Comparison
bisheng vs dify
Verdict
Pick bisheng if bISHENG is a comprehensive open-source LLM DevOps platform designed specifically for next-generation Enterprise AI applications; pick dify if dify is a platform for creating agentic workflows and RAG pipelines, supporting various AI models and tools, deployable on cloud, VPC, or self-hosted environments.
Markdown twin · bisheng alternatives · dify alternatives
GraphCanon updated Oct 4, 2026
8views this month
Trust & integrity
| Signal | bisheng | dify |
|---|---|---|
| Maintenance | Very active (0d since push) As of Aug 18, 2026 · github_public_v1 | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Aug 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No published findings from this source as of 2026-07-11 As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Oct 4, 2026 · 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
- bisheng
- BISHENG is an open LLM devops platform for next generation Enterprise AI applications
- dify
- Build Agentic workflows and RAG pipelines with rich AI model and tool support on one collaborative workspace.
Stars
- bisheng
- 12k
- dify
- 156k
Forks
- bisheng
- 1.9k
- dify
- 25k
Open issues
- bisheng
- 122
- dify
- 1.1k
Language
- bisheng
- Python
- dify
- TypeScript
Adopt for
- bisheng
- BISHENG is a comprehensive open-source LLM DevOps platform designed specifically for next-generation Enterprise AI applications.
- dify
- Dify is a platform for creating agentic workflows and RAG pipelines, supporting various AI models and tools, deployable on cloud, VPC, or self-hosted environments.
Persona
- bisheng
- -
- dify
- -
Runtime
- bisheng
- -
- dify
- -
License
- bisheng
- Apache-2.0
- dify
- Other
Last pushed
- bisheng
- Aug 18, 2026
- dify
- Sep 18, 2026
Categories
- bisheng
- AI Agents, Data & Retrieval, Developer Tools, Evaluation & Observability, LLM Frameworks, Model Training
- dify
- AI Agents, Data & Retrieval, Developer Tools
Trust and health
Open issues (now)
- bisheng
- 122
- dify
- 1.1k
Stars delta
- bisheng
- +348 (30d)
- dify
- +4.5k (30d)
Open issues delta
- bisheng
- +9 (30d)
- dify
- +172 (30d)
OSV dependency advisories
- bisheng
- No published findings from this source as of 2026-07-11
- dify
- No lockfile (source not queried)
Full report
- bisheng
- Trust report
- dify
- Trust report
Choose bisheng if…
- bisheng is primarily Python; dify is TypeScript.
- License: bisheng is Apache-2.0, dify is Other.
- Requirements: Min 16 GB RAM; Requires Docker.
- Tags unique to bisheng: chatbot, enterprise, finetune, genai.
- Also covers Evaluation & Observability, LLM Frameworks, Model Training.
- - When you need a unified solution that supports both GenAI workflows and RAG (Retrieval-Augmented Generation) capabilities, which are critical in enhancing the context understanding and response of L
When NOT to use bisheng
- - If your project requires minimal resource consumption and does not demand high enterprise-level system management or advanced observability features, BISHENG might be overkill given its hardware and
Choose dify if…
- dify is primarily TypeScript; bisheng is Python.
- License: dify is Other, bisheng is Apache-2.0.
- Tags unique to dify: agentic-ai, agentic-framework, agentic-workflow, automation.
- When you need a collaborative workspace that supports rich AI model and tool integration for agentic workflows and RAG pipelines.
When NOT to use dify
- If your project does not require agentic workflows or RAG pipelines, and you are looking for a more general-purpose AI development tool.
- When you need a platform that does not require Docker and Docker Compose for setup, as Dify's quick start guide assumes these prerequisites.
- If your team prefers a platform with a different licensing model, as Dify uses a modified Apache 2.0 license with additional conditions.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (dataelement/bisheng) · observed Sep 20, 2026
- GitHub forks (dataelement/bisheng) · observed Sep 20, 2026
- Last push (dataelement/bisheng) · observed Aug 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (langgenius/dify) · observed Sep 20, 2026
- GitHub forks (langgenius/dify) · observed Sep 20, 2026
- Last push (langgenius/dify) · observed Sep 18, 2026
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Oct 4, 2026
GitHub stars on cards: bisheng 12k · dify 156k (synced Sep 20, 2026).
Common questions
- What is the difference between bisheng and dify?
- bisheng: BISHENG is an open LLM devops platform for next generation Enterprise AI applications. dify: Build Agentic workflows and RAG pipelines with rich AI model and tool support on one collaborative workspace.. See the comparison table for live GitHub stats and shared categories.
- When should I choose bisheng over dify?
- Choose bisheng over dify when bisheng is primarily Python; dify is TypeScript; License: bisheng is Apache-2.0, dify is Other; Requirements: Min 16 GB RAM; Requires Docker; Tags unique to bisheng: chatbot, enterprise, finetune, genai; Also covers Evaluation & Observability, LLM Frameworks, Model Training; - When you need a unified solution that supports both GenAI workflows and RAG (Retrieval-Augmented Generation) capabilities, which are critical in enhancing the context understanding and response of L.
- When should I choose dify over bisheng?
- Choose dify over bisheng when dify is primarily TypeScript; bisheng is Python; License: dify is Other, bisheng is Apache-2.0; Tags unique to dify: agentic-ai, agentic-framework, agentic-workflow, automation; When you need a collaborative workspace that supports rich AI model and tool integration for agentic workflows and RAG pipelines.
- When should I avoid bisheng?
- - If your project requires minimal resource consumption and does not demand high enterprise-level system management or advanced observability features, BISHENG might be overkill given its hardware and
- When should I avoid dify?
- If your project does not require agentic workflows or RAG pipelines, and you are looking for a more general-purpose AI development tool. When you need a platform that does not require Docker and Docker Compose for setup, as Dify's quick start guide assumes these prerequisites. If your team prefers a platform with a different licensing model, as Dify uses a modified Apache 2.0 license with additional conditions.
- Is bisheng or dify more popular on GitHub?
- dify has more GitHub stars (156,243 vs 11,879). Stars measure visibility, not whether either tool fits your constraints.
- Are bisheng and dify open source?
- Yes - both are open-source projects on GitHub (bisheng: Apache-2.0, dify: Other).
- Where can I find alternatives to bisheng or dify?
- GraphCanon lists graph-backed alternatives at bisheng alternatives and dify alternatives (bisheng markdown twin, dify 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, bisheng or dify?
- bisheng: Very active. dify: 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 bisheng and dify?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: bisheng trust report; dify trust report.