Comparison
IndustryBench vs llm-app
Verdict
Pick IndustryBench when industryBench is primarily Python; llm-app is Jupyter Notebook; pick llm-app when llm-app is primarily Jupyter Notebook; IndustryBench is Python.
Markdown twin · IndustryBench alternatives · llm-app alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | IndustryBench | llm-app |
|---|---|---|
| Maintenance | Active (26d since push) As of today · github_public_v1 | Very active (5d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | 4 medium, 3 low (4 medium, 3 low) As of today · osv@v1 | No lockfile As of today · none |
Tagline
- IndustryBench
- A multi-lingual benchmark for evaluating industrial domain knowledge of LLMs.
- llm-app
- Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data.
Stars
- IndustryBench
- 155
- llm-app
- 59k
Forks
- IndustryBench
- 10
- llm-app
- 1.4k
Open issues
- IndustryBench
- 1
- llm-app
- 10
Language
- IndustryBench
- Python
- llm-app
- Jupyter Notebook
Adopt for
- IndustryBench
- -
- llm-app
- llm-app offers pre-configured cloud deployment templates designed specifically for creating AI-driven applications such as chatbots and machine learning projects leveraging Hugging Face models. It supports direct integrz
Persona
- IndustryBench
- -
- llm-app
- -
Runtime
- IndustryBench
- -
- llm-app
- -
License
- IndustryBench
- MIT
- llm-app
- MIT
Last pushed
- IndustryBench
- Jun 15, 2026
- llm-app
- Jul 5, 2026
Categories
- IndustryBench
- Data & Retrieval, LLM Frameworks, Model Training
- llm-app
- LLM Frameworks, Vector Databases, Data & Retrieval
Trust and health
Maintenance
- IndustryBench
- Active (82%)
- llm-app
- Very active (96%)
Days since push
- IndustryBench
- 26d
- llm-app
- 5d
Open issues (now)
- IndustryBench
- 1
- llm-app
- 10
Security scan
- IndustryBench
- 4 medium, 3 low (4 medium, 3 low)
- llm-app
- No lockfile
Full report
- IndustryBench
- Trust report
- llm-app
- Trust report
Choose IndustryBench if…
- IndustryBench is primarily Python; llm-app is Jupyter Notebook.
- Tags unique to IndustryBench: python, industry-benchmark, llm evaluation.
- Also covers Model Training.
When NOT to use IndustryBench
- Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Choose llm-app if…
- llm-app is primarily Jupyter Notebook; IndustryBench is Python.
- Requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others..
- Tags unique to llm-app: vector-database, llm, hugging-face, retrieval-augmented-generation.
- Also covers Vector Databases.
- - You need a ready-to-run solution that directly integrates with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and live APIs.
When NOT to use llm-app
- - You require custom deployment configurations that extend beyond the pre-set cloud templates available through llm-app.
- - There’s a need for tightly integrated support with data sources or APIs not explicitly mentioned, such as specialized CRM systems (Salesforce), which may lack direct template support in llm-app.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (alibaba-multimodal-industrial-ai/IndustryBench) · observed Jul 11, 2026
- GitHub forks (alibaba-multimodal-industrial-ai/IndustryBench) · observed Jul 11, 2026
- Last push (alibaba-multimodal-industrial-ai/IndustryBench) · observed Jun 15, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (pathwaycom/llm-app) · observed Jul 11, 2026
- GitHub forks (pathwaycom/llm-app) · observed Jul 11, 2026
- Last push (pathwaycom/llm-app) · observed Jul 5, 2026
- License file (MIT) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: IndustryBench 155 · llm-app 59k (synced Jul 11, 2026).
Common questions
- What is the difference between IndustryBench and llm-app?
- IndustryBench: A multi-lingual benchmark for evaluating industrial domain knowledge of LLMs.. llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data.. See the comparison table for live GitHub stats and shared categories.
- When should I choose IndustryBench over llm-app?
- Choose IndustryBench over llm-app when IndustryBench is primarily Python; llm-app is Jupyter Notebook; Tags unique to IndustryBench: python, industry-benchmark, llm evaluation; Also covers Model Training.
- When should I choose llm-app over IndustryBench?
- Choose llm-app over IndustryBench when llm-app is primarily Jupyter Notebook; IndustryBench is Python; Requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others.; Tags unique to llm-app: vector-database, llm, hugging-face, retrieval-augmented-generation; Also covers Vector Databases; - You need a ready-to-run solution that directly integrates with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and live APIs.
- When should I avoid IndustryBench?
- Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- When should I avoid llm-app?
- - You require custom deployment configurations that extend beyond the pre-set cloud templates available through llm-app. - There’s a need for tightly integrated support with data sources or APIs not explicitly mentioned, such as specialized CRM systems (Salesforce), which may lack direct template support in llm-app.
- Is IndustryBench or llm-app more popular on GitHub?
- llm-app has more GitHub stars (59,068 vs 155). Stars measure visibility, not whether either tool fits your constraints.
- Are IndustryBench and llm-app open source?
- Yes - both are open-source projects on GitHub (IndustryBench: MIT, llm-app: MIT).
- Where can I find alternatives to IndustryBench or llm-app?
- GraphCanon lists graph-backed alternatives at IndustryBench alternatives and llm-app alternatives (IndustryBench markdown twin, llm-app 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, IndustryBench or llm-app?
- IndustryBench: Active. llm-app: 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 IndustryBench and llm-app?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: IndustryBench trust report; llm-app trust report.