Home/Compare/ai-serving vs react-native-executorch

Comparison

ai-serving vs react-native-executorch

Verdict

Pick ai-serving if ai-Serving is an inference server supporting PMML and ONNX formats via HTTP or gRPC endpoints, easily deployable with Docker; pick react-native-executorch if react Native Executorch powers on-device AI inference in React Native apps using a declarative approach with ExecuTorch.

Markdown twin · ai-serving alternatives · react-native-executorch alternatives

GraphCanon updated today

ai-serving logo

ai-serving

autodeployai/ai-serving

166pushed Feb 24, 2026
vs
react-native-executorch logo

react-native-executorch

software-mansion/react-native-executorch

1.7kpushed Aug 24, 2026

Trust & integrity

Signalai-servingreact-native-executorch
Maintenance
Slowing (171d since push)
As of 1w · github_public_v1
Very active (0d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of 1w · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

ai-serving
Serving AI/ML models in open standard formats PMML and ONNX with HTTP and gRPC endpoints
react-native-executorch
Declarative way to run AI models in React Native on device

Stars

ai-serving
166
react-native-executorch
1.7k

Forks

ai-serving
31
react-native-executorch
95

Open issues

ai-serving
3
react-native-executorch
64

Language

ai-serving
Scala
react-native-executorch
C++

Adopt for

ai-serving
Ai-Serving is an inference server supporting PMML and ONNX formats via HTTP or gRPC endpoints, easily deployable with Docker.
react-native-executorch
React Native Executorch powers on-device AI inference in React Native apps using a declarative approach with ExecuTorch.

Persona

ai-serving
-
react-native-executorch
-

Runtime

ai-serving
-
react-native-executorch
-

License

ai-serving
Apache-2.0
react-native-executorch
Other

Last pushed

ai-serving
Feb 24, 2026
react-native-executorch
Aug 24, 2026

Categories

ai-serving
Inference & Serving
react-native-executorch
Computer Vision, Inference & Serving

Trust and health

Maintenance

ai-serving
Slowing (36%)
react-native-executorch
Very active (96%)

Days since push

ai-serving
171d
react-native-executorch
0d

Open issues (now)

ai-serving
3
react-native-executorch
64

Stars delta

ai-serving
0 (30d)
react-native-executorch
+23 (30d)

Open issues delta

ai-serving
0 (30d)
react-native-executorch
-13 (30d)

Full report

ai-serving
Trust report
react-native-executorch
Trust report

Choose ai-serving if…

  • ai-serving is primarily Scala; react-native-executorch is C++.
  • License: ai-serving is Apache-2.0, react-native-executorch is Other.
  • Tags unique to ai-serving: ai-serving, grpc, inference-server, onnx.
  • When you need to serve models in both PMML and ONNX formats without manual configuration changes between formats.

When NOT to use ai-serving

  • Avoid if your team lacks familiarity or willingness to use Scala for deployment through sbt build system for customization needs.
  • Not suitable when only one model format, either PMML or ONNX but not both, is needed and a simpler solution would suffice.
  • If your project strictly requires a non-Dockerized setup that does not align with using pre-built Docker images.

Choose react-native-executorch if…

  • react-native-executorch is primarily C++; ai-serving is Scala.
  • License: react-native-executorch is Other, ai-serving is Apache-2.0.
  • Tags unique to react-native-executorch: image-embeddings, llm-inference, object-detection, ocr.
  • Also covers Computer Vision.
  • You are developing a React Native application requiring efficient on-device AI inference capabilities.

When NOT to use react-native-executorch

  • When the development team lacks expertise in C++ or React Native integration specifics required by Executorch.
  • Projects that depend heavily on cloud-based machine learning services for their AI functionalities.
  • Scenarios where cross-platform support beyond React Native is necessary.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: ai-serving 166 · react-native-executorch 1.7k (synced Aug 14, 2026).

Common questions

What is the difference between ai-serving and react-native-executorch?
ai-serving: Serving AI/ML models in open standard formats PMML and ONNX with HTTP and gRPC endpoints. react-native-executorch: Declarative way to run AI models in React Native on device. See the comparison table for live GitHub stats and shared categories.
When should I choose ai-serving over react-native-executorch?
Choose ai-serving over react-native-executorch when ai-serving is primarily Scala; react-native-executorch is C++; License: ai-serving is Apache-2.0, react-native-executorch is Other; Tags unique to ai-serving: ai-serving, grpc, inference-server, onnx; When you need to serve models in both PMML and ONNX formats without manual configuration changes between formats.
When should I choose react-native-executorch over ai-serving?
Choose react-native-executorch over ai-serving when react-native-executorch is primarily C++; ai-serving is Scala; License: react-native-executorch is Other, ai-serving is Apache-2.0; Tags unique to react-native-executorch: image-embeddings, llm-inference, object-detection, ocr; Also covers Computer Vision; You are developing a React Native application requiring efficient on-device AI inference capabilities.
When should I avoid ai-serving?
Avoid if your team lacks familiarity or willingness to use Scala for deployment through sbt build system for customization needs. Not suitable when only one model format, either PMML or ONNX but not both, is needed and a simpler solution would suffice. If your project strictly requires a non-Dockerized setup that does not align with using pre-built Docker images.
When should I avoid react-native-executorch?
When the development team lacks expertise in C++ or React Native integration specifics required by Executorch. Projects that depend heavily on cloud-based machine learning services for their AI functionalities. Scenarios where cross-platform support beyond React Native is necessary.
Is ai-serving or react-native-executorch more popular on GitHub?
react-native-executorch has more GitHub stars (1,696 vs 166). Stars measure visibility, not whether either tool fits your constraints.
Are ai-serving and react-native-executorch open source?
Yes - both are open-source projects on GitHub (ai-serving: Apache-2.0, react-native-executorch: Other).
Where can I find alternatives to ai-serving or react-native-executorch?
GraphCanon lists graph-backed alternatives at ai-serving alternatives and react-native-executorch alternatives (ai-serving markdown twin, react-native-executorch markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, ai-serving or react-native-executorch?
ai-serving: Slowing. react-native-executorch: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for ai-serving and react-native-executorch?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ai-serving trust report; react-native-executorch trust report.

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