Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-27 16:00 UTC

OpenNMT / CTranslate2

Fast inference engine for Transformer models

C++ · PythonMIT★ 4,645 stars⑂ 521 forkssince Sep 2019View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

OpenNMT/CTranslate2 holds a health index of 86 out of 100, placing it in the Excellent band. It scores highest on Community & Adoption (86/100) and lowest on Security (44/100). It was last updated 10 days ago. A single contributor accounts for most of its recent work.

86
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.

86
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 72 is calibrated to 86 on the published index scale (record calibration 2026-08-02).

Ownership

OpenNMTOrganization
467 followers25 public repossince Oct 2016

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIctranslate24.8.112,442,8316155 days agoopennmtnmtneuralmachinetranslationcudamklinferencequantization

Metrics by category

Vitality

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

77Good · 21% of overall
How it's scored
28.8/36Push recencylast push 10 days ago
14.5/36Commit cadence21/52 weeks with commits
16.9/18Commit volume75 commits in the last year
0/10OpenSSF Scorecard: Maintainedno data
Inputs used
commits_last_year75
human_commit_share1
days_since_last_push10
active_weeks_last_year21
How it's scored
27/27Ships releases100 releases published
36/36Release recencylatest release 55 days ago
19.8/27Release cadencea release every ~68.8 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count100
latest_release_tagv4.8.1
releases_from_tagsno
days_since_latest_release55
mean_days_between_releases68.8

Community & Adoption

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

86Excellent · 17% of overall
How it's scored
59.5/60Stars4,645 stars
22.6/25Forks521 forks
9.5/15Watchers53 watchers
Inputs used
forks521
stars4,645
watchers53
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
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadge.fury.io, github.com, shields.io
has_pull_request_templateno
How it's scored
80/80Monthly downloads12,442,831 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesctranslate2
dependents
ecosystemspypi
total_downloads
monthly_downloads12,442,831
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?

66Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
2.2/22.5Commit distributiontop contributor authored 90% of commits
13.5/13.5Contributor breadth65 contributors
0/10OpenSSF Scorecard: Contributorsno data
Inputs used
bus_factor1
contributors_sampled65
top_contributor_share0.904
How it's scored
30.5/42Issue resolution73% of issues closed
28.2/30PR acceptance1,130/1,203 decided PRs merged
8.7/13Newcomer PR acceptance2/3 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs1,130
open_issues227
closed_issues602
prs_merged_7d0
prs_decided_7d1
prs_merged_30d3
prs_decided_30d4
issue_closed_ratio0.726
closed_unmerged_prs73
first_time_authors_30d3
first_time_prs_merged_30d2
first_time_prs_decided_30d3
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domain
19.2/25Owner reach467 followers of OpenNMT
22.3/25Track record25 public repos, account ~9 yr old
Inputs used
followers467
owner_typeOrganization
is_verifiedno
owner_loginOpenNMT
public_repos25
account_age_days3,593

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 55 days ago
20/20Version history61 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesctranslate2
ecosystemspypi
any_deprecatedno
min_days_since_publish55

Engineering Quality

Are baseline engineering and documentation practices in place?

84Excellent · 19% of overall
How it's scored
24/24CI workflows1 workflow(s)
24/24Tests present
16/16Linter configpython/setup.cfg ([flake8], [isort])
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

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://opennmt.net/CTranslate2
10/10Repository description
10/10Topics20 topics
0/10Wiki
Inputs used
topicsneural-machine-translation, cpp, mkl, quantization, cuda, thrust, opennmt, deep-neural-networks, openmp, onednn, intrinsics, avx2, avx, parallel-computing, gemm, neon, transformer-models, machine-translation, deep-learning, inference
has_wikino
homepagehttps://opennmt.net/CTranslate2
docs_sitehttps://opennmt.net/CTranslate2
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

44Weak · 16% of overall
How it's scored
30/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles
manifestsdocs/requirements.txt, python/pyproject.toml, python/setup.cfg, python/setup.py
has_codeql_workflowno
has_security_policyyes
has_dependabot_configno

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_packages3
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:ctranslate2@4.8.1 runtime dependency closure — what installing the published package pulls in — 3 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.

66Good · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history96 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.96
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format configpython/setup.cfg ([flake8], [isort])
11/11Static type checkingC++ (statically typed)
10/10Reproducible environmentDockerfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
0/8Automated maintenanceno automated dependency updates observed
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
toolchain_manifests
dependency_bot_commit_share0
How it's scored
45/45Type-checkable codeC++ (statically typed)
54.3/55Manageable file sizes4/323 source files over 60KB
Inputs used
primary_languageC++
largest_source_bytes907,858
source_files_sampled323
oversized_source_files4
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
Inputs used
example_dirsexamples
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

4,645GitHub stars
65contributors
75commits, last 12 months
10days since last push
100releases
1bus factor
227open 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); skipping Scorecard checks

More detail

Star and fork history 0 ★ / 521 ⇿
0Stars
521Forks
100Releases

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.

010020030040050048192019-102023-032026-08
Major 3Minor 62Patch 35

Each point covers 7 days.

All dependencies 28

Full resolved dependency set from the GitHub dependency graph: 0 direct and 28 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIaccelerateindirect
PyPIctranslate2indirect
PyPIdocker4.3.1indirect
PyPIfairseq0.12.2indirect
PyPIgputilindirect
PyPIgputil1.4.0indirect
PyPImyst-parser0.18.*indirect
PyPInumpyindirect
PyPIopennmt-pyindirect
PyPIopennmt-py2.2.*indirect
PyPIopennmt-tfindirect
PyPIprotobufindirect
PyPIpybind112.11.1indirect
PyPIpytestindirect
PyPIpyyamlindirect
PyPIsacrebleu1.4.14indirect
PyPIsentencepieceindirect
PyPIsetuptoolsindirect
PyPIsphinx5.3.*indirect
PyPIsphinx-rtd-theme1.0.*indirect
PyPItensorflowindirect
PyPItorch2.12indirect
PyPItransformersindirect
PyPItransformers4.31.*indirect
PyPItransformers4.40.*indirect
PyPIwheelindirect
PyPIwurlitzerindirect
PyPIwurlitzer3.1.*indirect
Dependency advisories 0

Installing pypi:ctranslate2@4.8.1 pulls in 3 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 v0.34.0 — full methodology · metrics wiki.

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