langflow vs LLMStack

Common questions

What is the difference between langflow and LLMStack?

langflow: Tool for building and deploying AI-powered agents and workflows. LLMStack: No-code multi-agent framework to build LLM Agents, workflows and applications with your data. See the comparison table for live GitHub stats and shared categories.

When should I choose langflow over LLMStack?

Choose langflow over LLMStack when License: langflow is MIT, LLMStack is Other; Pricing: Open-source under MIT license with community and commercial options available; the OSS version is free to use at your own risk.; Requirements: Min 4 GB RAM; Requires Docker; Requires Python 3.10–3.14, the recommended uv package manager is beneficial but not explicitly required for installation.; Docker can be used to start a Langflow container with default settings.; LLMStack and LangFlow are both platforms designed to facilitate the creation of AI agents, workflows, and applications but do so in different ways. LLMStack focuses on a no-code approach for generative AI, while LangFlow offers more flexible tools for building and deploying AI-powered agents; Tags unique to langflow: chatgpt, large language models, multiagent, react-flow; Also covers Model Training; Use Langflow if you are working with Python versions from 3.10 to 3.14, as these versions are specifically supported for seamless operation of the tool.

When should I choose LLMStack over langflow?

Choose LLMStack over langflow when License: LLMStack is Other, langflow is MIT; LLMStack and LangFlow are both platforms designed to facilitate the creation of AI agents, workflows, and applications but do so in different ways. LLMStack focuses on a no-code approach for generative AI, while LangFlow offers more flexible tools for building and deploying AI-powered agents; Tags unique to LLMStack: ai-agents-framework, llm-agents, llm-chain, no-code-ai; Also covers LLM Frameworks; Use LLMStack when you need a no-code solution to develop multi-agent systems based on large language models.

When should I avoid langflow?

Do not use Langflow if your Python environment does not align with version constraints between 3.10 and 3.14. Langflow may not be the best fit if you are seeking a platform that operates without any language model integration, as it fundamentally relies on such models for its functionality.

When should I avoid LLMStack?

Avoid using LLMStack if your project necessitates heavy customization or fine-tuning at the coding level, as it may limit flexibility compared to code-based alternatives. Not recommended for teams with robust software engineering capabilities and a need for detailed control over underlying AI model architectures.

Is langflow or LLMStack more popular on GitHub?

langflow has more GitHub stars (152,744 vs 2,309). Stars measure visibility, not whether either tool fits your constraints.

Are langflow and LLMStack open source?

Yes - both are open-source projects on GitHub (langflow: MIT, LLMStack: Other).

Where can I find alternatives to langflow or LLMStack?

GraphCanon lists graph-backed alternatives at langflow alternatives and LLMStack alternatives (langflow markdown twin, LLMStack 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, langflow or LLMStack?

langflow: Very active. LLMStack: 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 langflow and LLMStack?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: langflow trust report; LLMStack trust report.