present
0/40Legible commit historyno data
Inputs used
has_llms_txtyes
llms_txt_url
legible_history_share
agent_instruction_filesAGENTS.md, CLAUDE.md, include/cudnn_frontend/AGENTS.md, python/cudnn/AGENTS.md, samples/AGENTS.md, test/AGENTS.md
agent_instruction_max_bytes6,052
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config
0/11Static type checking
10/10Reproducible environmentDockerfile
0/10Demonstrated agent practiceno data
0/8Automated maintenanceno data
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileyes
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share
toolchain_manifests
dependency_bot_commit_share
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.
How it's scored
0/45Type-checkable codePython without a type-check config
49.7/55Manageable file sizes55/568 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes1,042,178
source_files_sampled568
oversized_source_files55
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 examplesnotebooks, samples
Inputs used
example_dirsnotebooks, samples
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

886GitHub stars
42contributors
143commits, last 12 months
0days since last push
66releases
1bus factor
46open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 4.8 / 10
4.8aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-07-21 03:06 UTC

10Binary-Artifactsno binaries found in the repo
5Branch-Protectionbranch protection is not maximal on development and all release branches
0CI-Tests0 out of 28 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
6Code-ReviewFound 20/30 approved changesets -- score normalized to 6
10Contributorsproject has 3 contributing companies or organizations -- score normalized to 10
n/aDangerous-Workflowno workflows found
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 26 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
n/aToken-PermissionsNo tokens found
10Vulnerabilities0 existing vulnerabilities detected
All dependencies 12

Full resolved dependency set from the GitHub dependency graph: 0 direct and 12 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIblack26.3.1indirect
PyPIclang-format21.1.6indirect
PyPIcmakeindirect
PyPIjupyterindirect
PyPIlooseversionindirect
PyPIninja1.11.1.1indirect
PyPInumpyindirect
PyPInvidia-cutlass-dslindirect
PyPIpybind11indirect
PyPIpytestindirect
PyPIpytest-xdistindirect
PyPIsetuptoolsindirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 3 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct. 9 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

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 v0.16.0 — full methodology · metrics wiki.

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