--- title: "firecrawl vs deepfabric" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/firecrawl-firecrawl-vs-nolabs-ai-deepfabric" tools: ["firecrawl-firecrawl", "nolabs-ai-deepfabric"] --- # firecrawl vs deepfabric *GraphCanon updated Jul 12, 2026* ## Verdict Pick firecrawl when firecrawl is primarily TypeScript; deepfabric is Python; pick deepfabric when deepfabric is primarily Python; firecrawl is TypeScript. [firecrawl](https://firecrawl.dev) reports 149k GitHub stars, 8.5k forks, and 395 open issues, last pushed Jul 11, 2026. [deepfabric](http://docs.deepfabric.dev) has 877 stars, 83 forks, and 23 open issues, last pushed Jul 3, 2026. Figures are from public GitHub metadata via [firecrawl's repository](https://github.com/firecrawl/firecrawl) and [deepfabric's repository](https://github.com/nolabs-ai/deepfabric). | | [firecrawl](/tools/firecrawl-firecrawl.md) | [deepfabric](/tools/nolabs-ai-deepfabric.md) | | --- | --- | --- | | Tagline | The API to search, scrape, and interact with the web at scale. 🔥 | Generate High-Quality Synthetics, Train, Measure, and Evaluate in a Single Pipeline | | Stars | 149,109 | 877 | | Forks | 8,524 | 83 | | Open issues | 395 | 23 | | Language | TypeScript | Python | | Adopt for | FireCrawl is an API-driven toolkit built for conducting scalable searches, scraping tasks, and interactive operations with the web using AI agents. | - | | Persona | - | - | | Runtime | - | - | | License | AGPL-3.0 license requires that any changes to FireCrawl's source code also be made available as free software when the adapted version is used. | Apache-2.0 | | Categories | AI Agents, Data & Retrieval | AI Agents, Data & Retrieval, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [firecrawl](/tools/firecrawl-firecrawl.md) | [deepfabric](/tools/nolabs-ai-deepfabric.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 7d | | Open issues (now) | 395 | 23 | | Full report | [trust report](/tools/firecrawl-firecrawl/trust.md) | [trust report](/tools/nolabs-ai-deepfabric/trust.md) | ## Decision facts: firecrawl - **Hosting:** self hosted - FireCrawl can be deployed on your infrastructure, giving you complete control over where and how the API interacts with web data. - **Requirements:** Min 4 GB RAM; Requires Docker - **Adopt for:** FireCrawl is an API-driven toolkit built for conducting scalable searches, scraping tasks, and interactive operations with the web using AI agents. - **License detail:** AGPL-3.0 license requires that any changes to FireCrawl's source code also be made available as free software when the adapted version is used. ## Choose when ### Choose firecrawl if… - firecrawl is primarily TypeScript; deepfabric is Python. - License: firecrawl is AGPL-3.0, deepfabric is Apache-2.0. - FireCrawl can be deployed on your infrastructure, giving you complete control over where and how the API interacts with web data. - Requirements: Min 4 GB RAM; Requires Docker. - Tags unique to firecrawl: ai-agents, crawler, scraping, search. - When you need to automate complex web interactions that require understanding context or content from multiple sources, leveraging its AI agent capabilities. ### Choose deepfabric if… - deepfabric is primarily Python; firecrawl is TypeScript. - License: deepfabric is Apache-2.0, firecrawl is AGPL-3.0. - Tags unique to deepfabric: agents, ai, data-science, dataset. - Also covers Model Training. ## When NOT to use firecrawl - For lightweight scraping tasks where minimal data extraction is sufficient and speed is of utmost importance without the need for advanced AI analysis. - If you require open-source components under a license other than AGPL-3.0, as this license may impose certain restrictions on derivative works. ## When NOT to use deepfabric - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## Common questions ### What is the difference between firecrawl and deepfabric? firecrawl: The API to search, scrape, and interact with the web at scale. 🔥. deepfabric: Generate High-Quality Synthetics, Train, Measure, and Evaluate in a Single Pipeline. See the comparison table for live GitHub stats and shared categories. ### When should I choose firecrawl over deepfabric? Choose firecrawl over deepfabric when firecrawl is primarily TypeScript; deepfabric is Python; License: firecrawl is AGPL-3.0, deepfabric is Apache-2.0; FireCrawl can be deployed on your infrastructure, giving you complete control over where and how the API interacts with web data; Requirements: Min 4 GB RAM; Requires Docker; Tags unique to firecrawl: ai-agents, crawler, scraping, search; When you need to automate complex web interactions that require understanding context or content from multiple sources, leveraging its AI agent capabilities. ### When should I choose deepfabric over firecrawl? Choose deepfabric over firecrawl when deepfabric is primarily Python; firecrawl is TypeScript; License: deepfabric is Apache-2.0, firecrawl is AGPL-3.0; Tags unique to deepfabric: agents, ai, data-science, dataset; Also covers Model Training. ### When should I avoid firecrawl? For lightweight scraping tasks where minimal data extraction is sufficient and speed is of utmost importance without the need for advanced AI analysis. If you require open-source components under a license other than AGPL-3.0, as this license may impose certain restrictions on derivative works. ### When should I avoid deepfabric? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### Is firecrawl or deepfabric more popular on GitHub? firecrawl has more GitHub stars (149,109 vs 877). Stars measure visibility, not whether either tool fits your constraints. ### Are firecrawl and deepfabric open source? Yes - both are open-source projects on GitHub (firecrawl: AGPL-3.0, deepfabric: Apache-2.0). ### Where can I find alternatives to firecrawl or deepfabric? GraphCanon lists graph-backed alternatives at [firecrawl alternatives](/tools/firecrawl-firecrawl/alternatives) and [deepfabric alternatives](/tools/nolabs-ai-deepfabric/alternatives) ([firecrawl markdown twin](/tools/firecrawl-firecrawl/alternatives.md), [deepfabric markdown twin](/tools/nolabs-ai-deepfabric/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/firecrawl-firecrawl-vs-nolabs-ai-deepfabric.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, firecrawl or deepfabric? firecrawl: Very active. deepfabric: 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 firecrawl and deepfabric? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [firecrawl trust report](/tools/firecrawl-firecrawl/trust); [deepfabric trust report](/tools/nolabs-ai-deepfabric/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=firecrawl-firecrawl`](/api/graphcanon/graph?tool=firecrawl-firecrawl) - 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/_