Comparison
awesome-open-mlops vs langflow
Verdict
Pick awesome-open-mlops when license: awesome-open-mlops is Apache-2.0, langflow is MIT; pick langflow when license: langflow is MIT, awesome-open-mlops is Apache-2.0.
Markdown twin · awesome-open-mlops alternatives · langflow alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | awesome-open-mlops | langflow |
|---|---|---|
| Maintenance | Dormant (418d since push) As of today · github_public_v1 | Very active (0d 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) | No lockfile As of today · none | No criticals As of today · osv@v1 |
Tagline
- awesome-open-mlops
- The Fuzzy Labs guide to the universe of open source MLOps
- langflow
- Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
Stars
- awesome-open-mlops
- 482
- langflow
- 152k
Forks
- awesome-open-mlops
- 54
- langflow
- 9.7k
Open issues
- awesome-open-mlops
- 6
- langflow
- 975
Language
- awesome-open-mlops
- -
- langflow
- Python
Adopt for
- awesome-open-mlops
- -
- langflow
- Langflow specializes in creating and deploying AI agents and complex workflows through a versatile GUI-based approach.
Persona
- awesome-open-mlops
- -
- langflow
- -
Runtime
- awesome-open-mlops
- -
- langflow
- -
License
- awesome-open-mlops
- Apache-2.0
- langflow
- MIT
Last pushed
- awesome-open-mlops
- May 19, 2025
- langflow
- Jul 11, 2026
Categories
- awesome-open-mlops
- AI Agents, Model Training, Inference & Serving
- langflow
- AI Agents, Inference & Serving
Trust and health
Maintenance
- awesome-open-mlops
- Dormant (18%)
- langflow
- Very active (96%)
Days since push
- awesome-open-mlops
- 418d
- langflow
- 0d
Open issues (now)
- awesome-open-mlops
- 6
- langflow
- 975
Security scan
- awesome-open-mlops
- No lockfile
- langflow
- No criticals
Full report
- awesome-open-mlops
- Trust report
- langflow
- Trust report
Choose awesome-open-mlops if…
- License: awesome-open-mlops is Apache-2.0, langflow is MIT.
- Tags unique to awesome-open-mlops: machinelearning, datascience, machine-learning, mlops.
- Also covers Model Training.
When NOT to use awesome-open-mlops
- Last GitHub push was 418 days ago (dormant maintenance, May 19, 2025). Validate activity before betting a new project on awesome-open-mlops.
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
Choose langflow if…
- License: langflow is MIT, awesome-open-mlops is Apache-2.0.
- Tags unique to langflow: multiagent, agents, python, large-language-models.
- - When you need an intuitive graphical interface to manage the creation of AI agents and workflows without deep coding knowledge.
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
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (fuzzylabs/awesome-open-mlops) · observed Jul 11, 2026
- GitHub forks (fuzzylabs/awesome-open-mlops) · observed Jul 11, 2026
- Last push (fuzzylabs/awesome-open-mlops) · observed May 19, 2025
- License file (Apache-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (langflow-ai/langflow) · observed Jul 11, 2026
- GitHub forks (langflow-ai/langflow) · observed Jul 11, 2026
- Last push (langflow-ai/langflow) · observed Jul 11, 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: awesome-open-mlops 482 · langflow 152k (synced Jul 11, 2026).
Common questions
- What is the difference between awesome-open-mlops and langflow?
- awesome-open-mlops: The Fuzzy Labs guide to the universe of open source MLOps. langflow: Langflow is a powerful tool for building and deploying AI-powered agents and workflows.. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-open-mlops over langflow?
- Choose awesome-open-mlops over langflow when License: awesome-open-mlops is Apache-2.0, langflow is MIT; Tags unique to awesome-open-mlops: machinelearning, datascience, machine-learning, mlops; Also covers Model Training.
- When should I choose langflow over awesome-open-mlops?
- Choose langflow over awesome-open-mlops when License: langflow is MIT, awesome-open-mlops is Apache-2.0; Tags unique to langflow: multiagent, agents, python, large-language-models; - When you need an intuitive graphical interface to manage the creation of AI agents and workflows without deep coding knowledge.
- When should I avoid awesome-open-mlops?
- Last GitHub push was 418 days ago (dormant maintenance, May 19, 2025). Validate activity before betting a new project on awesome-open-mlops. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- 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
- Is awesome-open-mlops or langflow more popular on GitHub?
- langflow has more GitHub stars (151,697 vs 482). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-open-mlops and langflow open source?
- Yes - both are open-source projects on GitHub (awesome-open-mlops: Apache-2.0, langflow: MIT).
- Where can I find alternatives to awesome-open-mlops or langflow?
- GraphCanon lists graph-backed alternatives at awesome-open-mlops alternatives and langflow alternatives (awesome-open-mlops markdown twin, langflow 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, awesome-open-mlops or langflow?
- awesome-open-mlops: Dormant. langflow: 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 awesome-open-mlops and langflow?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-open-mlops trust report; langflow trust report.