--- title: "langflow vs blast" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/langflow-ai-langflow-vs-stanford-mast-blast" tools: ["langflow-ai-langflow", "stanford-mast-blast"] --- # langflow vs blast *GraphCanon updated Jul 11, 2026* ## Verdict Pick langflow when tags unique to langflow: multiagent, agents, large-language-models, generative-ai; pick blast when tags unique to blast: browser-automation, llm-inference, ai-agents. [langflow](http://www.langflow.org) reports 152k GitHub stars, 9.7k forks, and 975 open issues, last pushed Jul 11, 2026. [blast](http://blastproject.org/) has 776 stars, 50 forks, and 6 open issues, last pushed May 29, 2026. Figures are from public GitHub metadata via [langflow's repository](https://github.com/langflow-ai/langflow) and [blast's repository](https://github.com/stanford-mast/blast). | | [langflow](/tools/langflow-ai-langflow.md) | [blast](/tools/stanford-mast-blast.md) | | --- | --- | --- | | Tagline | Langflow is a powerful tool for building and deploying AI-powered agents and workflows. | Open-source VMs-as-a-service | | Stars | 151,697 | 776 | | Forks | 9,654 | 50 | | Open issues | 975 | 6 | | 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 | MIT | MIT | | Categories | AI Agents, Inference & Serving | LLM Frameworks, AI Agents, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [langflow](/tools/langflow-ai-langflow.md) | [blast](/tools/stanford-mast-blast.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 42d | | Open issues (now) | 975 | 6 | | Security scan | No criticals | No lockfile | | Full report | [trust report](/tools/langflow-ai-langflow/trust.md) | [trust report](/tools/stanford-mast-blast/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 langflow if… - Tags unique to langflow: multiagent, agents, large-language-models, generative-ai. - - When you need an intuitive graphical interface to manage the creation of AI agents and workflows without deep coding knowledge. - More GitHub stars (152k vs 776) - visibility, not fit. ### Choose blast if… - Tags unique to blast: browser-automation, llm-inference, ai-agents. - Also covers LLM Frameworks. - Leaner open-issue backlog (6). ## 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 ## When NOT to use blast - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - 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. ## Common questions ### What is the difference between langflow and blast? langflow: Langflow is a powerful tool for building and deploying AI-powered agents and workflows.. blast: Open-source VMs-as-a-service. See the comparison table for live GitHub stats and shared categories. ### When should I choose langflow over blast? Choose langflow over blast when Tags unique to langflow: multiagent, agents, large-language-models, generative-ai; - When you need an intuitive graphical interface to manage the creation of AI agents and workflows without deep coding knowledge; More GitHub stars (152k vs 776) - visibility, not fit. ### When should I choose blast over langflow? Choose blast over langflow when Tags unique to blast: browser-automation, llm-inference, ai-agents; Also covers LLM Frameworks; Leaner open-issue backlog (6). ### 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 ### When should I avoid blast? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. 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. ### Is langflow or blast more popular on GitHub? langflow has more GitHub stars (151,697 vs 776). Stars measure visibility, not whether either tool fits your constraints. ### Are langflow and blast open source? Yes - both are open-source projects on GitHub (langflow: MIT, blast: MIT). ### Where can I find alternatives to langflow or blast? GraphCanon lists graph-backed alternatives at [langflow alternatives](/tools/langflow-ai-langflow/alternatives) and [blast alternatives](/tools/stanford-mast-blast/alternatives) ([langflow markdown twin](/tools/langflow-ai-langflow/alternatives.md), [blast markdown twin](/tools/stanford-mast-blast/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/langflow-ai-langflow-vs-stanford-mast-blast.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, langflow or blast? langflow: Very active. blast: Steady. 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 blast? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [langflow trust report](/tools/langflow-ai-langflow/trust); [blast trust report](/tools/stanford-mast-blast/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=langflow-ai-langflow`](/api/graphcanon/graph?tool=langflow-ai-langflow) - 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/_