Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-11 04:04 UTC

microsoft / onnxruntime-genai

Generative AI extensions for onnxruntime

C++ · PythonMIT★ 1,119 stars⑂ 350 forkssince Nov 2023View on GitHub ↗
KindMobile applicationLibraryhow this is determined

microsoft/onnxruntime-genai holds a health index of 99 out of 100, placing it in the Exceptional band. It scores highest on Vitality (100/100) and lowest on Community & Adoption (74/100). It was last updated today. 5 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

MicrosoftOrganization · verified domain
129,473 followers8,301 public repossince Dec 2013

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
NuGetMicrosoft.ML.OnnxRuntimeGenAI0.15.2-3435 days agoonnxruntimegenaimachinelearning

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 recencylast push 0 days ago
36/36Commit cadence52/52 weeks with commits
18/18Commit volume456 commits in the last year
0/10OpenSSF Scorecard: Maintainedno data
Inputs used
commits_last_year456
human_commit_share0.99
days_since_last_push0
active_weeks_last_year52

Release discipline

100Exceptional
How it's scored
27/27Ships releases32 releases published
36/36Release recencylatest release 34 days ago
27/27Release cadencea release every ~19.4 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count32
latest_release_tagv0.15.2
releases_from_tagsno
days_since_latest_release34
mean_days_between_releases19.4

Community & Adoption

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

74Good · 17% of overall
How it's scored
49.4/60Stars1,119 stars
21.2/25Forks350 forks
9.2/15Watchers47 watchers
Inputs used
forks350
stars1,119
watchers47
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
0/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges2
has_contributingno
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateno
How it's scored
62.8/80Total downloads1,115,900 downloads all-time across nuget
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesMicrosoft.ML.OnnxRuntimeGenAI
dependents
ecosystemsnuget
total_downloads1,115,900
monthly_downloads
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?

91Excellent · 23% of overall
How it's scored
45.9/54Bus factor5 contributor(s) cover half of all commits
18.6/22.5Commit distributiontop contributor authored 17% of commits
13.5/13.5Contributor breadth97 contributors
0/10OpenSSF Scorecard: Contributorsno data
Inputs used
bus_factor5
contributors_sampled97
top_contributor_share0.173
How it's scored
31.3/42Issue resolution74% of issues closed
24.7/30PR acceptance1,470/1,782 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs1,470
open_issues144
closed_issues421
prs_merged_7d9
prs_decided_7d10
prs_merged_30d42
prs_decided_30d54
issue_closed_ratio0.745
closed_unmerged_prs312
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
20/20Verified domain
25/25Owner reach129,473 followers of microsoft
25/25Track record8,301 public repos, account ~12 yr old
Inputs used
followers129,473
owner_typeOrganization
is_verifiedyes
owner_loginmicrosoft
public_repos8,301
account_age_days4,657

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on nuget
35/35Publish recencylatest publish 35 days ago
20/20Version history34 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesMicrosoft.ML.OnnxRuntimeGenAI
ecosystemsnuget
any_deprecatedno
min_days_since_publish35

Engineering Quality

Are baseline engineering and documentation practices in place?

78Good · 19% of overall
How it's scored
24/24CI workflows15 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.ruff])
0/9.6Pre-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_configno
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
0/10Topics
10/10Wiki
Inputs used
topics
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?

100Exceptional · 16% of overall

Security posture

100Exceptional
How it's scored
30/30Security policy (SECURITY.md)
25/25Dependabot config
0/25Dependency lockfilespublished library — lockfiles are an application concern, not expected
20/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles
manifestsbenchmark/requirements.txt, pyproject.toml, requirements-dev.txt, requirements-lintrunner.txt
has_codeql_workflowyes
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
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
advisories3
affected_packages3
assessed_packages28
unassessed_packages17
affected_by_severitymoderate 3
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 28 resolved dependencies against OSV. 17 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.

92Excellent · 4% of overall
How it's scored
45/45Agent instructions.github/copilot-instructions.md, .github/instructions/python-model-builder.instructions.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history99 of 99 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, .github/instructions/python-model-builder.instructions.md
agent_instruction_max_bytes6,420
How it's scored
12.6/18One-command bootstrapexamples/csharp/ModelChat/ModelChat.csproj, examples/csharp/ModelMM/ModelMM.csproj, examples/csharp/NemotronSpeech/NemotronSpeech.csproj (toolchain convention, no task runner)
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.ruff])
11/11Static type checkingC++ (statically typed)
10/10Reproducible environmentDockerfile
10/10Demonstrated agent practice32 of the last 100 commits agent-authored or agent-credited
5/8Automated maintenancedependency automation configured, none observed in the sampled commits
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileyes
typed_languageyes
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0.32
toolchain_manifestsexamples/csharp/ModelChat/ModelChat.csproj, examples/csharp/ModelMM/ModelMM.csproj, examples/csharp/NemotronSpeech/NemotronSpeech.csproj, src/csharp/Microsoft.ML.OnnxRuntimeGenAI.csproj, src/java/build.gradle, src/java/src/test/android/app/build.gradle, src/java/src/test/android/build.gradle, test/csharp/Microsoft.ML.OnnxRuntimeGenAI.Tests.csproj
dependency_bot_commit_share0
How it's scored
45/45Type-checkable codeC++ (statically typed)
53.7/55Manageable file sizes16/677 source files over 60KB
Inputs used
primary_languageC++
largest_source_bytes314,204
source_files_sampled677
oversized_source_files16
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 examplesexample, examples
Inputs used
example_dirsexample, examples
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

1,119GitHub stars
97contributors
456commits, last 12 months
0days since last push
32releases
5bus factor
144open 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 (killed by SIGKILL — most likely the container's memory limit; 2026/09/11 04:01:37 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 ★ / 350 ⇿
0Stars
350Forks
32Releases

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.

012525037533682023-122025-042026-08
Major 0Minor 13Patch 18

Each point covers 3 days.

Direct dependencies 2
RegistryPackageVersion constraintManifest
NuGetSystem.Memory4.5.5src/csharp/Microsoft.ML.OnnxRuntimeGenAI.csproj
NuGetMicrosoft.Extensions.AI.Abstractions9.8.0src/csharp/Microsoft.ML.OnnxRuntimeGenAI.csproj
All dependencies 45

Full resolved dependency set from the GitHub dependency graph: 2 direct and 43 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
NuGetMicrosoft.Extensions.AI.Abstractions9.8.0direct
NuGetSystem.Memory4.5.5direct
NuGetMicrosoft.Direct3D.DXC1.7.2308.12indirect
NuGetMicrosoft.ML.OnnxRuntimeindirect
NuGetMicrosoft.ML.OnnxRuntimeGenAI0.14.1indirect
NuGetMicrosoft.ML.OnnxRuntimeGenAI.Cuda0.14.1indirect
NuGetMicrosoft.ML.OnnxRuntimeGenAI.DirectML0.14.1indirect
NuGetMicrosoft.NET.Test.Sdk17.5.0indirect
NuGetNAudio2.2.1indirect
NuGetSystem.CommandLine2.0.1indirect
NuGetxunit2.4.1indirect
NuGetxunit.runner.visualstudio2.4.3indirect
PyPIargparseindirect
PyPIclang-format20.1.8indirect
PyPIcoloredlogsindirect
PyPIflatbuffersindirect
PyPIgnureadlineindirect
PyPIlintrunner0.12.7indirect
PyPIlintrunner-adapters0.12.5indirect
PyPImypyindirect
PyPInumpyindirect
PyPIonnxindirect
PyPIonnx-irindirect
PyPIonnxruntime1.28.0indirect
PyPIonnxruntime1.28.0.dev20260612004indirect
PyPIonnxruntime1.30.0.dev20260824004indirect
PyPIonnxruntime-directml1.25.0.dev20260125001indirect
PyPIonnxruntime-ep-webgpu0.2.0.dev20260611indirect
PyPIpackagingindirect
PyPIpatchelfindirect
PyPIprotobuf6.33.5indirect
PyPIpybind113.0.4indirect
PyPIpytestindirect
PyPIrequestsindirect
PyPIrequests2.33.0indirect
PyPIruff0.12.12indirect
PyPIsetuptoolsindirect
PyPIsympyindirect
PyPIsympy1.12indirect
PyPItorch2.11.0+cu128indirect
PyPItorch2.12.0indirect
PyPItorch2.12.0+cpuindirect
PyPItransformersindirect
PyPIwheelindirect
PyPIwheel0.47.0indirect
Dependency advisories 3

This repository publishes no package the index resolves, so its own dependency graph was assessed — 28 packages, which also include development and test pins that never ship: 3 carry known advisories, of which 0 are direct. 17 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
torch2.11.0+cu128indirectmoderate12.13.0
torch2.12.0indirectmoderate12.13.0
torch2.12.0+cpuindirectmoderate12.13.0

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 v0.34.0 — full methodology · metrics wiki.

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