--- title: "Kiln vs langflow" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/kiln-ai-kiln-vs-langflow-ai-langflow" tools: ["kiln-ai-kiln", "langflow-ai-langflow"] --- # Kiln vs langflow *GraphCanon updated Jul 12, 2026* ## Verdict Pick Kiln when license: Kiln is Other, langflow is MIT; pick langflow when license: langflow is MIT, Kiln is Other. [Kiln](https://kiln.tech) reports 5.0k GitHub stars, 375 forks, and 63 open issues, last pushed Jul 11, 2026. [langflow](http://www.langflow.org) has 152k stars, 9.7k forks, and 975 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [Kiln's repository](https://github.com/Kiln-AI/Kiln) and [langflow's repository](https://github.com/langflow-ai/langflow). | | [Kiln](/tools/kiln-ai-kiln.md) | [langflow](/tools/langflow-ai-langflow.md) | | --- | --- | --- | | Tagline | Build, Evaluate, and Optimize AI Systems. Includes evals, RAG, agents, fine-tuning, synthetic data generation, dataset management, MCP, and more. | Langflow is a powerful tool for building and deploying AI-powered agents and workflows. | | Stars | 4,960 | 151,697 | | Forks | 375 | 9,654 | | Open issues | 63 | 975 | | Language | Python | Python | | Adopt for | - | Langflow specializes in creating and deploying AI agents and complex workflows through a versatile GUI-based approach. | | Persona | - | - | | Runtime | - | - | | License | Other | MIT | | Categories | AI Agents, Inference & Serving, LLM Frameworks | AI Agents, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Kiln](/tools/kiln-ai-kiln.md) | [langflow](/tools/langflow-ai-langflow.md) | | --- | --- | --- | | Open issues (now) | 63 | 975 | | Security scan | No MCP manifest | No criticals | | Full report | [trust report](/tools/kiln-ai-kiln/trust.md) | [trust report](/tools/langflow-ai-langflow/trust.md) | ## Decision facts: langflow - **Adopt for:** Langflow specializes in creating and deploying AI agents and complex workflows through a versatile GUI-based approach. ## Choose when ### Choose Kiln if… - License: Kiln is Other, langflow is MIT. - Tags unique to Kiln: ai, chain-of-thought, collaboration, dataset-generation. - Also covers LLM Frameworks. ### Choose langflow if… - License: langflow is MIT, Kiln is Other. - Tags unique to langflow: agents, chatgpt, generative-ai, large-language-models. - - When you need an intuitive graphical interface to manage the creation of AI agents and workflows without deep coding knowledge. ## When NOT to use Kiln - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use langflow - - For developers preferring a code-first approach who find GUI interfaces restrictive for customization and workflow. - - When the project does not align with or leverage the specific topics of focus such as ChatGPT, multi-agent systems, or requires integration with platforms that Langflow's graphical interface cannot旖 ## Common questions ### What is the difference between Kiln and langflow? Kiln: Build, Evaluate, and Optimize AI Systems. Includes evals, RAG, agents, fine-tuning, synthetic data generation, dataset management, MCP, and more.. langflow: Langflow is a powerful tool for building and deploying AI-powered agents and workflows.. See the comparison table for live GitHub stats and shared categories. ### When should I choose Kiln over langflow? Choose Kiln over langflow when License: Kiln is Other, langflow is MIT; Tags unique to Kiln: ai, chain-of-thought, collaboration, dataset-generation; Also covers LLM Frameworks. ### When should I choose langflow over Kiln? Choose langflow over Kiln when License: langflow is MIT, Kiln is Other; Tags unique to langflow: agents, chatgpt, generative-ai, large-language-models; - When you need an intuitive graphical interface to manage the creation of AI agents and workflows without deep coding knowledge. ### When should I avoid Kiln? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid langflow? - For developers preferring a code-first approach who find GUI interfaces restrictive for customization and workflow. - When the project does not align with or leverage the specific topics of focus such as ChatGPT, multi-agent systems, or requires integration with platforms that Langflow's graphical interface cannot旖 ### Is Kiln or langflow more popular on GitHub? langflow has more GitHub stars (151,697 vs 4,960). Stars measure visibility, not whether either tool fits your constraints. ### Are Kiln and langflow open source? Yes - both are open-source projects on GitHub (Kiln: Other, langflow: MIT). ### Where can I find alternatives to Kiln or langflow? GraphCanon lists graph-backed alternatives at [Kiln alternatives](/tools/kiln-ai-kiln/alternatives) and [langflow alternatives](/tools/langflow-ai-langflow/alternatives) ([Kiln markdown twin](/tools/kiln-ai-kiln/alternatives.md), [langflow markdown twin](/tools/langflow-ai-langflow/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/kiln-ai-kiln-vs-langflow-ai-langflow.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Kiln or langflow? Kiln: Very active. langflow: 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 Kiln and langflow? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Kiln trust report](/tools/kiln-ai-kiln/trust); [langflow trust report](/tools/langflow-ai-langflow/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=kiln-ai-kiln`](/api/graphcanon/graph?tool=kiln-ai-kiln) - 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/_