Comparison
ai-serving vs seldon-core
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 seldon-core if seldon-core is an MLOps framework designed for managing machine learning models in Kubernetes environments.
Markdown twin · ai-serving alternatives · seldon-core alternatives
GraphCanon updated 1w
vs
Trust & integrity
| Signal | ai-serving | seldon-core |
|---|---|---|
| Maintenance | Slowing (171d since push) As of 1w · github_public_v1 | Slowing (133d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 1w · github_public_v1 | Not a fork · Organization account As of 3w · 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
- seldon-core
- An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
Stars
- ai-serving
- 166
- seldon-core
- 4.8k
Forks
- ai-serving
- 31
- seldon-core
- 867
Open issues
- ai-serving
- 3
- seldon-core
- 396
Language
- ai-serving
- Scala
- seldon-core
- Go
Adopt for
- ai-serving
- Ai-Serving is an inference server supporting PMML and ONNX formats via HTTP or gRPC endpoints, easily deployable with Docker.
- seldon-core
- seldon-core is an MLOps framework designed for managing machine learning models in Kubernetes environments.
Persona
- ai-serving
- -
- seldon-core
- -
Runtime
- ai-serving
- -
- seldon-core
- -
License
- ai-serving
- Apache-2.0
- seldon-core
- SeldonIO/seldon-core uses The Business Source License for distribution
Last pushed
- ai-serving
- Feb 24, 2026
- seldon-core
- Mar 23, 2026
Categories
- ai-serving
- Inference & Serving
- seldon-core
- Inference & Serving
Trust and health
Days since push
- ai-serving
- 171d
- seldon-core
- 133d
Open issues (now)
- ai-serving
- 3
- seldon-core
- 396
Stars delta
- ai-serving
- 0 (30d)
- seldon-core
- Unknown
Open issues delta
- ai-serving
- 0 (30d)
- seldon-core
- Unknown
Full report
- ai-serving
- Trust report
- seldon-core
- Trust report
Choose ai-serving if…
- ai-serving is primarily Scala; seldon-core is Go.
- License: ai-serving is Apache-2.0, seldon-core 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 seldon-core if…
- seldon-core is primarily Go; ai-serving is Scala.
- License: seldon-core is Other, ai-serving is Apache-2.0.
- Requirements: Requires Docker; Requires Docker for deployment environments.
- Tags unique to seldon-core: aiops, deployment, kubernetes, machine-learning-operations.
- If you are deploying and serving ML models on Kubernetes clusters, seldon-core provides specialized capabilities within its MLOps framework to facilitate this.
When NOT to use seldon-core
- Consider alternatives if you are not running your infrastructure on Kubernetes, since seldon-core is optimized for Kubernetes environments.
- If compatibility or licensing concerns arise due to the Business Source License under which Seldon is distributed, explore other frameworks with more permissive licenses.
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 Aug 14, 2026
- GitHub forks (autodeployai/ai-serving) · observed Aug 14, 2026
- Last push (autodeployai/ai-serving) · observed Feb 24, 2026
- License file (Apache-2.0) · observed Aug 14, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (SeldonIO/seldon-core) · observed Aug 3, 2026
- GitHub forks (SeldonIO/seldon-core) · observed Aug 3, 2026
- Last push (SeldonIO/seldon-core) · observed Mar 23, 2026
- License file (Other) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: ai-serving 166 · seldon-core 4.8k (synced Aug 14, 2026).
Common questions
- What is the difference between ai-serving and seldon-core?
- ai-serving: Serving AI/ML models in open standard formats PMML and ONNX with HTTP and gRPC endpoints. seldon-core: An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models. See the comparison table for live GitHub stats and shared categories.
- When should I choose ai-serving over seldon-core?
- Choose ai-serving over seldon-core when ai-serving is primarily Scala; seldon-core is Go; License: ai-serving is Apache-2.0, seldon-core 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 seldon-core over ai-serving?
- Choose seldon-core over ai-serving when seldon-core is primarily Go; ai-serving is Scala; License: seldon-core is Other, ai-serving is Apache-2.0; Requirements: Requires Docker; Requires Docker for deployment environments; Tags unique to seldon-core: aiops, deployment, kubernetes, machine-learning-operations; If you are deploying and serving ML models on Kubernetes clusters, seldon-core provides specialized capabilities within its MLOps framework to facilitate this.
- 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 seldon-core?
- Consider alternatives if you are not running your infrastructure on Kubernetes, since seldon-core is optimized for Kubernetes environments. If compatibility or licensing concerns arise due to the Business Source License under which Seldon is distributed, explore other frameworks with more permissive licenses.
- Is ai-serving or seldon-core more popular on GitHub?
- seldon-core has more GitHub stars (4,765 vs 166). Stars measure visibility, not whether either tool fits your constraints.
- Are ai-serving and seldon-core open source?
- Yes - both are open-source projects on GitHub (ai-serving: Apache-2.0, seldon-core: Other).
- Where can I find alternatives to ai-serving or seldon-core?
- GraphCanon lists graph-backed alternatives at ai-serving alternatives and seldon-core alternatives (ai-serving markdown twin, seldon-core 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 seldon-core?
- ai-serving: Slowing. seldon-core: Slowing. 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 seldon-core?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ai-serving trust report; seldon-core trust report.