Comparison
ai-serving vs runanywhere-sdks
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 runanywhere-sdks if runAnywhere SDKs enable efficient cross-platform deployment of various AI models on local devices with support for specific hardware optimizations.
Markdown twin · ai-serving alternatives · runanywhere-sdks alternatives
GraphCanon updated Sep 20, 2026
10views this month
vs
Trust & integrity
| Signal | ai-serving | runanywhere-sdks |
|---|---|---|
| Maintenance | Slowing (208d since push) As of Sep 20, 2026 · github_public_v1 | Very active (0d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 2026 · 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
- runanywhere-sdks
- Production ready toolkit to run AI locally
Stars
- ai-serving
- 166
- runanywhere-sdks
- 10k
Forks
- ai-serving
- 31
- runanywhere-sdks
- 380
Open issues
- ai-serving
- 3
- runanywhere-sdks
- 136
Language
- ai-serving
- Scala
- runanywhere-sdks
- 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.
- runanywhere-sdks
- RunAnywhere SDKs enable efficient cross-platform deployment of various AI models on local devices with support for specific hardware optimizations.
Persona
- ai-serving
- -
- runanywhere-sdks
- -
Runtime
- ai-serving
- -
- runanywhere-sdks
- -
License
- ai-serving
- Apache-2.0
- runanywhere-sdks
- Apache 2.0 with additional terms for commercial use
Last pushed
- ai-serving
- Feb 24, 2026
- runanywhere-sdks
- Sep 19, 2026
Categories
- ai-serving
- Inference & Serving
- runanywhere-sdks
- Inference & Serving
Trust and health
Maintenance
- ai-serving
- Slowing (36%)
- runanywhere-sdks
- Very active (96%)
Days since push
- ai-serving
- 208d
- runanywhere-sdks
- 0d
Open issues (now)
- ai-serving
- 3
- runanywhere-sdks
- 136
Stars delta
- ai-serving
- 0 (30d)
- runanywhere-sdks
- -3 (30d)
Open issues delta
- ai-serving
- 0 (30d)
- runanywhere-sdks
- +120 (30d)
Full report
- ai-serving
- Trust report
- runanywhere-sdks
- Trust report
Choose ai-serving if…
- ai-serving is primarily Scala; runanywhere-sdks is C++.
- License: ai-serving is Apache-2.0, runanywhere-sdks 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 runanywhere-sdks if…
- runanywhere-sdks is primarily C++; ai-serving is Scala.
- License: runanywhere-sdks is Other, ai-serving is Apache-2.0.
- Requirements: Min 2 GB RAM; Hexagon NPU for Snapdragon 8 Elite class or newer.
- Tags unique to runanywhere-sdks: android, cpp, diffusion-models, edge.
- When deploying AI models that need to run locally across multiple platforms including Web, iOS, macOS, Android, React Native, and Flutter
When NOT to use runanywhere-sdks
- If your deployment does not require support for older versions of Android below API level 24 or macOS earlier than version 14.0+
- In environments that do not meet the minimum hardware requirements, such as devices with less than 2 GB of RAM
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (autodeployai/ai-serving) · observed Sep 20, 2026
- GitHub forks (autodeployai/ai-serving) · observed Sep 20, 2026
- Last push (autodeployai/ai-serving) · observed Feb 24, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (RunanywhereAI/runanywhere-sdks) · observed Sep 20, 2026
- GitHub forks (RunanywhereAI/runanywhere-sdks) · observed Sep 20, 2026
- Last push (RunanywhereAI/runanywhere-sdks) · observed Sep 19, 2026
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: ai-serving 166 · runanywhere-sdks 10k (synced Sep 20, 2026).
Common questions
- What is the difference between ai-serving and runanywhere-sdks?
- ai-serving: Serving AI/ML models in open standard formats PMML and ONNX with HTTP and gRPC endpoints. runanywhere-sdks: Production ready toolkit to run AI locally. See the comparison table for live GitHub stats and shared categories.
- When should I choose ai-serving over runanywhere-sdks?
- Choose ai-serving over runanywhere-sdks when ai-serving is primarily Scala; runanywhere-sdks is C++; License: ai-serving is Apache-2.0, runanywhere-sdks 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 runanywhere-sdks over ai-serving?
- Choose runanywhere-sdks over ai-serving when runanywhere-sdks is primarily C++; ai-serving is Scala; License: runanywhere-sdks is Other, ai-serving is Apache-2.0; Requirements: Min 2 GB RAM; Hexagon NPU for Snapdragon 8 Elite class or newer; Tags unique to runanywhere-sdks: android, cpp, diffusion-models, edge; When deploying AI models that need to run locally across multiple platforms including Web, iOS, macOS, Android, React Native, and Flutter.
- 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 runanywhere-sdks?
- If your deployment does not require support for older versions of Android below API level 24 or macOS earlier than version 14.0+ In environments that do not meet the minimum hardware requirements, such as devices with less than 2 GB of RAM
- Is ai-serving or runanywhere-sdks more popular on GitHub?
- runanywhere-sdks has more GitHub stars (10,297 vs 166). Stars measure visibility, not whether either tool fits your constraints.
- Are ai-serving and runanywhere-sdks open source?
- Yes - both are open-source projects on GitHub (ai-serving: Apache-2.0, runanywhere-sdks: Other).
- Where can I find alternatives to ai-serving or runanywhere-sdks?
- GraphCanon lists graph-backed alternatives at ai-serving alternatives and runanywhere-sdks alternatives (ai-serving markdown twin, runanywhere-sdks 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 runanywhere-sdks?
- ai-serving: Slowing. runanywhere-sdks: 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 runanywhere-sdks?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ai-serving trust report; runanywhere-sdks trust report.