Comparison
FastGPT vs quilt
Verdict
Pick FastGPT if fastGPT is a knowledge-based platform optimized for developing and deploying complex question-answering systems with built-in capabilities to process data, retrieve relevant information through RAG techniques, and enable; pick quilt if quilt is a platform focused on managing scientific and AI-related datasets through detailed version control and context-rich data packages hosted on AWS.
Markdown twin · FastGPT alternatives · quilt alternatives
GraphCanon updated 1w
Trust & integrity
| Signal | FastGPT | quilt |
|---|---|---|
| Maintenance | Very active (0d since push) As of 1w · github_public_v1 | Very active (2d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 1w · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- FastGPT
- A knowledge-based platform built on LLMs for developing and deploying complex question-answering systems
- quilt
- Scientific Data Management Platform on AWS for managing data packages
Stars
- FastGPT
- 29k
- quilt
- 1.4k
Forks
- FastGPT
- 7.3k
- quilt
- 90
Open issues
- FastGPT
- 165
- quilt
- 143
Language
- FastGPT
- TypeScript
- quilt
- TypeScript
Adopt for
- FastGPT
- FastGPT is a knowledge-based platform optimized for developing and deploying complex question-answering systems with built-in capabilities to process data, retrieve relevant information through RAG techniques, and enable
- quilt
- Quilt is a platform focused on managing scientific and AI-related datasets through detailed version control and context-rich data packages hosted on AWS.
Persona
- FastGPT
- -
- quilt
- -
Runtime
- FastGPT
- -
- quilt
- -
License
- FastGPT
- Other
- quilt
- Apache-2.0
Last pushed
- FastGPT
- Aug 16, 2026
- quilt
- Jul 31, 2026
Categories
- FastGPT
- AI Agents, Data & Retrieval, LLM Frameworks
- quilt
- Data & Retrieval
Trust and health
Days since push
- FastGPT
- 0d
- quilt
- 2d
Open issues (now)
- FastGPT
- 165
- quilt
- 143
Stars delta
- FastGPT
- +360 (30d)
- quilt
- Unknown
Open issues delta
- FastGPT
- +7 (30d)
- quilt
- Unknown
Full report
- FastGPT
- Trust report
- quilt
- Trust report
Choose FastGPT if…
- License: FastGPT is Other, quilt is Apache-2.0.
- Tags unique to FastGPT: agent, claude, deepseek, llm.
- Also covers AI Agents, LLM Frameworks.
- You prioritize ease of setup and configuration for advanced AI applications.
When NOT to use FastGPT
- If your needs extend beyond question-answering to other AI applications that require extensive customization which FastGPT does not natively support.
- When the level of customization for specific data processors or RAG methods is more critical than out-of-the-box functionality.
- Your use case requires a broader array of model integration, as FastGPT currently specializes in certain frameworks and may lack the depth needed for highly specialized models.
Choose quilt if…
- License: quilt is Apache-2.0, FastGPT is Other.
- Tags unique to quilt: data-engineering, data-version-control, data-versioning, parquet.
- When your team requires in-depth version control for complex scientific datasets, ensuring that every change to the dataset is tracked and documented.
When NOT to use quilt
- Not recommended if you prefer on-premises solutions over AWS-hosted services, as Quilt operates exclusively within the Amazon Web Services ecosystem.
- If your project involves handling simple and static datasets where traditional CVS tools suffice. The overhead of using a specialized solution like Quilt might not justify its use.
- Teams with limited experience in data engineering or with less sophisticated dataset requirements may find Quilt's robust features overly complex, potentially leading to underutilization.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (labring/FastGPT) · observed Aug 16, 2026
- GitHub forks (labring/FastGPT) · observed Aug 16, 2026
- Last push (labring/FastGPT) · observed Aug 16, 2026
- License file (Other) · observed Aug 16, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (quiltdata/quilt) · observed Aug 3, 2026
- GitHub forks (quiltdata/quilt) · observed Aug 3, 2026
- Last push (quiltdata/quilt) · observed Jul 31, 2026
- License file (Apache-2.0) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: FastGPT 29k · quilt 1.4k (synced Aug 16, 2026).
Common questions
- What is the difference between FastGPT and quilt?
- FastGPT: A knowledge-based platform built on LLMs for developing and deploying complex question-answering systems. quilt: Scientific Data Management Platform on AWS for managing data packages. See the comparison table for live GitHub stats and shared categories.
- When should I choose FastGPT over quilt?
- Choose FastGPT over quilt when License: FastGPT is Other, quilt is Apache-2.0; Tags unique to FastGPT: agent, claude, deepseek, llm; Also covers AI Agents, LLM Frameworks; You prioritize ease of setup and configuration for advanced AI applications.
- When should I choose quilt over FastGPT?
- Choose quilt over FastGPT when License: quilt is Apache-2.0, FastGPT is Other; Tags unique to quilt: data-engineering, data-version-control, data-versioning, parquet; When your team requires in-depth version control for complex scientific datasets, ensuring that every change to the dataset is tracked and documented.
- When should I avoid FastGPT?
- If your needs extend beyond question-answering to other AI applications that require extensive customization which FastGPT does not natively support. When the level of customization for specific data processors or RAG methods is more critical than out-of-the-box functionality. Your use case requires a broader array of model integration, as FastGPT currently specializes in certain frameworks and may lack the depth needed for highly specialized models.
- When should I avoid quilt?
- Not recommended if you prefer on-premises solutions over AWS-hosted services, as Quilt operates exclusively within the Amazon Web Services ecosystem. If your project involves handling simple and static datasets where traditional CVS tools suffice. The overhead of using a specialized solution like Quilt might not justify its use. Teams with limited experience in data engineering or with less sophisticated dataset requirements may find Quilt's robust features overly complex, potentially leading to underutilization.
- Is FastGPT or quilt more popular on GitHub?
- FastGPT has more GitHub stars (29,366 vs 1,367). Stars measure visibility, not whether either tool fits your constraints.
- Are FastGPT and quilt open source?
- Yes - both are open-source projects on GitHub (FastGPT: Other, quilt: Apache-2.0).
- Where can I find alternatives to FastGPT or quilt?
- GraphCanon lists graph-backed alternatives at FastGPT alternatives and quilt alternatives (FastGPT markdown twin, quilt 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, FastGPT or quilt?
- FastGPT: Very active. quilt: 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 FastGPT and quilt?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: FastGPT trust report; quilt trust report.