Home/Compare/DeepSeek-R1 vs katib

Comparison

DeepSeek-R1 vs katib

Verdict

Pick DeepSeek-R1 when license: DeepSeek-R1 is MIT, katib is Apache-2.0; pick katib when license: katib is Apache-2.0, DeepSeek-R1 is MIT.

Markdown twin · DeepSeek-R1 alternatives · katib alternatives

GraphCanon updated today

DeepSeek-R1 logo

DeepSeek-R1

deepseek-ai/DeepSeek-R1

92kpushed Jun 27, 2025
vs
katib logo

katib

kubeflow/katib

1.7kpushed Jul 10, 2026

Trust & integrity

SignalDeepSeek-R1katib
Maintenance
Dormant (379d since push)
As of today · github_public_v1
Very active (1d 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 1d · none
51 low (51 low)
As of today · osv@v1

Tagline

DeepSeek-R1
Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.
katib
Automated Machine Learning on Kubernetes

Stars

DeepSeek-R1
92k
katib
1.7k

Forks

DeepSeek-R1
12k
katib
532

Open issues

DeepSeek-R1
45
katib
110

Language

DeepSeek-R1
-
katib
Python

Adopt for

DeepSeek-R1
DeepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use.
katib
-

Persona

DeepSeek-R1
-
katib
-

Runtime

DeepSeek-R1
-
katib
-

License

DeepSeek-R1
MIT
katib
Apache-2.0

Last pushed

DeepSeek-R1
Jun 27, 2025
katib
Jul 10, 2026

Categories

DeepSeek-R1
LLM Frameworks, Model Training
katib
Developer Tools, LLM Frameworks, Model Training

Trust and health

Maintenance

DeepSeek-R1
Dormant (18%)
katib
Very active (96%)

Days since push

DeepSeek-R1
379d
katib
1d

Open issues (now)

DeepSeek-R1
45
katib
110

Security scan

DeepSeek-R1
No lockfile
katib
51 low (51 low)

Full report

DeepSeek-R1
Trust report

Choose DeepSeek-R1 if…

  • License: DeepSeek-R1 is MIT, katib is Apache-2.0.
  • Pricing: The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository..
  • Requirements: Min 4 GB RAM; This is a rough estimate based on common model requirements. Specific models within DeepSeek-R1 may have different resource needs..
  • Tags unique to DeepSeek-R1: commercial use, derived models, distilled models, mit license.
  • When you need to work with pre-trained models derived specifically from the Qwen-2.5 and Llama3.x series, benefiting from their unique characteristics.

When NOT to use DeepSeek-R1

  • Avoid if you need foundational models rather than distilled versions, as DeepSeek-R1 specializes in providing smaller, more efficient models suitable for resource-constrained environments.
  • If your project is tightly regulated or requires models from a different lineage, as DeepSeek-R1 exclusively provides derivatives of Qwen and LLaMA series.

Choose katib if…

  • License: katib is Apache-2.0, DeepSeek-R1 is MIT.
  • Tags unique to katib: ai, automl, huggingface, hyperparameter-tuning.
  • Also covers Developer Tools.

When NOT to use katib

  • Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
  • 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.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: DeepSeek-R1 92k · katib 1.7k (synced Jul 12, 2026).

Common questions

What is the difference between DeepSeek-R1 and katib?
DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. katib: Automated Machine Learning on Kubernetes. See the comparison table for live GitHub stats and shared categories.
When should I choose DeepSeek-R1 over katib?
Choose DeepSeek-R1 over katib when License: DeepSeek-R1 is MIT, katib is Apache-2.0; Pricing: The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository.; Requirements: Min 4 GB RAM; This is a rough estimate based on common model requirements. Specific models within DeepSeek-R1 may have different resource needs.; Tags unique to DeepSeek-R1: commercial use, derived models, distilled models, mit license; When you need to work with pre-trained models derived specifically from the Qwen-2.5 and Llama3.x series, benefiting from their unique characteristics.
When should I choose katib over DeepSeek-R1?
Choose katib over DeepSeek-R1 when License: katib is Apache-2.0, DeepSeek-R1 is MIT; Tags unique to katib: ai, automl, huggingface, hyperparameter-tuning; Also covers Developer Tools.
When should I avoid DeepSeek-R1?
Avoid if you need foundational models rather than distilled versions, as DeepSeek-R1 specializes in providing smaller, more efficient models suitable for resource-constrained environments. If your project is tightly regulated or requires models from a different lineage, as DeepSeek-R1 exclusively provides derivatives of Qwen and LLaMA series.
When should I avoid katib?
Developer Tools: A gateway is overkill when you're pinned to a single provider and model. 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.
Is DeepSeek-R1 or katib more popular on GitHub?
DeepSeek-R1 has more GitHub stars (91,991 vs 1,690). Stars measure visibility, not whether either tool fits your constraints.
Are DeepSeek-R1 and katib open source?
Yes - both are open-source projects on GitHub (DeepSeek-R1: MIT, katib: Apache-2.0).
Where can I find alternatives to DeepSeek-R1 or katib?
GraphCanon lists graph-backed alternatives at DeepSeek-R1 alternatives and katib alternatives (DeepSeek-R1 markdown twin, katib 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, DeepSeek-R1 or katib?
DeepSeek-R1: Dormant. katib: 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 DeepSeek-R1 and katib?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepSeek-R1 trust report; katib trust report.