--- title: "ai-serving vs pinferencia" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/autodeployai-ai-serving-vs-underneathall-pinferencia" tools: ["autodeployai-ai-serving", "underneathall-pinferencia"] --- # ai-serving vs pinferencia *GraphCanon updated Aug 14, 2026* ## 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 pinferencia if pinferencia is a Python library that simplifies the process of setting up model inference servers with minimal code. [ai-serving](https://github.com/autodeployai/ai-serving) reports 166 GitHub stars, 31 forks, and 3 open issues, last pushed Feb 24, 2026. [pinferencia](https://pinferencia.underneathall.app) has 543 stars, 83 forks, and 17 open issues, last pushed Feb 14, 2023. Figures are from public GitHub metadata via [ai-serving's repository](https://github.com/autodeployai/ai-serving) and [pinferencia's repository](https://github.com/underneathall/pinferencia). | | [ai-serving](/tools/autodeployai-ai-serving.md) | [pinferencia](/tools/underneathall-pinferencia.md) | | --- | --- | --- | | Tagline | Serving AI/ML models in open standard formats PMML and ONNX with HTTP and gRPC endpoints | Python library for simplest model inference server | | Stars | 166 | 543 | | Forks | 31 | 83 | | Open issues | 3 | 17 | | Language | Scala | Python | | Adopt for | Ai-Serving is an inference server supporting PMML and ONNX formats via HTTP or gRPC endpoints, easily deployable with Docker. | Pinferencia is a Python library that simplifies the process of setting up model inference servers with minimal code. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Inference & Serving | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ai-serving](/tools/autodeployai-ai-serving.md) | [pinferencia](/tools/underneathall-pinferencia.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 171d | 1262d | | Open issues (now) | 3 | 17 | | Stars delta | 0 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Full report | [trust report](/tools/autodeployai-ai-serving/trust.md) | [trust report](/tools/underneathall-pinferencia/trust.md) | ## Decision facts: ai-serving - **Adopt for:** Ai-Serving is an inference server supporting PMML and ONNX formats via HTTP or gRPC endpoints, easily deployable with Docker. ## Decision facts: pinferencia - **Adopt for:** Pinferencia is a Python library that simplifies the process of setting up model inference servers with minimal code. ## Choose when ### Choose ai-serving if… - ai-serving is primarily Scala; pinferencia is Python. - Tags unique to ai-serving: ai-serving, grpc, onnx, pmml-deployment. - When you need to serve models in both PMML and ONNX formats without manual configuration changes between formats. ### Choose pinferencia if… - pinferencia is primarily Python; ai-serving is Scala. - Tags unique to pinferencia: ai, artificial-intelligence, computer-vision, data-science. - Pinferencia is a Python library that simplifies the process of setting up model inference servers with minimal code. ## 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. ## When NOT to use pinferencia - Last GitHub push was 1288 days ago (dormant maintenance, Feb 14, 2023). Validate activity before betting a new project on pinferencia. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## Common questions ### What is the difference between ai-serving and pinferencia? ai-serving: Serving AI/ML models in open standard formats PMML and ONNX with HTTP and gRPC endpoints. pinferencia: Python library for simplest model inference server. See the comparison table for live GitHub stats and shared categories. ### When should I choose ai-serving over pinferencia? Choose ai-serving over pinferencia when ai-serving is primarily Scala; pinferencia is Python; Tags unique to ai-serving: ai-serving, grpc, onnx, pmml-deployment; When you need to serve models in both PMML and ONNX formats without manual configuration changes between formats. ### When should I choose pinferencia over ai-serving? Choose pinferencia over ai-serving when pinferencia is primarily Python; ai-serving is Scala; Tags unique to pinferencia: ai, artificial-intelligence, computer-vision, data-science; Pinferencia is a Python library that simplifies the process of setting up model inference servers with minimal code. ### 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 pinferencia? Last GitHub push was 1288 days ago (dormant maintenance, Feb 14, 2023). Validate activity before betting a new project on pinferencia. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### Is ai-serving or pinferencia more popular on GitHub? pinferencia has more GitHub stars (543 vs 166). Stars measure visibility, not whether either tool fits your constraints. ### Are ai-serving and pinferencia open source? Yes - both are open-source projects on GitHub (ai-serving: Apache-2.0, pinferencia: Apache-2.0). ### Where can I find alternatives to ai-serving or pinferencia? GraphCanon lists graph-backed alternatives at [ai-serving alternatives](/tools/autodeployai-ai-serving/alternatives) and [pinferencia alternatives](/tools/underneathall-pinferencia/alternatives) ([ai-serving markdown twin](/tools/autodeployai-ai-serving/alternatives.md), [pinferencia markdown twin](/tools/underneathall-pinferencia/alternatives.md)), 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](/compare/autodeployai-ai-serving-vs-underneathall-pinferencia.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ai-serving or pinferencia? ai-serving: Slowing. pinferencia: Dormant. 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 pinferencia? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ai-serving trust report](/tools/autodeployai-ai-serving/trust); [pinferencia trust report](/tools/underneathall-pinferencia/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=autodeployai-ai-serving`](/api/graphcanon/graph?tool=autodeployai-ai-serving) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_