--- title: "ai-serving vs caffe" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/autodeployai-ai-serving-vs-bvlc-caffe" tools: ["autodeployai-ai-serving", "bvlc-caffe"] --- # ai-serving vs caffe *GraphCanon updated Jul 15, 2026* ## Verdict Pick ai-serving when ai-serving is primarily Scala; caffe is C++; pick caffe when caffe is primarily C++; ai-serving is Scala. [ai-serving](https://github.com/autodeployai/ai-serving) reports 166 GitHub stars, 31 forks, and 3 open issues, last pushed Feb 24, 2026. [caffe](http://caffe.berkeleyvision.org/) has 35k stars, 18k forks, and 1.2k open issues, last pushed Jul 31, 2024. Figures are from public GitHub metadata via [ai-serving's repository](https://github.com/autodeployai/ai-serving) and [caffe's repository](https://github.com/BVLC/caffe). | | [ai-serving](/tools/autodeployai-ai-serving.md) | [caffe](/tools/bvlc-caffe.md) | | --- | --- | --- | | Tagline | Serving AI/ML models in the open standard formats PMML and ONNX with both HTTP (REST API) and gRPC endpoints | Caffe: a fast open framework for deep learning. | | Stars | 166 | 34,574 | | Forks | 31 | 18,458 | | Open issues | 3 | 1,209 | | Language | Scala | C++ | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Other | | Categories | Computer Vision, Inference & Serving | Computer Vision, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ai-serving](/tools/autodeployai-ai-serving.md) | [caffe](/tools/bvlc-caffe.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 141d | 710d | | Open issues (now) | 3 | 1.2k | | Full report | [trust report](/tools/autodeployai-ai-serving/trust.md) | [trust report](/tools/bvlc-caffe/trust.md) | ## Choose when ### Choose ai-serving if… - ai-serving is primarily Scala; caffe is C++. - License: ai-serving is Apache-2.0, caffe is Other. - Tags unique to ai-serving: ai-serving, inference, inference-server, onnx. - Also covers Inference & Serving. ### Choose caffe if… - caffe is primarily C++; ai-serving is Scala. - License: caffe is Other, ai-serving is Apache-2.0. - Tags unique to caffe: c#, deep-learning, machine-learning, vision. - Also covers Vector Databases. ## When NOT to use ai-serving - Last GitHub push was 141 days ago (slowing maintenance, Feb 24, 2026). Validate activity before betting a new project on ai-serving. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## When NOT to use caffe - Last GitHub push was 713 days ago (dormant maintenance, Jul 31, 2024). Validate activity before betting a new project on caffe. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between ai-serving and caffe? ai-serving: Serving AI/ML models in the open standard formats PMML and ONNX with both HTTP (REST API) and gRPC endpoints. caffe: Caffe: a fast open framework for deep learning.. See the comparison table for live GitHub stats and shared categories. ### When should I choose ai-serving over caffe? Choose ai-serving over caffe when ai-serving is primarily Scala; caffe is C++; License: ai-serving is Apache-2.0, caffe is Other; Tags unique to ai-serving: ai-serving, inference, inference-server, onnx; Also covers Inference & Serving. ### When should I choose caffe over ai-serving? Choose caffe over ai-serving when caffe is primarily C++; ai-serving is Scala; License: caffe is Other, ai-serving is Apache-2.0; Tags unique to caffe: c#, deep-learning, machine-learning, vision; Also covers Vector Databases. ### When should I avoid ai-serving? Last GitHub push was 141 days ago (slowing maintenance, Feb 24, 2026). Validate activity before betting a new project on ai-serving. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### When should I avoid caffe? Last GitHub push was 713 days ago (dormant maintenance, Jul 31, 2024). Validate activity before betting a new project on caffe. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is ai-serving or caffe more popular on GitHub? caffe has more GitHub stars (34,574 vs 166). Stars measure visibility, not whether either tool fits your constraints. ### Are ai-serving and caffe open source? Yes - both are open-source projects on GitHub (ai-serving: Apache-2.0, caffe: Other). ### Where can I find alternatives to ai-serving or caffe? GraphCanon lists graph-backed alternatives at [ai-serving alternatives](/tools/autodeployai-ai-serving/alternatives) and [caffe alternatives](/tools/bvlc-caffe/alternatives) ([ai-serving markdown twin](/tools/autodeployai-ai-serving/alternatives.md), [caffe markdown twin](/tools/bvlc-caffe/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-bvlc-caffe.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ai-serving or caffe? ai-serving: Slowing. caffe: 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 caffe? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ai-serving trust report](/tools/autodeployai-ai-serving/trust); [caffe trust report](/tools/bvlc-caffe/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/_