--- title: "infinity vs langcorn" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/michaelfeil-infinity-vs-msoedov-langcorn" tools: ["michaelfeil-infinity", "msoedov-langcorn"] --- # infinity vs langcorn *GraphCanon updated Aug 21, 2026* ## Verdict Pick infinity if infinity is a high-throughput, low-latency serving engine that supports text-embeddings, reranking models, CLIP, CLAP, and ColPaLi, with GPU acceleration including ROCm and TensorRT; pick langcorn if langCorn is a tool that serves LangChain LLM apps and agents with FastApi. [infinity](https://michaelfeil.github.io/infinity/) reports 2.9k GitHub stars, 196 forks, and 130 open issues, last pushed Mar 24, 2026. [langcorn](https://langcorn.vercel.app/docs) has 938 stars, 69 forks, and 21 open issues, last pushed Jul 15, 2024. Figures are from public GitHub metadata via [infinity's repository](https://github.com/michaelfeil/infinity) and [langcorn's repository](https://github.com/msoedov/langcorn). | | [infinity](/tools/michaelfeil-infinity.md) | [langcorn](/tools/msoedov-langcorn.md) | | --- | --- | --- | | Tagline | High-throughput, low-latency serving engine for text-embeddings and various models | Serving LangChain LLM apps and agents automagically with FastApi | | Stars | 2,907 | 938 | | Forks | 196 | 69 | | Open issues | 130 | 21 | | Language | Python | Python | | Adopt for | Infinity is a high-throughput, low-latency serving engine that supports text-embeddings, reranking models, CLIP, CLAP, and ColPaLi, with GPU acceleration including ROCm and TensorRT. | LangCorn is a tool that serves LangChain LLM apps and agents with FastApi. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Inference & Serving | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [infinity](/tools/michaelfeil-infinity.md) | [langcorn](/tools/msoedov-langcorn.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 136d | 766d | | Open issues (now) | 130 | 21 | | Stars delta | Unknown | 0 (30d) | | Open issues delta | Unknown | 0 (30d) | | Full report | [trust report](/tools/michaelfeil-infinity/trust.md) | [trust report](/tools/msoedov-langcorn/trust.md) | ## Shared compatibility - **Python**: [infinity](/tools/michaelfeil-infinity.md) - Python runtime; [langcorn](/tools/msoedov-langcorn.md) - Python runtime ## Decision facts: infinity - **Adopt for:** Infinity is a high-throughput, low-latency serving engine that supports text-embeddings, reranking models, CLIP, CLAP, and ColPaLi, with GPU acceleration including ROCm and TensorRT. ## Decision facts: langcorn - **Adopt for:** LangCorn is a tool that serves LangChain LLM apps and agents with FastApi. ## Choose when ### Choose infinity if… - Tags unique to infinity: clap, clip, colpali, docker-container. - When you need to serve embeddings and various models with high throughput and low latency. - More GitHub stars (2.9k vs 938) - visibility, not fit. ### Choose langcorn if… - Tags unique to langcorn: api, fastapi, langchain, large language models. - When you are deploying applications built with Large Language Models (LLMs) like OpenAI. - Leaner open-issue backlog (21). ## When NOT to use infinity - Avoid using Infinity if your setup does not require GPU acceleration since its specialized Docker images may introduce unnecessary complexity. - Do not use Infinity if you are working with models that are not supported by it (such as specific NLP models outside of embeddings and reranking). ## When NOT to use langcorn - When you require a framework other than FastAPI for your deployment needs. - If you are looking for broader support beyond LangChain-compatible projects. - In cases where minimal integration with the current infrastructure is not acceptable, as LangCorn requires specific adaptation steps. ## Common questions ### What is the difference between infinity and langcorn? infinity: High-throughput, low-latency serving engine for text-embeddings and various models. langcorn: Serving LangChain LLM apps and agents automagically with FastApi. See the comparison table for live GitHub stats and shared categories. ### When should I choose infinity over langcorn? Choose infinity over langcorn when Tags unique to infinity: clap, clip, colpali, docker-container; When you need to serve embeddings and various models with high throughput and low latency; More GitHub stars (2.9k vs 938) - visibility, not fit. ### When should I choose langcorn over infinity? Choose langcorn over infinity when Tags unique to langcorn: api, fastapi, langchain, large language models; When you are deploying applications built with Large Language Models (LLMs) like OpenAI; Leaner open-issue backlog (21). ### When should I avoid infinity? Avoid using Infinity if your setup does not require GPU acceleration since its specialized Docker images may introduce unnecessary complexity. Do not use Infinity if you are working with models that are not supported by it (such as specific NLP models outside of embeddings and reranking). ### When should I avoid langcorn? When you require a framework other than FastAPI for your deployment needs. If you are looking for broader support beyond LangChain-compatible projects. In cases where minimal integration with the current infrastructure is not acceptable, as LangCorn requires specific adaptation steps. ### Is infinity or langcorn more popular on GitHub? infinity has more GitHub stars (2,907 vs 938). Stars measure visibility, not whether either tool fits your constraints. ### Are infinity and langcorn open source? Yes - both are open-source projects on GitHub (infinity: MIT, langcorn: MIT). ### Where can I find alternatives to infinity or langcorn? GraphCanon lists graph-backed alternatives at [infinity alternatives](/tools/michaelfeil-infinity/alternatives) and [langcorn alternatives](/tools/msoedov-langcorn/alternatives) ([infinity markdown twin](/tools/michaelfeil-infinity/alternatives.md), [langcorn markdown twin](/tools/msoedov-langcorn/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/michaelfeil-infinity-vs-msoedov-langcorn.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, infinity or langcorn? infinity: Slowing. langcorn: 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 infinity and langcorn? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [infinity trust report](/tools/michaelfeil-infinity/trust); [langcorn trust report](/tools/msoedov-langcorn/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=michaelfeil-infinity`](/api/graphcanon/graph?tool=michaelfeil-infinity) - 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/_